IoT Analytics released a new analysis, based on the ’Industrial IoT & Industry 4.0 Case Study Report 2023’.

Key insights:

• Digitalization has become essential for industrial companies worldwide, as IoT Analytics expects the industrial IoT market to reach $145 billion in 2023.
• The Industrial IoT and Industry 4.0 Case Studies Report 2023 delves into 22 case studies, exploring their project objectives, technologies deployed, lessons learned, challenges, and outcomes.
• In this article, we share five learnings from the report: 1) Upgrading the ERP is often the first step in digital transformation, 2) cloud-native data storage and streaming are coming up, 3) first successful implementations of private 5G use cases, 4) digitalization becoming a prerequisite to achieving sustainability, and 5) the continued journey toward predictive maintenance.

Key quotes:

Rajini Nair, Analyst at IoT Analytics, remarks: “Upon analyzing the case studies outlined in the report, it becomes evident that digitalization is a key catalyst driving technological progress in industrial settings. This includes the enhancement of ERP systems and the migration of data to cloud platforms equipped with real-time streaming capabilities. Furthermore, digitalization proves essential in harmonizing companies with their sustainability objectives. Strategies such as the implementation of predictive maintenance algorithms and the adoption of private industrial 5G use cases are leveraged to improve operational efficiency. Looking forward, the technological landscape is transforming with the rise of AI, poised to shape the future of manufacturing.”

Digitalization has become crucial to manufacturers globally

Digitalization has become crucial for manufacturers in their respective competitive landscapes. IoT Analytics estimates the industrial IoT market to reach $145B in 2023, with a CAGR of 17.9% until 2030, as more and more companies undertake digital transformation initiatives.

For many, digitalization has already become a game changer:

• Carmaker Mercedes has achieved 25% greater efficiency in its S-class assembly after optimizing the value chain and introducing innovative technologies at its Germany-based Factory 56 facility.
• Energy giant TotalEnergies aims to generate $1.5 billion annually in savings with its digital solutions by 2025.
• Chemical company Covestro increased efficiency and reduced unnecessary downtime by shifting from calendar-based to condition-based maintenance.

These are just some of the benefits of the digital transformation initiatives our research uncovered as part of the 255-page Industrial IoT and Industry 4.0 Case Studies Report 2023. The report delves into 22 recent industrial digital transformation case studies, looking at initiatives related to digital transformation, data architecture, predictive maintenance, AI, and industrial 5G.

Benefits of case studies for digitalization journeys

Case studies by peers or companies in other industries are a great way to learn about digitalization, identify common challenges, develop a view of best practices, and understand how companies manage to scale.

The 22 case studies in our report offer readers a diverse set of manufacturing examples of current IIoT and Industry 4.0 projects, along with project objectives and takeaways from each. Our analysis of these takeaways yielded many trends in these companies’ digital transformation journeys, five of which we will delve into in this article (including selected highlights from the report):

1. ERP: An upgraded ERP is often the first step to digital transformation.
2. Cloud: Cloud-native data storage and streaming are increasingly accepted.
3. 5G: First manufacturers have successfully implemented private 5G use cases.
4. Sustainability: Digitalization is becoming a prerequisite to achieving sustainability objectives.
5. Maintenance: The journey toward predictive maintenance and remote monitoring continues.

Learning 1: An upgraded ERP is often the first step to digital transformation

Our analysis found that many manufacturers elect to prioritize upgrading their ERP systems to ensure their various data sources are connected before prioritizing other digital transformation initiatives. Since ERP systems are often the central nervous system of a business, prioritizing an updated ERP allows different departments to share and operate on the same data, reducing errors and improving efficiency.

Selected highlight: Celanese

In recent years, US-based chemical manufacturer Celanese has acquired several businesses or divisions from other companies. Celanese had been operating on a legacy SAP ERP system, and the acquired assets had different legacy ERP environments, making cross-section integration difficult. Celanese’s global CIO, Sameer Purao, did not want the company to invest in integrating the new acquisitions into older technology. Given this situation and Celanese’s adoption of a strategic, long-term approach to a scalable digital transformation plan, an ERP upgrade became necessary.

“Our previous ERP system had been a backbone, but it was close to 20 years old. Given its age, we didn’t want to invest in transforming until we upgraded that piece first. The acquisitions underscored that it wouldn’t make sense to invest in integrating them into older technology, so we opted to upgrade.” – Sameer Purao, senior vice president and global CIO, Celanese Corporation

In May 2023, Celanese announced that it had completed its upgrade to SAP S/4HANA. Further, since Celanese acquired DuPont’s Mobility & Materials (M&M) business just six months prior, it quickly cutover to upgrading M&M’s legacy ERP system as well, which is expected to be completed in the first half of 2024.

While there are other major aspects of Celanese’s digital transformation journey detailed in our report, this upgrade to its ERP provided a stronger backbone from which other digitalization solutions could be built. Another benefit of this upgrade is improved visibility and collaboration, enhancing transparency and teamwork and allowing for efficient data access across the enterprise.

Learning 2: Cloud-native data storage and streaming are increasingly accepted

The cloud market nearly doubled between 2020 and 2022, growing from $109 billion to $206 billion, based on our analysis of global cloud projects. While the COVID-19 pandemic certainly played a major role, it was not the only growth factor. Our analysis found that large-scale enterprise digitalization efforts and strong SaaS adoption also helped fuel this growth.

Cloud storage and data streaming allow companies to centralize and share their data with a smaller footprint than running their own on-premises servers, which comes with footprint and maintenance costs. Moving these services to the cloud also allows companies to scale without the need for significant capital investment in physical hardware.

Selected highlight: Michelin

In 2019, tire manufacturer Michelin started using Apache’s Kafka event streaming platform on-premises in its data centers to gain real-time insights and process data as continuous streams. However, as its operational footprint expanded, so did the resources it had to dedicate to maintaining the solution. By Q4 2019, Michelin’s IT department initiated its migration to the cloud, with Microsoft Azure as the cloud partner.

“One of the challenges with [streaming technology] Kafka was its operational complexity, especially as the footprint expanded across our organization. It’s a complex, distributed system, so we had to allocate a lot of our valuable technical resources and expertise to babysit it and keep it running.” – – Olivier Jauze, now CTO of Experiences Business Line, Michelin

By 2021, Michelin migrated its services to Confluent Cloud for Azure, a Kafka-based platform, to support its multi-cloud environment. Soon after, the company began exploring use case projects and has since migrated one of its most critical projects, online order management, to the cloud—replacing its on-premises orchestrator. By 2023, Michelin expanded its cloud-based event streaming architecture into several departments, including supply chain management, customer services, manufacturing, and R&D.

Through its adoption of cloud-native data storage and streaming, Michelin achieved the following benefits (among other things):

• Cost savings: Estimated 35% in cost savings in the cloud compared to on-premises operations
• Improved uptime: 99.99% uptime

Learning 3: First manufacturers have successfully implemented private 5G use cases

As 5G continues its public rollout globally, some manufacturers have successfully deployed private 5G networks to enable new use cases within their facilities. While faster speeds and lower latency may seem like key adoption drivers, our analysis found that improved reliability over Wi-Fi, enhanced cybersecurity, and the ability to access data locally are the core motivating factors.

Our analysis also found that during the public rollout of 5G, some companies did not simply dive into integrating 5G-specific technology. Instead, many integrated robust LTE solutions that were upgradable to 5G with relative ease (or so-called 4.9G solutions) once the technology evolved or became approved for industrial use.

Selected highlight: Airbus

To increase aircraft production and validation efficiency, European multinational aerospace corporation Airbus partnered with Ericsson, a Swedish multinational telecommunications company, in 2021 to implement private industrial 5G networks at 11 aircraft assembly manufacturing sites in Europe. The approach began with implementing 4G networks that either already had 5G capabilities or could seamlessly upgrade to 5G.

However, Airbus is not limiting this deployment to its European facilities. During a Q&A at the 5G Manufacturing Forum in November 2022, Hakim Achouri, the 5G and IoT solutions expert for digital aviation at Airbus, noted, “Airbus is going way beyond 11 networks at 11 sites, expanding beyond its core European manufacturing bases in France and Germany, to also deploy private 5G in Canada, China, Spain, the UK, and the US.”

With its implementation of private 5G networks at its production and assembly facilities, Airbus has realized the following benefits:

• Ability to implement advanced use cases: This includes site surveillance, efficient flight-to-ground data offloads, quality inspections, and the operation of automated guided vehicles (AGVs).
• Enhanced user experience: With increased speed, bandwidth, and reliability, employees at the production sites have access to more data, making operations smoother, more efficient, and more secure.
• Scalability through reusability: By developing a pattern in its strategy, Airbus was able to roll out private 4G/5G networks across its many sites with consistent quality and performance.

Learning 4: Digitalization is becoming a prerequisite to achieving sustainability objectives

We recently noted a trend of companies deploying digital twins to help realize their sustainability goals. But it is not simply digital twins assisting companies on this front—digitalization projects overall are helping companies monitor energy consumption, optimize resource usage, and reduce their environmental footprint in the manufacturing process.
Backing this awareness and trend toward sustainability are data points from our latest What CEOs Talked About report, where “sustainability” and related terms remained among the most discussed topics in boardrooms.

Selected highlight: TotalEnergies

French multinational energy and petroleum company TotalEnergies has publicly declared its ambition to achieve carbon neutrality by 2050. To meet this goal, the energy company has leveraged digital solutions to advance the implementation of sustainability measures on its offshore platforms.

For instance, TotalEnergies retrofitted their pipes with LoRaWAN-connected temperature sensors to detect gas leaks along their flare networks. As hydrocarbons are released, the temperature of the pipes significantly changes. When this change is detected, operators are alerted via emails for immediate action. This not only helps limit the release of hydrocarbons but also saves TotalEnergies money by reducing the loss of product.

Learning 5: The journey toward predictive maintenance and remote monitoring continues

According to our Predictive Maintenance and Asset Performance Market Report 2023–2028 (published in November 2023), the predictive maintenance market reached $5.5 billion in 2022. While the report notes several tailwinds supporting this interest and market growth, such as skill shortages and interest in reducing energy usage and CO2 emissions, costs are a major driver, as noted in our case studies report as well.

Equipment failure, especially during core operational hours, reduces productivity and adds repair expenses. To avoid these costs, companies often use preventative maintenance procedures, such as time-based inspections and repairs or condition criteria from sensors or physical measurements to trigger preventative intervention. However, intervening based on time can be inefficient since the equipment may not be in need of repair at that time, and data collection/monitoring requires personnel to conduct these tasks.

By implementing digital solutions, companies can remotely monitor the condition of critical equipment and establish conditions in which intervention is actually needed well before failure occurs.

Selected highlight: Battalion Oil Corp

US-based Battalion Oil Corp partnered with Novity, a US-based predictive maintenance solutions company, to pilot a predictive maintenance solution to detect valve leaks within their compressors and reduce unexpected compressor downtime. Initially, Battalion would sporadically measure valve cap temperatures using handheld devices to identify potential gradual leaks that could lead to a failure. While the checks were intended to be conducted daily, varying daily maintenance tasks and priorities often disrupted these important checks.

“Predictive automation is a game-changer for the oil and gas industry. By analyzing data in real-time and making accurate predictions about future events, drilling companies can optimize their operations to maximize efficiency, reduce costs, and improve safety. This technology has the potential to transform the way we do business and stay competitive in today’s market.” – John Smith, CEO of Oil and Gas Exploration Company

An initial step in the solution was to use a crank angle sensor and pressure transducers. However, physical crank angle sensors are usually the most difficult and expensive sensors to install, so the engineers developed a virtual crank angle sensor based on physics-based and data-driven methods using data from the pressure sensors.

After validating that the rotational position calculated by the virtual sensors matched the position provided by the physical sensors, engineers applied prognostic methods to the data from the virtual crank angle sensor and physical pressure sensors. The result was predicted gradual valve failures several weeks in advance—five to seven days on average before temperature checks indicated a gradual leak.

The digital transformation journey carries on

The Industrial IoT and Industry 4.0 Case Studies Report 2023 delves further into the above-mentioned and 18 other case studies of ongoing digital transformation projections. While these companies and many others are advancing in their digital transformation journeys, there is still a long road ahead for many companies, some of which still rely on analog, pen-and-paper methods in their facilities. Even still, many companies are already experiencing real value, e.g., Mercedes’ achieving 25% greater efficiency and Battalion observing signs of gradual valve failures several weeks in advance.

Digitalization has become more than a nice-to-have for manufacturers today—it has become crucial for them in their respective competitive landscapes. The market reflects this assessment: according to our enterprise IoT market dashboard, the IIoT market size in 2023 is approximately $145 billion, with a forecasted CAGR of 17.9% between 2023 and 2030.

