IoT Analytics performs research and analysis from its base in Germany and with affiliated people globally. I have an affiliation with them. Through Microsoft, I discovered this 59-page IoT Signals Report – Manufacturing Spotlight (August 2022), published by Microsoft and Intel, with research conducted by IoT Analytics. As part of this research, IoT Analytics surveyed 500 decision-makers working in discrete, hybrid, or process manufacturing in April and May 2022 and conducted in-depth interviews with a subset of them.
One of the findings from the research tells us 72% of manufacturers have partially or fully implemented a smart factory strategy today. Similarly, nearly two-thirds (65%) are in various stages of implementing their IoT strategy. Although the pandemic, looming recession, inflation, and global supply chain issues have been prevalent topics in the last year(s), manufacturers are determined to fast-track their digital transformation projects in the next three years.
- When evaluating the success of a smart factory, operational KPIs are important for manufacturers in all regions and industries and across all company sizes.
- Companies are ambitious to improve supply chain, safety, and sustainability KPIs in the next three years.
Why it matters
- For manufacturers: The data provide an opportunity to benchmark against industry peers.
- For technology vendors: Aligning services and products offered with the KPIs that manufacturers prioritize is important.
1. Most important operational KPI: Increase in OEE
All the top five manufacturing KPIs are related to operational goals. Across all regions and industries, respondents are highly focused on improving operational performance, including overall equipment effectiveness (OEE), labor efficiency, and output. The increase in OEE is the most important manufacturing KPI for measuring the success of their smart factory strategies. This KPI is seen as either important or very important by 86% of manufacturers.
2. Most important supply chain KPI: Increase supply chain resiliency
The increase in supply chain resiliency is regarded as important or very important for 73% of manufacturers. The global supply chain issues that were sparked by pandemic lockdowns and (trade) wars have put this manufacturing KPI in the spotlight of many factories. On average, the ambition of manufacturers is to increase supply chain resiliency by 28% in the next three years. Decision-makers see implementing new IoT based technology as a smart way to safeguard themselves from global turbulences.
3. Most important safety KPI: Decrease in reported safety incidents
A decrease in reported safety incidents is regarded by 67% of manufacturers as an important manufacturing KPI in measuring the success of their smart factory strategy. And decision-makers want to act on it. The average ambition of manufacturers is to improve the KPI by 30% in the next three years. Safer employees are happier and more productive employees—not only during the current environment of labor shortage but also otherwise.
4. Most important marketing and sales KPI: Increase in revenue
For 69% of manufacturers, the increase in revenue is an important manufacturing KPI to measure the success of their smart factory strategy. The introduction of new IoT-based technologies does not only affect the operations themselves but also indirectly affects the revenue. Customers expect vendors in discrete and process industries to deliver high-quality, highly customized products on time.
5. Most important sustainability KPI: Reduction of waste
Nearly two-thirds (63%) of manufacturers see the reduction of waste as an integral part of their smart factory transformation. Although sustainability improvements are not the main driver of smart factory strategies, manufacturers are devoting more attention to the topic and often see it as complementary to the existing operational KPIs. Respondents ranked “decrease in waste” as the manufacturing KPI with the second-highest overall ambition and “carbon footprint reduction” as the fastest-accelerating manufacturing KPI. This indicates that respondents recognize the opportunity for tangible improvements and are likely to boost the importance of sustainability KPIs in the coming years. Moreover, improving a sustainability KPI often correlates with improving an operational KPI and vice versa. For example, a reduction in energy usage or waste may lead to a reduction in costs, while an increase in process efficiency may lead to lower energy use and a better carbon footprint.
What if the time has come to rethink all these specific silos and strategies around which we build manufacturing software solutions?
The time has come to rethink all the departmental silos manufacturing executives constructed over the years with vendors targeting their applications to fit. This era of the Internet of Things (IoT), sensor-driven real-time data, innovative unstructured databases, powerful analytics engines, and visualization provide us with new ways of thinking about organizing manufacturing.
A suite of manufacturing solutions that typically link shop floor equipment and operations with enterprise solutions has evolved from Manufacturing Resources Planning (MRP, what I did in the late 1970s) to MES (originally Manufacturing Execution Systems which the trade organization MESA has called Manufacturing Enterprise Solutions) to now what we can call Real-time Operational Intelligence (RtOI) solutions. I was digitizing manufacturing operations in 1978 in a crude way. Now it is much more sophisticated, yet in many ways, easier. Each of these steps has taken us deeper into increasing digitization, vast amounts of data, and increasing connectivity. Not just name changes, these solutions reflect the growing ability to provide managers of all levels the kind of information needed for better, faster decision making.
Focus on Maintenance Management
I have worked with a number of maintenance and reliability media companies. They have all been embroiled in discussions of the comparative value of maintenance strategies: Reactive (run-to-failure), Preventive, Predictive, Reliability-centered. These are presented as a continuum progressing from the Stone Age to Star Wars. Discussions about which is best proliferate within trade media.