Looking ahead, AI continues to become a major theme in companies’ digital transformation initiatives. According to our continual series What CEOs Talked About, the topic and its related terms have already been of high and growing interest in boardrooms throughout 2023. We see a plethora of generative AI projects across the board, even in the industrial space (which we will report on soon). We will continue to monitor this space and highlight interesting case studies from adopters.

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In today’s interconnected world, the convergence of technology and industry has given rise to the Industrial Internet of Things (IIoT), a powerful force that is revolutionizing the way we operate, optimize, and innovate within various sectors. The IIoT, a subset of the broader Internet of Things (IoT), is reshaping industrial processes, enhancing productivity, and fostering new possibilities across a wide range of industries.

What is the Industrial Internet of Things?

The Industrial Internet of Things, often referred to as Industry 4.0, is the application of IoT technologies and concepts to the industrial sector. It involves the integration of smart sensors, data analytics, cloud computing, and machine-to-machine (M2M) communication into traditional industries, such as manufacturing, energy, transportation, and agriculture. These technologies enable the collection, analysis, and exchange of data to create more efficient and intelligent systems.

Key Components of IIoT

1. Sensors and Devices

At the core of IIoT are sensors and devices that collect data from the physical world. These devices are equipped with a variety of sensors, including temperature, pressure, motion, and more, which allow them to capture real-time information.

2. Connectivity

The data collected by sensors and devices is transmitted through various communication protocols such as Wi-Fi, Bluetooth, or cellular networks. This connectivity allows data to be sent to central servers or cloud platforms for analysis.

3. Data Analytics

Once the data is collected, it is processed and analyzed using powerful algorithms. Advanced analytics can uncover valuable insights, trends, and patterns that were previously hidden in the massive amounts of data generated.

4. Cloud Computing

Cloud platforms play a crucial role in IIoT, serving as the storage and processing hubs for the vast amounts of data generated. Cloud solutions enable real-time access to data, making it accessible to authorized stakeholders anywhere in the world.

5. Machine Learning and Artificial Intelligence

Machine learning and AI are integral to IIoT for predictive maintenance, anomaly detection, and process optimization. These technologies make it possible to respond to real-time data and automate decision-making.

Transforming Industries

The IIoT is transforming industries in various ways, leading to increased efficiency, improved safety, and a fundamental shift in business models.

1. Manufacturing

In the manufacturing sector, IIoT is revolutionizing production processes. Smart factories equipped with IIoT technologies can monitor equipment health, automate maintenance, and optimize production schedules. Real-time data analytics help manufacturers identify bottlenecks and inefficiencies, reducing downtime and waste. The result is increased productivity and cost savings.

2. Energy and Utilities

The energy and utilities sector is harnessing the power of IIoT to improve grid management, energy distribution, and asset maintenance. Smart meters and sensors allow for better monitoring of energy consumption, while predictive maintenance minimizes the risk of power outages. IIoT has the potential to significantly reduce energy waste and carbon emissions.

3. Transportation and Logistics

In the transportation and logistics industry, IIoT is improving supply chain visibility and efficiency. Fleet management systems equipped with IIoT devices can track vehicle location, monitor cargo conditions, and optimize delivery routes. This not only improves customer satisfaction but also reduces operational costs.

4. Agriculture

Agriculture is experiencing a digital transformation thanks to IIoT. Smart farming solutions utilize sensors and data analytics to monitor soil conditions, crop health, and weather patterns. This data helps farmers make informed decisions about irrigation, fertilization, and planting, ultimately increasing crop yields and reducing resource usage.

Challenges and Considerations

While the Industrial Internet of Things offers tremendous benefits, it also presents challenges that must be addressed:

1. Security and Privacy

The increased connectivity and data sharing in IIoT raise concerns about data security and privacy. Organizations must invest in robust cybersecurity measures to protect sensitive information from unauthorized access or cyberattacks.

2. Interoperability

With various devices and systems being integrated into IIoT ecosystems, ensuring interoperability between them can be complex. Standards and protocols must be established to facilitate seamless communication and data exchange.

3. Data Overload

The sheer volume of data generated by IIoT devices can be overwhelming. Organizations need to implement effective data management strategies to sift through the noise and focus on relevant information.

4. Workforce Training

The adoption of IIoT technologies requires a skilled workforce capable of managing and maintaining these systems. Investment in training and upskilling is necessary to harness the full potential of IIoT.

Future Trends of IIoT

The IIoT continues to evolve, and several key trends are shaping its future:

1. 5G Connectivity

The rollout of 5G networks promises faster and more reliable connectivity, enabling real-time data transmission and better support for IIoT applications.

2. Edge Computing

Edge computing, which involves processing data closer to the source, is gaining importance in IIoT. It reduces latency and can be crucial for applications that require rapid decision-making.

3. AI Integration

AI and machine learning will play an increasingly significant role in IIoT, providing intelligent insights and predictive capabilities to optimize industrial processes.

4. Sustainability

IIoT will contribute to sustainability efforts by improving resource management, reducing waste, and enhancing energy efficiency.

Conclusion

The Industrial Internet of Things is reshaping industries across the globe, unlocking new possibilities and revolutionizing the way we approach manufacturing, energy, transportation, and more. As organizations continue to invest in IIoT technologies, it is essential to address challenges related to security, interoperability, data management, and workforce training.

The future of IIoT looks promising, with advancements in 5G connectivity, edge computing, and AI integration. As the world becomes increasingly connected, the Industrial Internet of Things will continue to drive efficiency, innovation, and sustainability in a wide range of industries, ushering in a new era of digital transformation.

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IoT Analytics published a 217-page adoption report containing statistics on the current and future status of Industry 4.0 and smart manufacturing.

This research is based on the feedback from 500 decision makers in manufacturing organizations.

Key insights:

• A look at five key statistics shows that Industry 4.0 activity has risen since 2011, with COVID-19 and the 2022 slowdown presenting recent bumps on the road.
• The analysis considered five indicators: Public search interest, academic papers, startup funding, M&A activity, and enterprise adoption.

Key quotes:

• Dimitris Paraskevopoulos, analyst at IoT Analytics, says: “The concept of Industry 4.0 was introduced 11 years ago and first started as a vague concept to revolutionize manufacturing through “cyber-physical systems”. It has since become a mandatory part of most manufacturers’ strategy. Today, search interest has increased by 140 times and all signs point to the fact that interest in Industry 4.0 is still going strong.”

• Knud Lasse Lueth, CEO of IoT Analytics, adds:
  

  “Our latest research shows that industrial companies have further advanced on their digitization journey. The fact that 72% of manufacturers have an Industry 4.0 strategy in place is a clear indicator that adoption is happening, and Industry 4.0 is here to stay.”

The rise of Industry 4.0 in 5 stats

More than 10 years after its creation, it seems that Industry 4.0 is in full swing: Public search interest has risen 140 times since then, 50,000 research papers were published on the topic in 2021 alone, start-ups are now receiving a total of $3 billion in funding each year (Q3 2021 to Q3 2022), and M&A activity has doubled.

The term “Industry 4.0” was first publicly introduced at Hannover Fair 2011 by German Chancellor Angela Merkel who (as rumor has it) picked up the term, sparking a number of interesting discussions as a result.

What first started as a vague concept to revolutionize manufacturing through “cyber-physical systems” has since taken shape.

Some of the key advances since 2011 include:

• Much more powerful chipsets
• Widespread adoption of cloud services
• Containerization of software
• Creation of much-improved software middleware/tools
• Open interfaces to edge computing hardware
• New and improved communication standards/protocols
• Availability of relevant AI models and libraries

Few of these were obvious 10 years ago.

| “Industry 4.0” Definition
The use of modern I4.0 tech stack elements, or specific supporting technologies that enable manufacturers to integrate various data sources, achieve higher OEE, reduce costs, or improve other KPIs relevant to a production setup (manufacturing of goods, mining, oil, and gas) mostly in conjunction with rolling out new or improved use cases.

Here is a look at five key stats that show how “Industry 4.0” activity has changed since 2011:

#1 PUBLIC SEARCH INTEREST: 140 TIMES HIGHER

Searches for Industry 4.0 on Google in 2022 are 140 times higher compared to the year it was first introduced and made public (2011). In addition, related terms such as Industrial IoT and Smart Manufacturing grew quite fast in the same time frame as well (32 times and 3.5 times more searches respectively).

Industry 4.0 is an umbrella term that describes several advances in the manufacturing industry. The below picture shows how four of the supporting technologies for Industry 4.0 have also risen in popularity in the same time frame:

Search interests for “Cobots” increased more than 10 times since 2011, “Additive Manufacturing” almost nine times, “Digital Twin” more than four times, and “Machine Vision” 1.3 times. These supporting technologies are also representative of the interest in several other Industry 4.0-related technologies.

#2 ACADEMIC PAPERS: 200,000+ PAPERS PUBLISHED

More than 50,000 academic papers on Industry 4.0 were released in 2020 and 2021, and more than 200,000 have been published in total within the last 10 years. It is safe to say that a lot of research is being done on Industry 4.0. One of these ideas can be the “next big thing” that will move the topic forward.

Based on Google Scholar, the three most cited papers relating to Industry 4.0 are:

#3 FUNDING: 2,513 DEALS SINCE 2011

The annual funding of start-ups that are active in Industry 4.0 has increased by +319% from 2011 to 2021. 2021 saw a total of $2.2 billion of funding spent on upcoming companies that develop technology related to Industry 4.0. A total of 2,513 deals were announced in the 11-year time frame. The total number of funding rounds decreased when COVID-19 hit in 2020 and has also taken a hit as of late with the inflation and war-related slowdown.

Notable investment rounds included a $179 million Series A for BrightMachines in 2018, a $100 million Series C for Tulip Interfaces in 2021, and a $75 million Series E in Xometry in 2020.

#4 M&A ACTIVITY: DOUBLED FROM 2011 TO 2021

The annual number of Industry 4.0-related acquisitions reached a peak of 132 in 2021. This marks a 116% increase in the past 10 years. In the first three quarters of 2020, there were less than half
acquisitions compared to the usual average in the rest of the years. COVID-19 had a clear impact on the M&A activity as well.

Notable acquisitions included AspenTech acquired by Emerson for $11 billion in 2021, Fetch Robotics acquired by Zebra Technologies for $290 million in 2021, and IQMS acquired by Dassault Systèmes for $425 million in 2018.

#5 ENTERPRISE ADOPTION: MOST ORGANIZATIONS NOW HAVE AN INDUSTRY 4.0 STRATEGY

A 2015 World Economic Forum survey of 250 market leaders found that 88% of the participants did not understand the underlying business models and long-term implications of the industrial IoT to their industries

A 2019 Industry 4.0 adoption survey by IoT Analytics showed that the situation had changed with 25% of Industry 4.0 use cases already fully or extensively rolled out with enterprises on a global level.

The latest 2022 Industry 4.0 adoption survey now shows that companies have even further advanced. Companies that are not executing against an Industry 4.0 strategy are in the minority. A staggering 72% of the survey respondents report that they are in the process of implementing their Industry 4.0/Smart Factory with many initiatives in progress and some already completed.

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Combined Technology Empowers Enterprise Managers and Site Operators To Easily, Quickly, and Cost-Effectively Benefit from Industry 4.0.

Kerlink, a specialist in solutions dedicated to the Internet of Things (IoT), and Senzary, an industrial IoT service provider for end-to-end industrial solutions, today announced Kerlink’s hardware and software connectivity offers and Senzary’s IoTLogIQ platform are available in a single solution.

Senzary’s secure IoTLogIQ platform provides scalable, on-demand, real-time data processing, with advanced analytics, AI-enabled machine learning, and anomaly-detection solutions to help users plan and deploy their digital-transformation projects quickly and cost effectively.

Kerlink provides end-to-end connectivity solutions for designing, deploying, and operating public & private low-power/wide-area (LPWA) IoT networks. Its comprehensive product portfolio includes industrial-grade network equipment, best-of-breed network core, operations & management software, value-added applications, and expert professional services.

The combination of Kerlink’s Wanesy Management Center and Wirnet indoor/outdoor LoRaWAN® gateways with Senzary’s technology and IoTLogIQ’s end-to-end services provides the necessary elements for clients looking for a turnkey, professional solution, allowing them to focus on their business processes, and not on the technology.

“Our partnership provides integrators and enterprise customers with a complete solution, from sensors and gateways to an IoT platform, analytics, and machine learning, as a single, on-demand solution that can be deployed as cloud-based, edge-based, or a hybrid system,” said Josic Thepaut, sales manager Americas at Kerlink.

“Upon installation, site owners and enterprise managers can quickly achieve maximum visibility into their equipment or processes, along with receiving predictive failure alarms and utilization reports, by simply adding more sensors over time.”

Senzary’s IoTLogIQ platform thus enables plug-and-play solutions that solve every day industrial problems and tasks. These include predictive maintenance with RotaryIQ, energy management with PowerIQ, and water management with WaterIQ. Its end-to-end integration and pre-designed solutions allow for quick-to-market applications and pilots, enabling users to cost effectively embrace the full potential of industry 4.0 solutions.

“Industry 4.0 still has significant barriers, most of which are centered around sensors connecting to the network, secure communication, aggregated management, and then what to do with all this generated data,” said Senzary CEO Eric Schummer. “Organizations realize that for them to stay competitive, their equipment must become more connected to their businesses. Senzary’s IoTLogIQ and Kerlink’s connectivity technology working together pave the way for enterprise managers and site operators to have easier, quicker, and more cost-effective access to the reality of industry 4.0.”

Immediate benefits include aggregated information for operations, early warning of equipment failure, and timely reaction to critical events. These benefits increase companies’ ability to plan for and reduce downtime more effectively and manage the supply chain intelligently based on anticipated preventive maintenance, to avoid costly repairs.

“The direct benefits are increased productivity, positive EBITDA contributions, and improved on-site safety, among many others,” Schummer said.

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• More than 15,000 trackers and 250 antennas deployed at two key Safran Aircraft Engines production sites in France
• Using data from the trackers, Safran Aircraft Engines teams can remotely locate and manage all their tools and equipment in real time

Safran Aircraft Engines, a world-class aircraft engine manufacturer, was seeking a solution to optimize the tracking and management of its tools in large-scale production areas.

They needed a solution tailored to the specific metallic environment of the plants, and one that would not cause wave interference with the equipment within the industrial sites.

Orange Business Services was selected by Safran Aircraft Engines to equip two key production sites with its smart tracking IoT solution, which is based on an ecosystem of industry-leading partners specialized in geolocation technologies in industrial settings.

A Large-Scale, Customized Deployment

Using trackers, the solution makes it possible to accurately pinpoint locations within three meters in a complex environment. The trackers were placed on more than 15,000 specific tools, and 250 antennas were installed at two French plants: Villaroche and Saint-Quentin-en-Yvelines, which measure 55,000 and 20,000 square meters, respectively.

Centralizing Data to Improve Business Processes

The teams in the Villaroche and Saint-Quentin-en-Yvelines plants can utilize data from the trackers to find out where their tracked tools are located – remotely and in real time – with the help of an integrated software platform adapted by Orange Business Services.

With smart tracking, Safran Aircraft Engines benefits from a tailor-made, precise and reliable digital solution that also optimizes the management and preventive maintenance of its fleet of tools.

Christophe Blayo, Head of tooling for commercial engines assembling at Safran Aircraft Engines, explains:

“We have chosen Orange Business Services as our trusted partner to provide a new innovative solution in our Industry 4.0 factory and to address our business challenges.”

“The Orange teams’ commitment throughout the implementation of the entire project was crucial for developing the optimal solution and deploying it effectively.”

“We are delighted to support Safran Aircraft Engines with its geolocation project and digitalization of its processes. With our dual expertise as a carrier and an integrator, we draw on our ecosystem of partners to bring market-leading technologies together, allowing us to best meet our customers’ needs across the entire value chain. This IoT integration project illustrates our ability to deliver a large-scale industrial project, tackle all the challenges that come with it and adapt our solutions in partnership with an innovative company like Safran Aircraft Engines — all of which has a positive impact on its business,” says Emmanuel Routier, Vice President, Industry 4.0 at Orange Business Services.

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Putting machines to communicate with humans is a beauty called the internet-of-things. To put industrial machines to communicate is a breakthrough and perhaps the biggest of all we know. Since everyone is talking about 5G, it is equally important to discuss the optimal potential of the next-gen network bandwidth. In all honesty, industry 4.0 was an upcoming trend until the networking hassles were put to rest with the inception of private 5G networks.

They are pacing to touch USD 15.7 billion by 2026 at a CAGR of 79% and that’s huge. As a result, multiple IIoT applications that had waited for speedier networks are finally actualized to their optimal potential.

Why 5G is better for IIoT?

No matter 4G, networks have provided the needed start to the 4.0 revolution, it is time to upscale the strength and achieve bigger, better and speedier processes on the floor. For IIoT businesses, 5G is leaps & bounds ahead of 4G; the delay in sending/receiving data is 1 millisecond in 5G compared to 200 milliseconds in 4G. Now imagine the change for industries that work in highly agile environments such as FMCG, healthcare, etc. Moreover, 5G can connect up to a million devices per .38 square miles. This is 100 times more devices than 4G and a sure-shot boon for unifying private networks for cross-location units. Briefly, it can handle more volume of data at a greater speed yet lesser cost.

However, for industries, it means more than just fast internet.

The operational technology suite (OT) in an industrial setup uses a wide variety of networking technologies both fixed and mobile. To control and communicate with devices and floor processes, the software application has to stream data in real-time. For example, digital twins, automated production lines, remote monitoring through live videos, predictive maintenance etc. cannot perform in average networks. Their performance requirement is demanding and the usual Wi-Fi or LTE networks will not suffice.

5G bandwidths are strong enough to support automated guided vehicles (AGVs) at limited densities. To upscale the production, it can support a greater number of AGVs per service area. Others such as extended reality headsets are also making progress with the backing of faster streaming. Also known as data goggles, the emergency device helps maintenance engineers seek real-time insights into complicated industrial requirements. Not to miss, it ensures round-the-clock remote control of equipment and processes, no matter how complex the IIoT landscape is.

For any corporate setup, slicing is an integral strategy in the networking stack. Through virtualization, it is used to split the incoming network into multiple networks for distinctive customers. Moreover, no traffic from other networks would influence the quality of service on the particular slice. Just like a tenant on a cloud platform, slice obtains similar exclusivity. 5G network slicing makes it faster to enable or disable network fragments and create on-demand sub-networks for particular departments in an industrial setup.

5G is what big data has dreamt about. Over the years, organizations have built data management infrastructure to store, process and stream real-time analytics. Since IoT works closely with big data, 5G networking is a step ahead to implement edge computing. For industries, it is a trend in the making.

While we are at it, the omnipresence of the 5G private network should not be ignored.

Since most production units operate from different locations, it is essential that the network capacity in all the units is the same. floLIVE, for example, provides a private 5G networking solution to support a wide variety of use cases for small as well as global enterprises. So be it the network for a private campus, multiple campuses within a country or a cross-country service, their private network solution supports multiple RAN providers. The IoT solution is built over a Software-defined Connectivity (SDC) infrastructure to ensure flexibility and security.

Through pre-allocated IMSIs from an internal IMSI library, enterprises can avail multiple operators and yet create a unified private network for their enterprise. Working as a single private network, their platform simplifies cross-border regulatory compliance hassles. With an emphasis on performance, the cloud-native solution enables policies in line with enterprise verticals, staff safety, corporate security and confidentiality.

The solution resolves a key network infrastructure challenge for the industries – centralized management of the multisite & multi-facility with on-demand deployment options.

Conclusion

Industry 4.0 could never be a possibility without remote & predictive analysis of data. The ability to track using process and performance sensors and generate on-request insights in real-time is the very foundation of what we call smart industrialization today. Everything else that you know about IIoT is related in one way or the other. With the evolution of technology, remote monitoring in IIoT will become mainstream just like AI. The differentiator, however, will be the QoS in controlling the equipment anytime and from anywhere.

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• Amazon Monitron provides customers an end-to-end machine monitoring solution comprised of sensors, gateway, and machine learning service to detect abnormal equipment conditions that may require maintenance
• Amazon Lookout for Equipment gives customers with existing equipment sensors the ability to use AWS machine learning models to detect abnormal equipment behavior and enable predictive maintenance
• AWS Panorama Appliance enables customers with existing cameras in their industrial facilities with the ability to use computer vision to improve quality control and workplace safety
• AWS Panorama Software Development Kit (SDK) allows industrial camera manufacturers to embed computer vision capabilities in new cameras
• Amazon Lookout for Vision uses AWS-trained computer vision models on images and video streams to find anomalies and flaws in products or processes
• Axis, ADLINK Technology, BP, Deloitte, Fender, GE Healthcare, and Siemens Mobility among customers and partners using new AWS industrial machine learning services

Today at AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com company, announced Amazon Monitron, Amazon Lookout for Equipment, the AWS Panorama Appliance, the AWS Panorama SDK, and Amazon Lookout for Vision.

Together, these five new machine learning services help industrial and manufacturing customers embed intelligence in their production processes in order to improve operational efficiency, quality control, security, and workplace safety. The services combine sophisticated machine learning, sensor analysis, and computer vision capabilities to address common technical challenges faced by industrial customers, and represent the most comprehensive suite of cloud-to-edge industrial machine learning services available. This is why more than a hundred thousand customers are using AWS for machine learning, and why customers of all sizes and across all industries are using AWS services to make machine learning core to their business strategy.

Companies are increasingly looking to add machine learning capabilities to industrial environments, such as manufacturing facilities, fulfillment centers, and food processing plants. For these customers, data has become the connective tissue that holds their complex industrial systems together. Industrial systems typically have numerous interdependent processes that operate with small tolerances for error, and even minor issues can have major ramifications. Being able to analyze data about the equipment operating in their facilities helps customers address this challenge, and many customers have embraced services like AWS IoT SiteWise as a way to collect data and generate real-time performance metrics from their industrial equipment. As customers have begun to use the cloud to collect and analyze industrial data, they have also asked for new ways to incorporate machine learning to help make sense of the data and further drive operational efficiency. In some cases, customers want to use machine learning to help them realize the promise of predictive maintenance to reduce costs and improve operational efficiency. In other cases, customers running in disconnected or latency-sensitive environments want to use computer vision at the edge to spot product defects and improve workplace safety. With these evolving needs and opportunities, industrial companies have asked AWS to help them leverage the cloud, the industrial edge, and machine learning together to get even more value from the vast amounts of data being generated by their equipment.

Amazon Monitron and Amazon Lookout for Equipment enable predictive maintenance powered by machine learning

A major challenge facing industrial and manufacturing companies today is the ongoing maintenance of their equipment. Historically, most equipment maintenance is either reactive (after a machine breaks) or preventive (performed at regular intervals to ensure a machine doesn’t break). Reactive maintenance can result in significant costs and downtime, while preventive maintenance can be costly, result in over-maintenance, or fail to prevent breakdown if not performed often enough. Predictive maintenance (the ability to foresee when equipment is likely to need maintenance) is a more promising solution. However, in order to make it work, companies have historically needed skilled technicians and data scientists to piece together a complex solution from scratch. This included identifying and procuring the right type of sensors for the use case and connecting them together with an IoT gateway (a device that aggregates and transmits data). Companies then had to test the monitoring system and transfer the data to on-premises infrastructure or the cloud for processing. Only then could the data scientists on staff build machine learning models to analyze the data for patterns and anomalies, or create an alerting system when an outlier was detected. Some companies have invested heavily in installing sensors across their equipment and the necessary infrastructure for data connectivity, storage, analytics, and alerting. But even these companies typically use rudimentary data analytics and simple modeling approaches that are expensive and often ineffective at detecting abnormal conditions compared to advanced machine learning models. Most companies lack the expertise and staff to build and refine the machine learning models that would enable highly accurate predictive maintenance. As a result, few companies have been able to successfully implement predictive maintenance, and those that have done it are looking for ways to further leverage their investment, while also easing the burden of maintaining their homegrown solutions.

Here’s how the new AWS machine learning services can help:

• For customers who do not have an existing sensor network, Amazon Monitron offers an end-to-end machine monitoring system comprised of sensors, a gateway, and a machine learning service to detect anomalies and predict when industrial equipment will require maintenance. Amazon Monitron enables customers to remove cost and complexity from building a sophisticated, machine learning-driven predictive maintenance system from scratch, and it also allows them to focus on their core manufacturing, supply chain, and operations functions. Amazon Monitron detects when machines are not operating normally based on abnormal fluctuations in vibration or temperature, and notifies customers when to examine machinery in order to determine if preventative maintenance is needed. The end-to-end system includes IoT sensors to capture vibration and temperature data, a gateway to aggregate and transfer data to AWS, and a machine learning cloud service that can detect abnormal equipment patterns and deliver results in minutes with no machine learning or cloud experience required. With Amazon Monitron, maintenance technicians can start tracking machine health in a matter of hours, without any development work or specialized training. Amazon Monitron can be used on a variety of rotating equipment, such as bearings, motors, pumps, and conveyer belts in industrial and manufacturing settings. Use cases range from monitoring a few critical machines like the cooling fans or water pumps used in data centers, to large scale installations in manufacturing facilities with production and conveyance systems. Amazon Monitron also includes a mobile app for a customer’s onsite maintenance technicians to monitor equipment behavior in real time. With the mobile app, a technician can receive alerts of any abnormal equipment conditions across different machines, check up on the health of the machine, and decide if they need to schedule maintenance. To increase the accuracy of the system, technicians can enter feedback on the accuracy of the alerts in the mobile app, and Amazon Monitron learns from that feedback to continually improve over time. Amazon Monitron is now generally available.