The IT companies I have worked with fixated on predictive maintenance. They had powerful predictive analytics to combine with their database and compute capabilities and saw that as the Next Big Thing. They were wrong.
I was taught early in my career that Preventive maintenance consisted solely as scheduled maintenance. Management sends technicians out on rounds on a regular basis with clipboards, lube equipment, and meters to check out, lubricate and adjust. As often as not, these adjustments would disturb the Force and something would break down.
What if? What if we use all the sensor data from equipment sent to the cloud to a powerful database? What if we use that data to intelligently dispatch technicians to the necessary equipment with the appropriate tools to fix before breaking and at an appropriate collaborative time?
A company called Matics recently was introduced to me via a long-time marketing contact. They wanted to talk about the second definition of preventive maintenance. Not just unscheduled rounds but using sensor-driven data, or IoT, to feed its Central Data Repository with the goal of providing Real-time Operational Intelligence (RtOI) to its customers.
According to Matics, its RtOI system has provided customers with:
- 25% increased machine availability
- 30% decrease in rejects
- 10% reduction in energy consumption
Smarter preventive maintenance leverages continuous condition monitoring targeting as-needed maintenance resulting in fewer unnecessary checks and less machine stoppage for repair.
I am not trying to write a marketing piece for Matics, although the company does compensate me for some content development including this post. But their software provides me a way to riff into a new way of thinking.
Usually product engineers and marketing people will show me a new product. I’ll become enthused. “Wow, this is cool. Now if you could just do this and this…” I drive product people crazy in those meetings. I think the same here. I like the approach. Now, if customers can take the ball and run with it thinking about manufacturing in a a new way, that would be cool—and beneficial and profitable. I think innovative managers and engineers could find new ways to bring engineering, production, and maintenance together in a more collaborative way around real-time information.
Much as some of its large industrial competitors, ABB is quickly building out industrial software solutions. A friend who is a financial analyst told me that Wall Street and other investors prize software right now. A company focused on instrumentation and automation platforms doesn’t evoke the same eyes full of longing and desire as when they add software.
In this announcement, ABB and Red Hat, the open source enterprise software company, are partnering to deliver ABB automation and industrial software solutions at the intersection of information technology (IT) and operational technology (OT), equipping the industrial ecosystem with extended deployment capabilities and greater agility. This is consistent with ABB’s vision of the evolution of process automation.
- ABB will deliver digital solutions to customers on-demand and at scale using Red HatOpenShift
- Customers will be better able to harness the potential of data-based decisions by using applications that can be deployed flexibly from the edge to the cloud
The partnership enables virtualization and containerization of automation software with Red Hat OpenShift to provide advanced flexibility in hardware deployment, optimized according to application needs. It also provides efficient system orchestration, enabling real-time, data-based decision making at the edge and further processing in the cloud.
Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform, with Red Hat Enterprise Linux as its foundation, provides ABB with a single consistent application platform, from small single node systems to scaled-out hyperconverged clusters at the industrial edge, which simplifies development and management efforts for ABB’s customers.
“This exciting partnership with Red Hat demonstrates ABB’s commitment to meet customer needs by seeking alliances with other innovative market leaders,” said Bernhard Eschermann, Chief Technology Officer, ABB Process Automation. “The alliance with Red Hat will see ABB continue helping our customers improve their operations as they navigate a rapidly evolving digital landscape. It will give them access to the tools they need to integrate plantwide IT and OT, while reducing risks and optimizing performance.”
Red Hat OpenShift increases the deployment flexibility and scalability of ABB Ability Edgenius, a comprehensive edge platform for industrial software applications, together with ABB Ability Genix Industrial Analytics and AI Suite, an enterprise-grade platform and applications suite that leverages industrial AI to drive Industry 4.0 digital business outcomes for customers. ABB’s Edgenius and Genix can both be scaled seamlessly and securely across multiple deployments. With this partnership, ABB will have access to capabilities like zero-touch provisioning (remote configuration of networks) which can increase manageability and consistency across plant environments.
“Red Hat is excited to work with ABB to bring operational and information technology closer together to form the industrial edge. Together, we intend to streamline the transition from automated to autonomous operations and address current and future manufacturing needs using open-source technologies,” said Matt Hicks, executive vice president, Products and Technologies, Red Hat. “As we work to break down barriers between IT and the plant level, we look to drive limitless innovation and mark a paradigm shift in operational technology based on open source.”
Here is an interesting trend. Moxa released a series of IIoT gateways optimized for Microsoft Azure.
Moxa launched the AIG-300 Series of IIoT gateways. Optimized for seamless integration with the Microsoft Azure IoT Edge computing platform, AIG-300 gateways provide the stable connectivity needed in distributed and unmanned sites to collect, store, process, and analyze operational data from sensors and other IIoT devices.