• For customers that have existing sensors but don’t want to build machine learning models, Amazon Lookout for Equipment provides a way to send their sensor data to AWS to build models for them and return predictions to detect abnormal equipment behavior. To get started, customers upload their sensor data to Amazon Simple Storage Service (S3) and provide the S3 location to Amazon Lookout for Equipment. Amazon Lookout for Equipment can also pull data from AWS IoT SiteWise, and works seamlessly with other popular machine operations systems like OSIsoft. Amazon Lookout for Equipment analyzes the data, assesses normal or healthy patterns, and then uses the learnings from all of the data on which it is trained to build a model that is customized for the customer’s environment. Amazon Lookout for Equipment can then use the machine learning model to analyze incoming sensor data and identify early warning signs for machine failure. This allows customers to do predictive maintenance, saving them money and improving productivity by preventing the crash of an industrial system line. Amazon Lookout for Equipment allows customers to get more value from their existing sensors, and it helps customers make timely decisions that can materially improve the entire industrial process.

AWS Panorama uses computer vision to improve industrial operations and workplace safety

Many industrial and manufacturing customers want to be able to use computer vision on live video feeds of their facility and equipment to automate monitoring or visual inspection tasks and to make decisions in real time. For example, customers routinely need to inspect high-speed processes to determine if adjustments are needed (e.g. fine milling or laser tooling), to monitor site and yard activity to ensure operating compliance (e.g. ensure pedestrians and forklifts remain in designated work zones), or to assess worker safety within their facilities (e.g. appropriate social distancing or use of PPE). However, the typical monitoring methods used today are manual, error prone, and difficult to scale. Customers could build computer vision models in the cloud to monitor and analyze their live video feeds, but industrial processes typically need to be physically located in remote and isolated places, where connectivity can be slow, expensive, or completely non-existent. This problem is even more difficult for industrial processes that involve manual review like quality checks on manufactured parts or security feeds. For example, if a quality issue emerges on a high throughput production line, customers want to know immediately because the costs of letting the problem persist is steep. This type of video feed could be automatically processed in the cloud using computer vision, but video feeds are high bandwidth and can be slow to upload. As a result, customers are required to monitor video feeds in real time, which is hard to do, error prone, and expensive. While there is a desire to use smart cameras that have enough processing power to run these models, getting low latency performance with good accuracy from these cameras can be challenging. Most customers end up running unsophisticated models that can’t be programmed to run custom code that integrates into the industrial machines.

Here’s how AWS can now help:

• The AWS Panorama Appliance provides a new hardware appliance that allows organizations to add computer vision to existing on-premises cameras that customers may already have deployed. Customers start by connecting the AWS Panorama Appliance to their network, and the device automatically identifies camera streams and starts interacting with the existing industrial cameras. The AWS Panorama Appliance is integrated with AWS machine learning services and IoT services that can be used to build custom machine learning models or ingest video for more refined analysis. The AWS Panorama Appliance extends AWS machine learning to the edge to help customers make predictions locally in sites without connectivity. Each AWS Panorama Appliance can run computer vision models on multiple camera streams in parallel, making possible use cases like quality control, part identification, and workplace safety. The AWS Panorama Appliance works with AWS and third party pre-trained computer vision models for retail, manufacturing, construction, and other industries. Also, customer-developed computer vision models developed in Amazon SageMaker can be deployed on the AWS Panorama Appliance.

• The AWS Panorama Software Development Kit (SDK) enables hardware vendors to build new cameras that can run meaningful computer vision models at the edge. Cameras that are built with the AWS Panorama SDK run computer vision models for use cases like detecting damaged parts on a fast-moving conveyor belt or spotting when machinery is outside of a designated work zone. These cameras can use chips designed for computer vision from NVIDIA and Ambarella. By using the AWS Panorama SDK, manufacturers can build cameras with computer vision models that can process higher quality video with better resolution for spotting issues. They can also build more sophisticated models on low-cost devices that can be powered over Ethernet and placed around a site. Customers can train their own models in Amazon SageMaker and deploy them on cameras built with the AWS Panorama SDK with a single click. Customers can also add Lambda functions to cameras built with the AWS Panorama SDK to be alerted to potential issues via text or email. AWS also offers pre-built models for tasks like PPE detection and social distancing, and can deploy these models in minutes without doing any machine learning work or special optimizations.

Amazon Lookout for Vision offers automated fast and accurate visual anomaly detection for images and video at a low cost

One use case where AWS customers are excited to deploy computer vision with their cameras is for quality control. Industrial companies must maintain constant diligence to maintain quality control. In the manufacturing industry alone, production line shutdowns due to overlooked errors result in millions of dollars of cost overruns and lost revenue every year. The visual inspection of industrial processes typically requires human inspection, which can be tedious and inconsistent. Computer vision brings the speed and accuracy needed to identify defects consistently, but implementation can be complex and require teams of data scientists to build, deploy, and manage the machine learning models. Because of these barriers, machine learning-powered visual anomaly systems remain out of reach for the vast majority of companies.

Here’s how AWS can now help these companies:

• Amazon Lookout for Vision offers customers a high accuracy, low-cost anomaly detection solution that uses machine learning to process thousands of images an hour to spot defects and anomalies. Customers send camera images to Amazon Lookout for Vision in batch or in real-time to identify anomalies, such as a crack in a machine part, a dent in a panel, an irregular shape, or an incorrect color on a product. Amazon Lookout for Vision then reports the images that differ from the baseline so that appropriate action can be taken. Amazon Lookout for Vision is sophisticated enough to handle variances in camera angle, pose, and lighting arising from changes in work environments. As a result, customers can accurately and consistently assess machine parts or manufactured products by providing as few as 30 images of the baseline “good” state. Amazon Lookout for Vision also runs on Amazon Panorama appliances. Customers can run Amazon Lookout for Vision in AWS starting today, and beginning next year, customers will be able to run Amazon Lookout for Vision on AWS Panorama Appliances and other AWS Panorama devices so customers will be able to use Amazon Lookout for Vision in locations where Internet connectivity is limited or non-existent.

“Industrial and manufacturing customers are constantly under pressure from their shareholders, customers, governments, and competitors to reduce costs, improve quality, and maintain compliance. These organizations would like to use the cloud and machine learning to help them automate processes and augment human capabilities across their operations, but building these systems can be error prone, complex, time consuming, and expensive,” said Swami Sivasubramanian, Vice President of Amazon Machine Learning for AWS.

“We’re excited to bring customers five new machine learning services purpose-built for industrial use that are easy to install, deploy, and get up and running quickly and that connect the cloud to the edge to help deliver the smart factories of the future for our industrial customers.”

The post AWS Announces Five Industrial Machine Learning Services appeared first on IoT Business News.

The COVID-19 pandemic and the US-China trade friction have failed to slow Thailand’s resilient electronics and electrical (E&E) industry which on the contrary many investors see as a haven, Thailand Board of Investment (BOI) data shows.

In the first nine months of 2020, the number of foreign and domestic companies which applied to invest in Thailand’s E&E sector actually rose to 106 projects, from 94 projects in the same period in 2019, making it by far the most popular sector, totaling over $1.2 billion in investment applications submitted to the BOI.

With a supply chain of some 2,500 companies and 800,000 employees ranging from researchers with doctoral degrees to vocationally trained technicians and experienced assembly line workers, it is the country’s largest manufacturing employer, according to Thailand’s Electrical and Electronics Institute (EEI).

“E&E is fundamental to Thailand 4.0“, said EEI president Narat Rujirat, referring to the innovation-driven growth strategy of Southeast Asia’s second largest economy.

This ambitious vision involves creating a regional hub for futuristic industries including medical devices, electric vehicles, robotics and automation. At its heart is the technological transformation of one of Thailand’s long-established core industries, electrical and electronics, into what is today termed “Smart E&E” and the emergence of the so-called Internet of Things (IOT).

Thailand’s E&E sector has burgeoned into a global powerhouse and is the world’s second largest exporter of computer hard disc drives, air conditioners and washing machines, according to GSB Research, a unit of Thailand’s largest state-owned bank.

Foreign investors success stories in Thailand’s fast evolving E&E sector are numerous.

Back in 2002, New York-listed Benchmark Electronics Inc. paid $45 million for the Thailand and U.K. operations of an American competitor. Today, Benchmark’s Thailand unit accounts for one-fifth of the company’s $2.3 billion global revenues after morphing into a manufacturer of such sophisticated, high value-added products as surgical lasers, defibrillators and optical sensing technology for electric vehicles.

“The Thai acquisition was an excellent decision,” Mr Ronald Rocha, Benchmark’s Asia Vice President for Electrical Manufacturing Systems, said at the unit’s headquarters in the appropriately named Hi-Tech Industrial Estate north of Bangkok.

“In the past, companies would go to countries like Thailand just to reduce cost. We are here because of capability, technology and quality as well as the low-cost advantage. The government is industry friendly, there is a high emphasis on education and the workforce is very stable. Growth for us has been nonstop.”

Delta Electronics Inc., a Taiwan-based multinational that is one of the world’s leading manufacturers of power supplies and electronics fans that are essential to cool computers, smart phones, home appliances and, increasingly, medical devices and electric vehicles, first opened a factory in Bangkok in 1988 and in 1995 listed its local subsidiary on the Stock Exchange of Thailand.

Today, Delta Electronics (Thailand) employs 12,000 people and accounts for $1.6 billion, or about 18 percent, of the group’s $9 billion global revenues. Bangkok is the regional headquarters for all Delta’s operations in Southeast Asia, India and Australasia and the Thailand business oversees research and development hubs in Bangkok, India, the U.S. and Germany. Next year it plans to expand further by opening a third factory in Thailand.

“As an investor we really wanted to find a country that can give you confidence for the long term and that is why we chose Thailand,” says Delta Thailand President Jackie Chang. “It is also very good for logistics, such as air and sea freight, and the people can adapt easily to different cultures.”

Other global giants with presence in Thailand include Daikin, Mitsubishi, Sony and Toshiba of Japan, LG and Samsung of Korea, Bosch and Siemens of Germany, Seagate and Western Digital of the U.S. The sector also includes local champions such as chip designer Silicon Craft and ThaiGerTec, a Thai-German joint venture that designs and develops microelectronics, powerelectronics and embedded systems for the automotive industry.

In total, Thailand’s E&E industry generates $56.5 billion worth of exports in 2019, or 24 percent of total exports, according Thailand’s Ministry of Commerce and GSB Research.

In addition to a strong supply chain and skilled human resources, Thailand’s attraction for E&E investors also stems from its strategic geographical location at the crossroads of Asia, which has enabled it to become one of the world’s top exporters.

Investors also benefit from privileges offered by the BOI. E&E companies focused on innovation and research and development can receive tax breaks of up to 8 years and other incentives such as renewable smart visas of up to four years for international talent and investors in key sectors such as smart electronics, as well as their families. The BOI also supports companies by helping establish industrial linkage, sourcing of local suppliers and business matching. Many companies have developed strong partnerships with local academic institutions.

Similarly, both Benchmark Electronics Inc. and Delta Electronics (Thailand) are upbeat about the prospects for Thailand’s E&E sector. “We have a lot to look forward to,” says Mr Rocha. “Next year and 2022 are going to be pretty big for us. We are increasing our investment and the BOI is going to be a big part of what we do here.”

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• 74% of manufacturing decision-makers surveyed plan to upgrade comms and control networks in next two years to advance digital transformation and Industry 4.0
• More than 90% are investigating use of 4G/5G for their operations
• 84% that are considering 4G/5G will deploy their own local private wireless network in their manufacturing operations

Nokia has partnered with ABI Research, an independent research firm, to survey more than 600 manufacturing decision-makers to assess investment strategies related to 4G/LTE, 5G and Industry 4.0.¹

The survey found that 74% of respondents are looking to upgrade their communications and control networks by the end of 2022 with more than 90% investigating the use of either 4G and/or 5G in their operations. Just over half of respondents (52%) believe that the latest generation of 4G/LTE and 5G will be necessary to meet their transformational goals.

The research also identified key business use cases that would drive investment in 4G or 5G. Respondents reflected the need to digitalize and improve existing infrastructure (63%), automation with robotics (51%) and achieve new levels of employee productivity (42%).

Manish Gulyani, Vice President Marketing, Nokia Enterprise said:

“We have reached an inflection point in Industry 4.0 transformation as the fast, secure, low latency connectivity underpinning its implementation now becomes available. This research indicates the strong marketplace appetite for industrial-grade wireless networking to capture the transformational benefits of digitalization and automation. We believe that demand, combined with easy-to-deploy private wireless solutions, will drive adoption.”

The research examined near-term drivers influencing buying decisions for new industrial systems across IT (information technology) and OT (operations technology). IT drivers primarily focus on reducing downtime (53%), improving operations efficiency (42%), and enhancing security (36%). In comparison, OT drivers reflect a desire to replace aging infrastructure (43%), improve efficiency (40%) and increase capacity (38%).

Further highlights indicate:

• 88% of respondents stated that they were familiar with private wireless (4G/5G) networking
• 84% that are considering 4G/5G will deploy their own local private wireless network in their manufacturing operations
• leading priority buying areas are automation and machine upgrades (47%), IIoT initiatives (41%), with cloud infrastructure following at (37%).

Ryan Martin, Principal Analyst, ABI Research said:
“Importantly, research findings indicate a preference for deploying private fully-owned and operated wireless networks, with manufacturers favoring in-house management to allay security concerns. It’s evident that respondents are not entirely committed to Wi-Fi/WLAN and will consider latest generations of wireless technologies. As a result, 2020 is a critical year for networking suppliers to educate the market regarding the merits of 4G/LTE and 5G.”

“Based on this research we also observe a pan-industry need to quantify not only the potential ROI of investing in private wireless, but also to clearly indicate the cost of inaction – vendors need to make the case for investing in Industry 4.0 today to gain a clear competitive advantage over those who choose to wait.”

The post Nokia and ABI Research identify key trends in manufacturing investment to enable Industry 4.0 appeared first on IoT Business News.

Public agencies across the world warn that flushing wipes cause major sewer infrastructure issues at wastewater treatment facilities, creating a significant public health risk.

Sewage systems are impacted as consumers flush disinfectant wipes, paper towels, and napkins, an unintended consequence of the COVID-19 pandemic.

Wipes get caught on misaligned pipe joints choking sewer lines and wrapping around pump motors, causing clogs, excessive strain, and infrastructure damage. These clogs can result in overflows of raw sewage into local rivers and lakes, and creating backups into people’s homes. Significant blockages often require municipal staff to clear them, at a time when efforts and tax dollars need to be focused on critical services.

“Wastewater treatment facilities around the state already are reporting issues with their sewer management collection systems,” the California State Water Board said in a statement. “Wipes are among the leading causes of sewer system backups, impacting sewer system and treatment plant pumps and treatment systems.”

myDevices, the IoT Solutions company, and éolane, the leader in electronic industrial services and connected solutions, announces the launch of BOB Assistant by éolane, the first predictive maintenance solution for industrial equipment with embedded artificial intelligence that utilizes LoRa® Technology.

The predictive maintenance solution gathers data related to the performance of equipment such as sewage pumps, providing insight into the machine’s current health, helping predict future breakdowns. It serves various industries in manufacturing, automotive, energy, oil, gas, and building & facility management.

This powerful industrial IoT solution optimizes machine maintenance schedules and service logistics, helping ensure uptime and reduce costs by decreasing traditional onsite visual inspections with 24/7 remote monitoring. Place the sensor directly on machines, and it will learn and analyze the natural vibration patterns for that specific machine in that specific environment over a 7-day learning period. After the machine learning is complete, the solution will send SMS and email alerts if the sensor detects anomalies that exceed the threshold of the established baseline.

myDevices’ IoT solutions have been developed from edge to cloud to meet the highest security standards. Combining the built-in security of the LoRaWAN protocol with Microsoft’s Azure IoT Hub, our Predictive Maintenance solution provides secure and reliable communication between the IoT application and the BOB Assistant by éolane sensors, it manages with per-device authentication, built-in device management, and scaled provisioning.

BOB Assistant by éolane is:

• Intelligent: After the baseline is established, the sensor applies analysis algorithms to the data and alerts staff of potential issues.
• Visual: View machines’ operating status on the web dashboard and mobile app, including total runtime, anomaly reporting, and access to reports.
• Simple: It takes zero infrastructure, zero wiring, and zero configuration to install. The sensor is placed on the equipment and works independently for several years.
• Connected: LoRaWAN® technology provides maximum coverage across the entire facility regardless of its physical environment, with minimal energy consumption and long battery life.
• Secured: Your equipment production data is safe with BOB Assistant by éolane. It retains it and sends only end-to-end AES encrypted scan reports to the cloud.

“Water treatment facilities are facing an increase in sewage pump clogs posing an additional public health risk amidst the COVID-19 pandemic,” said Kevin Bromber, CEO & Founder of myDevices.

“The financial cost of downtime can be significant and hurts the bottom line. With the myDevices and BOB Assistant by éolane solution, facilities with industrial machines can go from costly corrective maintenance to preventative and predictive maintenance.”

“We designed the BOB Assistant by éolane sensor, with embedded artificial intelligence, to enable mechanical performance optimization and energy savings,” said Henri Juin, CEO of éolane. “We know well the many Industry 4.0 challenges to implement predictive maintenance and created BOB Assistant by éolane to simplify its deployment. No wires, it’s off-network, and requires zero configuration to make it the industries’ first autonomous predictive maintenance solution.”

“BOB Assistant by éolane attached to our plant equipment has become a vital addition to our team,” said Hervé Benhammou, Technical Project Engineer at Véolia. “The solution notifies our team before major machine malfunctions. A perfect example was our wastewater treatment plant in Angers where we were alerted to a drift with an agitator sludge digestor machine. Our maintenance team was able to intervene on time to maintain the injection of biogas into the network. It was critical to keep the machine functioning properly but provided time and cost savings.”

BOB Assistant by éolane Predictive Maintenance and other myDevices’ Plug & Play solutions are available through Sprint Business, as well as a growing network of channel partners.

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For many firms, the outbreak of COVID-19 has meant staff working from home and more use of teleconferencing rather than face to face meetings. However, it’s a different situation for manufacturers because, despite investments in automation, reducing the need for staff on assembly lines, they still need to receive raw materials.

The impact of Coronavirus is both global and unpredictable, and the supply chain shock it is causing will most definitely and substantially cut into the worldwide manufacturing revenue of US$15 trillion currently forecasted for 2020 by global tech market advisory firm, ABI Research.

The virus will have both short- and long-term ramifications for manufacturers. “Initially, plant managers and factory owners will be looking to secure supplies and be getting an appreciation of constraints further up the supply chain plus how much influence they have on their suppliers,” explains Michael Larner, Principal Analyst at ABI Research.

In the longer term, manufacturers will need to conduct an extensive due diligence process as they need to understand their risk exposure, including the operations of their supplier’s suppliers too.

“To mitigate supply chain risks, manufacturers should not only not source components from a single supplier but also, as COVID-19 has highlighted, shouldn’t source from suppliers in a single location,” Larner advises.

In software applications in the manufacturing setting, ABI Research forecasts that the supply chain impact of Covid-19 will spur manufacturer’s spend on enterprise resource planning (ERP) to reach US$14 billion in 2024. While many ERP platforms include modules for inventory control and supply chain management, in light of the outbreak, many manufacturers will also turn to specialist providers.

Larner adds, “Supply chain orchestration requires software to be more than a system of record and provide risk analysis and run simulations, enabling manufacturers to understand and prepare for supply chain shocks.”

Industry 4.0 has received much attention; however, the focus has been on the activities inside the factory gates.

Larner concludes:

“But investments in robotics or IoT sensors and the like assume that assembly lines receive a steady flow of raw materials. COVID-19 demonstrates that manufacturers need to be as focused on their supplier’s capabilities as they are on their factory floor.”

The post Coronavirus Outbreak Reveals the Weakest Links in the Supply Chain – The Supplier’s Supplier appeared first on IoT Business News.

Opportunities abound equally for the manufacturing sector and technology vendors.

Technology investments in the industrial and manufacturing sector are set to skyrocket, jumping from US$59 billion in 2019 to US$375 billion in 2030.

Including hardware revenues, that figure climbs to over US$1 trillion, according to data from global tech market advisory firm, ABI Research.

Manufacturing is in the midst of a major digital revolution and is investing in Industrial Internet of Things (IIoT) technologies like Artificial Intelligence (AI), Augmented Reality (AR), robotics (AGVS, AMRs) and cloud-based simulation and modeling.

Ryan Martin, Principal Analyst, Industrial & Manufacturing, at ABI Research, says:

“The transformative shift toward Industry 4.0 technologies and the broader field of software-defined manufacturing (SDM) presents a massive opportunity for a wide range of technology providers and implementers.”

Intelligently connected hardware represents the largest share of revenue, growing from US$200 billion in 2019 to a staggering US$800 billion in 2030, but will diminish in proportion as associated software and services take hold. After hardware, data and analytic services is the fastest growing segment in terms of revenue generation, reaching more than US$185 billion in 2030, up from just US$11 billion in 2019.

“As the amount of custom code required to deploy new solutions on the factory floor drops, data and analytic service revenue growth in smart manufacturing will accelerate,” Martin explains.

Machine tools, asset tracking, and connected PLCs will experience the most growth in terms of connected service revenue over the next 10 years. By 2030, machine tools such as 3D printers, computer numerical control (CNC) machines, lathes, mills and industrial drills, will grow in revenues to US$134 billion; asset tracking will reach US$78 billion, and Connected Programmable Logic Controllers (PLCs) will hit US$40 billion.

According to Martin:
“Industry 4.0 is creating millions of new end points that need to be interconnected. However, the existing infrastructure can’t support it, which is creating an opportunity for connectivity experts and providers to step in.”

Currently, there are 260 million digital factory connections, with 230 million of those connections made via a fixed line. But, by 2023, a vast number of the 5.5 billion digital factory connections will be wireless. “This is driven by the rise in newly connected endpoints, including sensors, mobile robots (AGVs, AMRs), advanced asset tracking (RTLS), condition-based monitoring, and predictive maintenance applications, etc.,” says Martin.

The leading industries driving these revenues overall include automotive, heavy machinery, food, beverage, tobacco products, and electronics. And, though Industry 4.0 is a global phenomenon, roughly half of the global revenue opportunities will be concentrated in China and the United States, followed by Germany and Japan. Furthermore, the United States leads the way in most industries such as automotive, while China leads in machinery, nonmetallic mineral products, primary metals, and textiles.

“There is a long and compelling list of digital transformation technologies and pilot projects that are now graduating to the factory floor. The companies and production environments embracing these opportunities have quickly seen the benefits and want to scale, rather than risk falling behind,” concluded Martin.

The post Digital Factory Revenues to Jump to US$375 Billion in 2030 appeared first on IoT Business News.

The Industry Marketplace will Leverage IOTA’s Distributed Ledger Technology, the Tangle, to Automate Interconnectivity Between Machines and Machine Readable Contracts, to Advance Digital Transformation.

The IOTA Foundation announced the launch of the ‘Industry Marketplace’, the world’s first decentralized marketplace which will automate the trading of physical and digital goods and services.

The next generation of industrial automation, Industry 4.0 (I4.0), is rapidly approaching. In tomorrow’s world, devices will contain not only asset information, but proactive decision and optimization algorithms to enable goal-oriented behavior among their components. Such I4.0 devices can be viewed as autonomous independent economic agents that cooperate according to market economy principles. The highly flexible value creation networks that result from I4.0 will require new forms of collaboration between companies – both at the national and global level.

The successful implementation of I4.0 will depend on the creation of a common global communication and computing infrastructure that allows economic relationships between machines. By combining the latest technology with established standards and openly-developed specifications, the Industry Marketplace will provide this platform and enable the economy of things.

“The Industry Marketplace paves the way for secure automated trade in the manufacturing sector,” said Holger Köther, Director of Partnerships of the IOTA Foundation. “The use of the IOTA Tangle, an open-source distributed ledger technology that is feeless and scalable, ensures stability and robustness for the Marketplace and its participants. We are now looking forward to expand the circle of participants, demonstrate the Marketplace under near-production conditions and continue its development with our industry partners.”