As edge computing use cases continue to evolve, Moxa AIG-300 gateways enable flexible and secure cloud connectivity by leveraging: Arm CortexA7 dual-core 1 GHz processors, pre-loaded Azure IoT Edge and Moxa ThingsPro Edge software, and versatile I/O options for Ethernet, CAN, RS-232/422/485, USB, and four digital (DI/DO) interfaces. For system integrators with wireless communication needs, the AIG-300 comes with LTE cellular, GPS and Wi-Fi antenna connectors.
ThinkIQ developed a manufacturing software platform focused on the flow of materials through the manufacturing process rather than the health of specific machines. I’ve had several interviews over the past couple of years with executives I’ve known for years from previous gigs. You can check them out here, here, and here.
I recently conducted an interview with Doug Lawson, CEO, Brian Anderson, CMO, and Rob Schoenthalar, CRO to discuss an added feature to their offering. They have added vision as a sensor attempting to solve a sticky problem for manufacturing management.
The problem? ThinkIQ’s customers are still effectively blind to up to 70% of events on the Factory Floor. Current safety practices are primarily reactive and rather than averting any unfortunate incident in the first place, these procedures only provide solutions to salvage a regrettable situation.
The solution? Enhancements to its Vision Platform.
Locating cameras in strategic locations around the plant facility, Think IQ can look at safety and correlations among activities. Maybe checking events of ship, store, manufacturing, looking for root causes. They offered an example General Mills has publicized where they recorded savings of $40 million out of oats for making Cheerios. They also avoided multiple recalls by detecting gluten entering the process before manufacturing.
An MES or other software may not always record every aspect of a process. Merging cameras with their MES, ThinkIQ can add much more data plus analysis to discover more problems. Their cameras do not do parts inspection. They observe movement and behavior generating what they call “Operational Data Streams.” Now ThinkIQ can combine data about material flow plus what machines are doing plus what people are doing. Operations does not need to ask operators to fill out HMI screen forms about what happened. ThinkIQ’s value add is intellectual property around AI/ML looking for patterns in the data.
From the press release:
The latest version of ThinkIQ Vision now has out-of-the-box abilities to detect and digitize dozens of common manufacturing events including:
- Vehicle activities in receiving and shipping
- Material movements and presence
- Anonymous People presence and activity
- Machine state and physical events
- Andon light status
- Safety violations
- Values from legacy analog and disconnected digital displays
- Values from stand-alone displays
[Updated with correct name spelling.] Manufacturing companies began a digital journey decades ago. I began a digital project in 1978. Digital is one thing. Connectivity is another. My customer in 1994 told me he would never allow a wire from a PLC to anything else (other than I/O of course) as long as he was the controls leader. By 1999 he was retired and the plant had some connected controllers.
He was right, though. The concern was risk. And that was before anyone knew anything about cybersecurity. But there was risk of someone breaking in and messing with the program and settings.
And risk was a key word as I was introduced to BT, a networking and IT company, through an interview with global manufacturing lead Jose Gastey. He told me connected boxes leads to risks and liability. There is a constant tension between efficient services and risk. This was my introduction to BT. I had not interviewed anyone from there before.
Three Key Words, Connectivity, Collaboration, Cybersecurity
Gastey told me, “BT as a company had to change. The question was how to provide security around data that customers expect us to transmit for them. Last year BT invested in Safe Security. We can talk about financial risk alongside risk of data loss and hacking.”
Manufacturing has made tremendous investments in digital technologies and connectivity. That come with a risk. According to the 2021 NTT Global Threat Intelligence Report, threat actors have made manufacturing one of the five most targeted industries seven times over the last nine years. Cyber-espionage, data theft and other types of digital attacks have become the norm rather than the exception.
BT industry sales representatives have an additional security tool in their toolbox of solutions for their clients. The Safe Security SAFE (‘Security Assessment Framework for Enterprises’) platform allows organisations to take a health check of their existing defences and understand their likelihood of suffering a major cyber attack.
SAFE is unique in calculating a financial cost to customers’ risks and giving actionable insight on the steps that can be taken to address them. The platform ultimately enables organisations to surgically target gaps in their defences, and already protects multiple Fortune 500 companies and governments around the world.
Sustainability, 5G and Ecosystem
Before leaving the briefing, Gastey told me about two other BT emphases of interest to manufacturing—sustainability and 5G/WiFi6 networks.
“Sustainability adds another layer,” said Gastey. BT has joined with Cisco and Global Data to compile data about global sustainability. In this context, the focus here is reduction of energy consumption.
BT works with private 5G and WiFi6. Gastey says scaling is crucial element. “Engineers install 5G in a plant,” he says, “and business managers say, this is great. Now, roll out to 200 plants. But that is hard. There are too many differences from plant to plant. Solving scaling is a big problem.”