The Industry Marketplace will serve as a vendor- and industry-neutral platform, automating the trading of physical and digital goods and services. Building on specifications developed by the Plattform Industrie 4.0 (Germany’s central network for the advancement of digital transformation in manufacturing), the Industry Marketplace combines distributed ledger technology and immutable audit logs. This is through eCl@ss standardized, machine-readable contracts with an integrated decentralized identity system, to ensure the authenticity of all participants and enable secure communication and payments across the industry landscape.

The Industry Marketplace has been developed as an open-source initiative and is free to join. Open innovation with other industry partners to explore new business models and the many possibilities of industrial automation is encouraged.

Key Features include:

• Vendor- and industry-neutral platform and communication
• Standardized communication for contracts, product data, purchasing, bids, orders, services
• Implementation of the Industry Platform 4.0 principles for driving forward digitalization and manufacturing
• Semantic language, based on open standards, developed by Platform Industrie 4.0 and academic institutes, as well as industrial non-profit organizations such as eCl@ss
• Decentralized and globally accessible protocol with paramount security
• Low system requirements
• Integrated decentralized ID, to ensure the authenticity of all participants
• Integrated payment option for goods and services, without transaction fees
• Payment Queue to execute outgoing payments in high frequent environments, e.g. buying many individual data sets, like weather data
• Immutable audit log for every step (including payments) to be compliant with regulatory aspects, digital trust as design principle through the IOTA Tangle

Thorsten Kroke, Head of Digital Processes & Standards, eCl@ss, said:

“The industry marketplace is designed to solve the current issues around creating a common standard language for autonomous machine to machine communication. This is an essential aspect of Industry 4.0, where secure data exchange without the loss of key information for decision making are foundational requirements.”

“The IOTA decentralized identity system is capable of solving an industrial need right now: identifying physical devices. Identity is a prerequisite to attach an Asset Administration Shell to a physical device,” said Jörg Nagel, Managing Director, Neoception. “The DID used by the Industry Marketplace may seem futuristic to some, but it solves a real problem for the industry, by providing globally unique IDs.”

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• E&K Automation GmbH, Konica Minolta and Endress+Hauser on board
• Campus networks with new functions for industry 4.0
• Telekom ecosystem around 5G for industry continues to grow

Deutsche Telekom is further expanding its 5G ecosystem for the industry.

In addition to the partnership with network supplier Ericsson, specialists for smart production and development are also joining the team. New partners are EK Automation, Konica Minolta and Endress+Hauser.

New functions for industry 4.0

With its campus networks, Telekom is the first network operator to offer an infrastructure for the smart factory of tomorrow. The business models and thus the requirements vary greatly from industry to industry.

To meet these needs, Deutsche Telekom counts on integrating existing technologies into the 5G infrastructure. This creates new solutions and opportunities for industry. Typical application areas for these technologies are production or logistics:

• Automated guided vehicle systems (AGVs) already support logistics processes on company premises today. They are now connected to the local IT system via a campus network. This significantly improves the mobile connection, e.g. compared to WiFi. And the use of so-called edge solutions significantly increases the computing power of the AGVs. An Edge Cloud shifts complex computing processes from a remote data center to a computer on the factory premises. Data is processed faster in this way. The vehicles can react to obstacles in real time.

• Augmented reality glasses are already being used by industry today. Especially when service personnel maintain machines and support the back office via video call. Such functions require high data rates: And they need a stable and fast connection. This minimizes reaction times and ensures a high level of convenience during use. A clear case for 5G.

• Industrial measurement technology is used for the safe and reliable control of systems. But it also provides valuable information for optimizing production and operational processes. In a campus network, this data is reliably transmitted and processed in the shortest possible time.

“Our development of a complete 5G ecosystem for industry will accelerate the pace of digitization in industry. This will strengthen Germany’s position in global competition,” emphasizes Claudia Nemat, Board member for Technology and Innovation at Deutsche Telekom. “We enjoy working with renowned and experienced partners. More and more industries are being added. In this way, our offering is becoming increasingly complete.”

Strong partners for smart production

Each partner contributes with specific know-how from the field of Industry 4.0.

EK Automation GmbH joined the Telekom partners in July. It has been manufacturing automated guided vehicle systems since 1980. As one of the European AGV market leaders, the partner is experienced in complex customer projects. Together with the Telekom incubator Hubraum, the company equipped transport robots with 3D cameras this summer. For the first time, the technicians integrated a 3D obstacle detection with dynamic route planning into the Edge Cloud. The transport robot sends the 3D camera images to the cloud for analysis almost in real time via the Telekom 5G network. This enabled the vehicle to immediately avoid obstacles placed in the roadway.

Jan Drömer explains:

“The new 5G mobile communications standard with data rates of more than one gigabit per second opens up new possibilities for us. For example, we can coordinate many transport robots in this way.”

The CIO of EK Automation went on to say: “We will jointly push the use of AGVs for efficient production”.

Konica Minolta has over 140 years of experience in optical systems. Together with Deutsche Telekom, the company is further developing its AIRe Lens. This lightweight augmented reality glasses helps a technician, for example, to assemble machines. It shows step-by-step instructions on the display. The technician keeps his hands free. He can also show the situation to an expert at a remote location. A camera is integrated in the glasses for this purpose. In the future, AIRe Lens will deliver data directly via Telekom’s 5G network.

“In combination with Telekom’s network, AIRe Lens enables us to offer our customers a wearable AR solution,” says Ikuo Nakagawa. The Senior Executive Officer, Digital Workplace Business Unit, Konica Minolta, Inc. explains: “The AR glasses help our customers to make their production processes more efficient. At the same time, it increases the speed and quality of manufacturing.”

Endress+Hauser is a global leader in measurement and automation technology. The company will be one of the first manufacturers to equip its sensors with mobile radio modules. Thanks to 5G, numerous measuring devices can transmit a wealth of process and device data in parallel and in real time. These can, for example, be evaluated in cloud applications for predictive plant maintenance.

“In addition to the actual measured values, our instruments have long recorded a wealth of information from the process and about the sensor. So far, however, this data has hardly been used,” says Matthias Altendorf. The CEO of the Endress+Hauser Group adds: “The 5G campus networks open a second signal path that is independent of the control system. This enables us to link value chains more closely across company boundaries and make industrial processes more efficient”.

Further partners are already in the starting blocks to make Telekom’s campus networks even more versatile. In the medium term, the company wants to be able to respond to the special needs of all industries.

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AI-Enabled Industrial Analytics Solutions Optimize Machine, Production and Quality Outcomes for Manufacturing 4.0.

Hitachi Vantara today announced Lumada Manufacturing Insights, a suite of industrial internet-of-things (IoT) solutions that empower the manufacturing industry to achieve transformative outcomes from data-driven insights.

Using artificial intelligence (AI), machine learning (ML) and DataOps, Lumada Manufacturing Insights optimizes machine, production and quality outcomes to set the foundation of digital innovation that is essential to Manufacturing 4.0.

“Data and analytics have the power to modernize and transform manufacturing operations. But for too many manufacturers today, legacy infrastructure and disconnected software and processes slow innovation and impact competitive advantage,” said Brad Surak, chief product and strategy officer at Hitachi Vantara.

“With Lumada Manufacturing Insights, customers can lay a foundation for digital innovation that works with the systems and software they have already to operationalize immediate gains in uptime, efficiency and quality and transform for the future.”

Accelerate Manufacturing Transformations

Lumada Manufacturing Insights applies data science rigor to drive continuous improvement opportunities based on predictive and prescriptive analytics. The solution integrates with existing applications and delivers actionable insights without the need for a rip-and-replace change of costly manufacturing equipment or applications. Lumada Manufacturing Insights supports a variety of deployment options and can run on-premises or in the cloud.

“With Hitachi Vantara, our customers benefit from our deep operational technology expertise and distinctive approach to co-creating with them to accelerate their digital journey,” said Bobby Soni, chief solutions and services officer at Hitachi Vantara.

“With our proven methodologies and advanced tools, we can tailor solutions for our customers that enhance productivity, increase the speed of delivery, and ultimately deliver greater business outcomes.”

Providing machine, production and quality analytics, Lumada Manufacturing Insights drives transformational business outcomes by enabling customers to:

• Build on the intelligent manufacturing maturity model and empower the digital innovation foundation for continuous process improvement.
• Integrate data silos and stranded assets and augment data from video, lidar and other advanced sensors to drive innovative new use cases for competitive advantage.
• Drive 4M (machine, man, material and methods) correlations for root-cause analysis at scale.
• Evaluate overall equipment effectiveness (OEE) and enhancement recommendations based on advanced AI and ML techniques.
• Evaluate scheduling efficiency and optimize for varying workloads, rates of production and workorder backlogs.
• Monitor and guide product quality with predictive and prescriptive insights.
• Improve precision of demand forecast and adherence to production plans and output.

“The big challenge for manufacturers is how to effectively manage the cost, resources and market pressures of supporting use cases for the immediate now and the transformative future,” said Mike Guilfoyle, director of research at ARC Advisory Group.

“Doing so requires a portfolio approach to transformation and a digital innovation foundation that is platform agnostic, secure and edge-to-multicloud capable. This is central to Manufacturing 4.0, and helps manufacturers accelerate time to value as they grow their digital competency.”

Early Adopters See Initial Benefits

“Significant short-lead products have to be designed, prototyped and delivered to meet the demands of our customers and partners as we accelerate the product supply for 5G. Ericsson and Hitachi Vantara have collaborated to test Lumada Manufacturing Insights to gear up for an anticipated increase in new product introductions, establishing a digital innovation foundation for sustained gains,” said Shannon Lucas, head of customer unit emerging business for Ericsson North America.

“We are leveraging the same solution that we will take to our joint customers in partnership with Hitachi Vantara, and will further expand IIoT use cases based on our 5G technologies.”

“As a progressive manufacturer, our focus was to accelerate transformative change, eliminate data silos and build a foundation for digital innovation that would accelerate our journey toward Manufacturing 4.0. We leveraged the IIoT workshop to align our use cases with our business transformation priorities and have a roadmap for success with Lumada Manufacturing Insights,” said Vijay Kamineni, business transformation leader at Logan Aluminum.

“The collaboration with Hitachi Vantara enables us to define business goals for each stage of our transformation, with clear outcomes that we believe will accelerate gains in productivity, quality, safety and sustainable manufacturing. Hitachi Vantara brings a unique IT/OT advantage that will help us in the long run.”

“Humans and machines working together to deliver the vision of ‘digital drilling’ is driven by our ambition to achieve transformative outcomes, drilling our best wells every time and consistently achieving Target Zero for accidents. With Hitachi Vantara, we are realizing time to value with industrial analytics and the powerful Lumada platform to process more than 20,000 data streams per second per rig, providing actionable information to the right people at the right time and helping make optimal decisions. This drives our operational excellence and consequently our competitive advantage,” said Shuja Goraya, CTO at Precision Drilling Corporation.

“We’re leveraging insights from video and lidar, integrating it with Lumada Manufacturing Insights to deliver business outcomes. It’s driving process optimization through effectively identifying improvement opportunities and shortening well delivery times for our customers. It’s all about effective use of data to make better decisions and then being able to consistently execute on these learnings. We are excited about our strategic partnership with Hitachi Vantara.”

Availability

Lumada Manufacturing Insights will be available worldwide Sept. 30, 2019.

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Automotive 5G manufacturing production is now a reality for German electric microcar company e.GO Mobile AG at its Aachen complex, enabled by 5G connectivity from Ericsson and Vodafone Germany.

In e.GO’s Factory 1, where the e.GO Life model is manufactured, an Ericsson Private Networks solution – spanning 5G Core and 5G New Radio solutions from Ericsson’s 5G Platform – will deliver secure and almost real-time data networking across the production chain, from digital material management to autonomous vehicle control.

Incorporating network slicing and mobile edge computing technologies, which are already in place, the optimized on-site network spans 36 antennas in the 8,500 sqm facility, delivering gigabit bandwidth and latency of just a few milliseconds. Ericsson 5G Radio Dots will be installed in the factory by the end of August.

The secure automatic identification and delivery of production materials to each specific vehicle as it goes through the assembly process, alongside fully autonomous vehicles replacing the traditional production line to move vehicles from station to station, increases operational speed and efficiency across the chain.

In the future, autonomous forklift trucks and small trains will also be used to transport material between warehouses and the production hall.

Günther Schuh, CEO, e.GO Mobile AG, says the 5G network will deliver faster and more reliable production with constant access to relevant information.

He says:

“The assembly plant for e.GO Life is a true Industry 4.0 factory. In other words, it is fully networked in terms of information technology. Connectivity links the physical and the digital world.”

Hannes Ametsreiter, Head of Vodafone Germany, says:
“Our automotive industry needs a fast network directly where the newest and most innovative cars are built. Data is an important fuel for modern automobile production.”

Arun Bansal, President and Head of Europe & Latin America, Ericsson, says:
“5G is the key to opening the door to a new era in manufacturing productivity, speed, security and efficiency – and the automotive industry is a prime example of the beneficiaries. Our 5G technology leadership, including solutions and abilities specifically tailored to manufacturing, enables us to partner with companies such as Vodafone and e.GO to deliver the very best private networks solutions.”

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The fourth industrial revolution, dubbed Industry 4.0, holds a promise in addressing the inefficiencies in traditional manufacturing by the application of disruptive technologies, says GlobalData, a leading data and analytics company.

Industry 4.0 is simply the next phase in the digital transformation of manufacturing through the use of data exchange techniques, advanced technologies and flexible automation for increased efficiency. It principally aims at enhanced human-machine interaction to drive interconnectivity, information transparency and autonomous decision making.

Kiran Raj, Disruptive Tech Analyst at GlobalData, comments: “Industry 4.0 is increasingly gaining importance in manufacturing owing to its capability in marrying operational technology with information technology to build a cyber-physical production system that can deliver higher-quality products at lower costs.”

An analysis of GlobalData’s Disruptor Tech Database reveals five technologies in Industry 4.0 as crucial in transforming the industrial manufacturing: big data and analytics (BDA), industrial internet of things (IIoT), cloud computing, additive manufacturing (3D printing) and augmented reality (AR). Others include advanced robotics, digital twinning, simulation, cyber security, artificial intelligence (AI) and blockchain.

BDA plays a remarkable role in the manufacturing environment by collecting and analyzing huge volumes of data coming from management systems and sensors fitted to the production equipment. It allows free up humans with machines in tiresome and dangerous tasks, thereby increasing efficiency as well as safety.

Mining giant Rio Tinto leveraged BDA and avoided the unexpected break down of its production vehicles estimated to cost up to US$2m. Its so-called autonomous haulage system (AHS) has close to 200 sensors producing more than 4TB of valuable vehicle data per day, including exact location, speed and other real-time metrics, across the fleet of 900 AHS.

From product prototyping to mass production of custom tooling, the advancement in 3D printing is phenomenal and opened up numerous possibilities for production.

German carmaker Volkswagen became the first manufacturer ready to use the latest 3D printing technology for mass production in the automotive industry. The technology named HP Metal Jet has been tested to increase productivity up to 50 times compared to the existing 3D printing methods based on the component.

Raj continues:

“Industry 4.0 can empower building what many refer to as ‘smart factory’ for a truly productive environment with benefits to manufacturers as well as consumers such as enhanced communication, real-time monitoring, advanced data analysis and self-diagnosis.”

Ideally, a smart factory is flexibly automated and self-monitoring where machines, materials and humans communicate with each other, sparing workers for other productive tasks and ultimately optimizing the design and production processes for elevated operational efficiency.

Beneath the layers, however, there are critical challenges for manufacturers such as data management, upskilling employees and cyber incidents for which fortunately there are steps and preventive measures without impacting production.

Raj concludes: “While incumbents, such as Bosch, GE and Siemens, have been muscling to capture a sizeable share of Industry 4.0, many manufacturers are yet to consider serious investments. Given the benefits over threats, a wait and watch stance may risk their competitive position in the future of manufacturing.”

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ABB and Ericsson today strengthened their long-standing relationship with the signing of a Memorandum of Understanding (MoU).

The collaboration enhances their joint vision for the future of flexible production with advanced automation and wireless communication.

• Complementary technologies and experiences will accelerate the industrial ecosystem to realize the benefits of Industry 4.0 and 5G, unlocking new business opportunities

• Intelligent automation system deployed at Ericsson’s manufacturing facilities in Tallinn, Estonia uses fully automated flexible robotics cell solution from ABB

ABB and Ericsson have strengthened their commitment to accelerate the industrial ecosystem for flexible wireless automation, which will enable enhanced connected services, industrial IoT and artificial intelligence technologies in the future.

The partners signed a Memorandum of Understanding at Hannover Messe 2019, establishing their joint vision for future flexible production with automation and wireless communication. The collaboration comes during the Industry 4.0 era and 5G connectivity which allow businesses to realize increased productivity, with the help of automation and digitalization.

The MoU confirms the partners’ agreement to continue their strong research collaboration, explore improvements in manufacturing processes and automation, and discover new business opportunities for the industrial ecosystem.

“We are very excited to extend our partnership with Ericsson as the world moves closer to the era of 5G technology,” said ABB CEO Ulrich Spiesshofer.

“ABB’s leadership in digital industries combined with Ericsson’s pioneering work in connectivity will open up new opportunities for customers to enhance productivity and competitiveness by digitalizing their businesses.”

“Ericsson and ABB already have a strong collaboration in research for 5G and Industrial IoT technologies,” Börje Ekholm, President and CEO, Ericsson said. “With this MoU, we strengthen our partnership to accelerate the industrial ecosystem and realize the full potential of flexible automation, unlocking new business opportunities enabled by combining 5G and Industry 4.0.”

The two partners are already fast-tracking the introduction of a new generation of intelligent factory technologies, with Ericsson deploying an intelligent automation system at its manufacturing facilities in Tallinn, Estonia. ABB has provided a fully automated flexible robotics cell solution that assembles 5G radios for Ericsson.

At the Hannover Messe 2019, ABB and Ericsson are exhibiting their latest and most innovative technologies and showcasing how they are enabling the “factory of the future” with the latest flexible robotics, wireless technologies, 5G, Industrial IoT and motion control technology.

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Ericsson has launched Ericsson Industry Connect, an easy-to-use cellular connectivity solution to accelerate Industry 4.0 digital transformation.

Ericsson Industry Connect enables communication service providers to offer dedicated cellular networks at factories and warehouses starting with 4G/LTE, with a clear path to 5G.

The offering strengthens Ericsson’s private networks and IoT portfolios by making 4G and 5G technologies accessible to new industrial markets.

Purpose-built for industrial environments such as factories and warehouses, the dedicated cellular connectivity solution enables secure, reliable coverage with high device density and predictable latency.

With a network management experience designed to be easy to use and manage for information technology (IT) and operational technology (OT) professionals, the solution aims to make cellular technology rapidly deployable for factory and warehouse staff.

With industrial-grade wireless connectivity, Ericsson Industry Connect can enable innovative Industry 4.0 use cases such as: digital twin inspection (a real-time digital replica of a physical entity) with massive amounts of sensors; mobility for human machine interface (HMI) instructions for workers; collision avoidance and remote control for autonomous guided vehicles (AGVs); and collaborative robotics for automated operations.

Åsa Tamsons, Senior Vice President, Head of Business Area Technologies and New Businesses, Ericsson, says:
“Ericsson Industry Connect is built on design thinking to meet industrial customers’ requirements on speed, reliability and security, while being easy to install and manage. It helps enterprises to accelerate their automation and operational efficiency to the next level. It complements service providers’ offerings to enterprises with a solution that is easy to scale. Ericsson Industry Connect increases the relevance of cellular solutions in the high growing segment of industrial connectivity – leveraging Ericsson’s technology leadership, strength in connectivity, and R&D investments to date.”

Swedish provider of transport solutions, Scania has already implemented Ericsson Industry Connect in its smart production lab in Södertälje, Sweden.

Roger Hartonen, Senior Manager Industrial IT, Scania Group, says:
“High quality, fast, and secure connectivity of our industrial environment is now an absolute must for us. Ericsson Industry Connect gives us reliable wireless connectivity which will enable flexibility for us on the factory floor. At Scania, we are driving the shift toward sustainable transport by continuously innovating our manufacturing processes.”

Pierce Owen, Principal Analyst, ABI Research, says:

“The technology case for private LTE has existed for some time now, but with Industry Connect, Ericsson has productized that technology in a way that empowers implementers and operators to deliver the benefits of private LTE to factories and warehouses with a real business case.”

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• 5G commercial services targeted to launch nationwide in early April 2019

• Mobile broadband subscribers to be initial beneficiaries

• National and global IoT and Industry 4.0 opportunities to be explored

KT (formerly known as Korea Telecom) has awarded Ericsson a 5G commercial contract to enable the nationwide launch of commercial 5G services in Korea starting early April 2019.

Korean operators have joined forces to target early April 2019 as the go-live date for the world’s first nationwide provision of 5G commercial services in time to support commercially available 5G smartphones. KT’s planned nationwide 5G network plays a central role.

Under this initial commercial contract – the first since Ericsson was selected as a 5G supplier to KT in November 2018 – Ericsson is providing 3GPP standards-based 5G New Radio (NR) hardware and software from Ericsson’s complete 5G platform to cover KT’s 3.5 GHz Non-Standalone (NSA) network.

Korean consumers are known as early adopters of technology such as advances in mobility, gaming, streaming, infotainment, and interactive functionality. All of these require large, and rapidly growing, amounts of data and bandwidth.

Such KT subscribers, with 5G smartphones, are set to be among the first globally to benefit from the enhanced mobile broadband enabled by 5G through seamless and ultra-low latency user experiences.

In addition to immersive media, KT’s 5G commercialization use case plans covers: smart factories, safety, drones, and connected vehicles.

Ericsson 5G can also enable KT to open up Internet of Things (IoT) and Industry 4.0 opportunities to Korean enterprises on a global scale.

Jinho Choi, Vice President, Access Network Design, KT, says:
“Having worked successfully with Ericsson on 4G LTE, we are pleased to continue that partnership to make our 5G ambitions a reality with Ericsson’s leading 5G technology.”

“Korea is one of the most competitive and technology-advanced markets in the world. By taking a global lead to enable nationwide commercial 5G services through commercially available 5G smartphones, KT is demonstrating our commitment to our customers and showing how we can drive a global 5G ecosystem where Korea plays a key role.”

Patrick Johansson, Head of Ericsson Korea, says:
“We’ve worked with KT for many years to bring the very best mobile user experiences to its customers. Notably on 5G, we worked closely together to show the world what 5G could do during a major global winter sports event in 2018.”

“With 5G we aim to help KT to take their customers’ experiences to new levels, whether through enhanced mobile broadband for mobile subscribers, or helping to make national and global IoT and Industry 4.0 opportunities a reality for enterprises and industries.”

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5G Americas Report Details 5G Communications for Automation in Vertical Domains.

The rationale for the development of the 5th generation of mobile communications (5G) was not only to expand the broadband capabilities of mobile networks, but also to provide advanced wireless connectivity for a wide variety of vertical industries, such as the manufacturing, automotive and agricultural sectors. The fourth stage of the Industrial Revolution, also termed “Industry 4.0”, is the next era in industrial production, which will be largely dependent upon advanced mobile wireless communications connectivity.

5G Americas, the industry trade association and voice of 5G and LTE for the Americas, today announced the publication of 5G Communications for Automation in Vertical Domains, summarizing automation concepts and communication modeling for vertical domains incorporating the key specific use cases, requirements and security mechanisms.

Communication for automation in vertical domains comes with demanding and diverse requirements with respect to latency, data rates, availability, reliability, and in some cases, high-accuracy positioning. The vertical industries that will reap the benefits of this new level of automation will range from railways, buildings, factories, healthcare, smart cities, electrical power supply and special events. These new Industry 4.0 opportunities will be possible through making sure that communications between machines is secure, dependable and seamless.

To achieve this, 5G supports three essential types of communication: enhanced Mobile Broadband (eMBB), massive Machine-Type Communication (mMTC), and Ultra-Reliable Low-Latency Communications (URLLC).

Connectivity is a key component of Industry 4.0 which aims at significantly improving the flexibility, versatility, usability and efficiency of future smart factories, integrates the Internet of Things (IoT) and related services in industrial manufacturing, and delivers seamless vertical and horizontal integration down the entire value chain and across all layers of the automation pyramid. Meeting these objectives will greatly depend on the 5G technical performance such as supporting a peak data rate of 1–20 Gbps; connection density 1 thousand – 1 million devices/km2; reliability of 99.999 percent; enhanced battery life of 10 years; higher position accuracy; latency 1–10 ms; and strong privacy and security.

Chris Pearson, President, 5G Americas said:

“New 5G technology developments will provide powerful and pervasive connectivity between machines, people and objects. Moreover, wireless communication, and in particular 5G, is an important means of achieving the required flexibility of production, supporting new advanced mobile applications for workers, and allowing mobile robots and autonomous vehicles to operate successfully in the future.”

It is becoming increasingly important that 5G technologies have the capabilities to provide ultra-reliable and low-latency communication which will enable automation in vertical domains through mission-critical machine type communication use cases. A 3GPP study item focuses on the requirements for automation in verticals with critical communications as an enabler for wireless control loops, identifying the normative 3GPP work needed to deliver 5G for automation in a variety of industries.

“5G technology will provide a wide range of vertical applications such as IoT, Virtual Reality (VR), industrial control, smart cities, smart grids and smart factories,” adds Rao Yallapragada from Intel and a co-leader of the white paper working group. “Security and seamless communication offered through 5G will be of utmost importance as we move towards automation of verticals.”

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• MoU signed under the witness of German chancellor and Chinese premier
• Siemens MindSphere to be deployed and operated on Alibaba Cloud’s infrastructure for China Mainland market

Siemens and Alibaba Cloud, the cloud computing arm of Alibaba Group, signed a Memorandum of Understanding (MoU) today to partner to foster the industrial Internet of Things (IoT) in China.

The two companies will leverage each other’s technology and industry resources to build a unique IoT solution to support Industrie 4.0, China’s manufacturing upgrade and transformation and other industrial Internet initiatives. Joe Kaeser, President and CEO of Siemens AG and Simon Hu, Senior Vice President of Alibaba Group and President of Alibaba Cloud signed the MoU in Berlin under the witness of German Chancellor Angela Merkel and Chinese Premier Li Keqiang during his official visit to Germany.

Joe Kaeser, said:
“We continue to build our global industrial digital network by partnering with Alibaba Cloud. This cooperation is a landmark deal for bringing Industrie 4.0-solutions to China as the world’s powerhouse of manufacturing.”

“Our customers will be able to unlock the potential of the Industrial Internet of Things with MindSphere now also on the leading Chinese cloud platform.”

“Today, we further strengthen our global leadership in automating and digitalizing the industrial world.”

“Today’s landmark partnership marks an exciting step towards Alibaba Cloud’s goal to enable digital transformation across the globe. We are delighted to partner with Siemens and together we hope to accelerate the adoption of IoT products and services that will create industry-wide breakthroughs and progress,” said Simon Hu.

As part of Siemens’ comprehensive digital offerings, MindSphere is Siemens’ cloud-based, open IoT operating system that delivers a wide range of device and enterprise connectivity options, robust applications, advanced analytics, and closed-loop innovation with complete digital twin solutions. The implementation of MindSphere on Alibaba Cloud will provide compelling services for companies in China Mainland to innovate with advanced industrial solutions.

Under the MoU, both companies will begin collaborating immediately and intend to make MindSphere on Alibaba Cloud available in 2019.

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New Augmented Reality, Machine Vision, Digital Twin and Automated Data Science capabilities enhance production, logistics, warehousing and maintenance.

Empowering modern businesses to improve production intelligence and market responsiveness, Oracle today unveiled new Industry 4.0 capabilities for Oracle Internet of Things (IoT) Cloud.

The advanced monitoring and analytics capabilities of the new offering enables organizations to improve efficiency, reduce costs, and identify new sources of revenue through advanced tracking of assets, workers, and vehicles; real-time issue detection; and predictive analytics.

According to The Economist Intelligence Unit, 63 percent of manufacturers have either undergone substantial digital transformation or are in the process of transforming parts of their organization, and 19 percent are developing transformation strategies. To remain competitive in the modern economy, businesses need to leverage new technologies and data to modernize their supply chains and improve visibility, predictive insights, and automation through connected workflows.

With new augmented reality, machine vision, digital twin and data science capabilities, Oracle IoT Cloud enables organizations to gain rich insight into the performance of assets, machines, workers, and vehicles so they can optimize their supply chain, manufacturing, and logistics, reduce time to market for new products; and enable new business models.

Bhagat Nainani, group vice president, IoT Applications at Oracle, said:

“IoT is the great enabler of Industry 4.0’s potential, providing real-time visibility and responsiveness at every step of the production process – from raw materials to customer fulfillment.”

“Oracle empowers organizations to create smart factories and modern supply chains with seamless interaction models between business applications and physical equipment. By receiving real-time data streams enhanced with predictive insights, our IoT applications provide intelligent business processes that deliver quick ROI.”

Today’s expansion follows the recent announcement of artificial Intelligence, digital thread and digital twin for supply chain, as well as industry-specific solutions for Oracle IoT Cloud. Oracle IoT Cloud is offered both as Software-as-a-Service (SaaS) applications, as well as Platform-as-a-Service (PaaS) offerings, enabling a high degree of adaptability for even the most demanding implementations.

Scott Rogers, technical director at Noble Plastics, said:

“We plan to leverage Oracle IoT Cloud and its machine learning capabilities to automatically analyze information gathered from the robot and process-monitoring systems. These analytics could help Noble identify ways to reduce cycle time, improve the manufacturing process, enhance product quality, and cut downtime.”

Oracle plans to add the new capabilities across the entire range of IoT Cloud Applications – Asset Monitoring, Production Monitoring, Fleet Monitoring, Connected Worker, and Service Monitoring for Connected Assets:

• Digital Twin: Enables remote users to monitor the health of assets and prevent failures before they occur, as well as running simulations of “what-if” scenarios in the context of the business processes. With Digital Twin, organizations have a new operational paradigm to interact with the physical world, allowing lower operational and capital expenditures, minimizing downtime, and optimizing asset performance.

• Augmented Reality: Gives operators and plant managers the ability to view operational metrics and related equipment information in the context of the physical asset for faster troubleshooting and assisted maintenance. In addition, the use of AR in training technicians reduces errors and on-boarding time, and improves user productivity.

• Machine Vision: Provides detailed non-intrusive visual inspections, which can detect defects invisible to the naked eye, at high speed and scale. Following the rapid inspection, Machine Vision sets in motion appropriate corrective actions when anomalies and errors are spotted.

• Auto Data Science: Automated business-specific data science and artificial intelligence algorithms continuously analyze asset utilization, production yield and quantity, inventory, fleet performance, as well as worker safety concerns, to predict issues before they arise. Auto Data Science features enable users to see performance metrics of each step in the modern supply chain with the ability to drill down into specific issues at each location without employing an army of data scientists.

Oracle IoT Cloud enables companies to monitor capital intensive assets to reduce downtime and servicing costs, and track utilization for accurate lifecycle insights and asset depreciation data, which improves enterprise procurement efficiency. The rich pool of data created by sensors within products enables organizations to offer their products as a service, gain insight into how customers are using their products, and offer improved value-added services that drive new sources of revenue.

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Sigfox, today announced a global partnership with Alizent, the Asset Interactive Company, representing another step forward in maximizing the benefits of IoT on industries across all sectors.

The two partners, seeing Industry 4.0 as one of the main growth paths driving the development of IoT, will combine their respective technologies and capabilities to provide monitoring and tracking solutions of industrial assets on a global basis.

Sigfox and Alizent are already working on exploring opportunities in Europe and the US:

• Air Liquide: Piloting gas cylinders tracking and CO2 tanks monitoring
  Alizent’s tracking solution combined with Sigfox connectivity in this pilot allows to collect accurate data from the fleet of returnable containers. This information offers valuable insights on the value chain and at the same time allows to provide real-time inventories to customers. With the support of Alizent, it is also considered to monitor the CO2 mini-tanks that are also used by Fast food chains for soda.

• Tracking animal vaccine boxes in the United States
  Animal health vaccines contain active bio-ingredients that must be transported with great care and under specific conditions. Not keeping vaccines at the appropriate temperature would tamper with the quality which, in turn, would result in a large number of animals not receiving the proper vaccinations. Thanks to Sigfox connectivity, Alizent is currently testing a tracking system in the United States that reports container data. These metrics are essential for quality control and traceability, leading to greater efficiencies and new services.

• Tracking of Oxygen cylinders in one of the largest hospitals in Texas
  Large hospitals have the complex task to track portable oxygen cylinders for inventory control and billing purposes. Tracking devices installed in 300 Oxygen cylinders in one of the largest hospitals in the Texas medical technology area have during the pilot phase significantly reduced cylinder losses and rental fees for customers while optimizing the supply chain.

• Preventive maintenance of beer equipment on customer premises
  Beer brewers seek to maintain a correct temperature for draft beer or cider, a paramount for customer’s satisfaction. Alizent’s predictive maintenance solution combined with Sigfox connectivity allows beer brewers to monitor beer coolers and dispensers temperature. This solution prevents breakdowns, expensive repairs, waste of time and money, and ultimately sales loss.

Alexis Duret, Managing Director, Alizent:

“We believe that connecting all industrial assets will generate valuable data for our customers.”

“Sigfox, through its unique technology and global network services, support and pricing, combined with Alizent proven ability and rare mix of industrial and technological skills, enables the connection of a whole new range of industrial assets for our clients”.

Vincent Sabot, VP Sales Europe, Sigfox:
“This partnership with Alizent once again illustrates that the IoT space opens up new and exciting opportunities for industries. Sigfox’s low-cost and low-power connectivity represents a dramatic shift for companies looking to reduce their costs and improve their industrial processes, as well as create new services based on big data”.

The two partners believe that combining Sigfox’s connectivity offering with Alizent’s knowledge of industrial customers will bring a unique value proposal to verticals such as Oil and Gas, Primary Metals, Manufacturing, Healthcare, Food & Beverage, Agriculture, Chemical & Pharmaceuticals.

The post Sigfox and Alizent Partner to Offer Industrial Internet of Things Services Worldwide appeared first on IoT Business News.

Manufacturers are under constant pressure to improve operational performance in four primary areas: Cost, Quality, Availability and Throughput.

The challenge is to overcome rigid, complex and poorly integrated infrastructure and traditional technologies that are costly, “rip and replace” and slow to implement and evolve.

There’s a wave of transformation coming from the IIoT and the new technologies it presents, and it’s having a profound impact on manufacturers around the world.

Solutions to Manufacturing Challenges

Manufacturing executives are turning to the Industrial Internet of Things (IIoT)/Industrie 4.0 to drive this new wave of continuous improvement in 2 key ways:

1) By making the factory:

a. Connected (IT/OT convergence)
b. Real-time
c. Digitally integrated
d. Predictive

2) By leveraging purpose-built IoT technology that is:

a. Quick to deploy
b. Quick to value
c. Agile and continuously evolving
d. Delivering modern experiences with web, mobile and augmented reality

Three Stages of Manufacturing Transformation

According to a 2016 LNS Research study, 51% of manufacturers surveyed will be investing in the IIoT in the next 12 months, and 75% are eventually expecting to invest in it. Manufacturers can leverage the IIoT to continuously improve their operational performance and flexibility through digital manufacturing, real-time intelligence and predictive analytics. There are three stages of Manufacturing Transformation: Understand, Advance and Outperform.

Stage 1: Understand

In the first stage of the transformation journey, manufacturers should consider taking these initial steps to get their arms around existing data, and gain real-time access to it:

• Connect diverse and disparate assets, sensors, business systems and external data sources in real time
• Broadcast real-time alerts about assets and performance anomalies
• Simplify data in up-to-the-minute, role-based views of operational performance
• Enhance existing infrastructure with smart sensors and modern technologies

Expected results include improved information quality & reliability, decreased unplanned downtime, increased operator efficiency, improved maintenance efficiency and improved product quality. By taking these steps, a leading transportation manufacturer used real-time Performance Visibility data to reduce unplanned downtime by 10-20%, with plant deployments taking just a matter of weeks.

Stage 2: Advance

Once the data is available in real-time format, manufacturers should then:

• Apply predictive analytics to machine health (to alert when the machine might fail) and quality processes (if a certain parameter is trending downward, it can be quickly corrected)
• Employ intuitive, in-context 3D and augmented reality to guide workers
• Digitally design manufacturing processes & quality plans
• Utilize agile methodologies to rapidly create & continuously evolve manufacturing applications

By implementing these processes, results can include accelerated continuous improvement, increased speed and flexibility, increased workforce efficiency, improved product quality and optimized maintenance processes. For example, a boat builder streamlined their product development and manufacturing processes using these techniques, which enabled them to deliver their product on-time and under budget for the first time ever.

Stage 3: Outperform

In the final stage, the goal is to extend these capabilities to an enterprise level, to include suppliers and:

• Obtain supplier production visibility to gain early status into performance and quality
• Synchronize resources to ensure flawless execution of production
• Implement consistent KPIs and operations-wide performance benchmarking to identify and implement best practices
• Deploy physical-digital closed- loop processes to drive continuous improvement

This will result in improved production processes, improved profitability, reduced unplanned downtime, shortened lead times and improved agility and responsiveness. One Fortune 50 Food and Beverage leader uses real-time visibility to improve productivity by 8-10%.

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