With the pandemic mostly in the rearview mirror, Inductive Automation held its Ignition Community Conference 2022 in Folsom, CA Sept. 20-21.
ICC 2022
The event was sold out, as usual. Sessions were packed and lively with questions. I didn’t pick up much news from the event. It was good to catch up with people I’ve known for years but haven’t seen since 2019. The new Inductive leadership team mingled with customers and took a little time to chat with me.
Two things:
An acquaintance from another and non-competitive software company I talked with at the Hannover Messe Chicago the week before told me that his sales people saw Inductive everywhere. “They are crushing it,” he said. Indeed, it is the one company in its software market that has momentum and constant innovation.
I met owner/founder Steve Hechtman in 2006 at an ISA event. Everything he told me back then seemed far out—and everything they talked about at this conference confirmed his initial vision. Mostly that was doing SCADA in an IT-friendly way.
A bonus:
Here is a link to my March 15, 2011 podcast recorded in the conference room at the company’s original headquarters in Sacramento. This was the 112th episode of my podcast, which back then was Automation Minutes done for Automation World magazine. I expected Steve Hechtman to do all the talking, but he turned it over to the software developers of what is now Ignition—Colby Clegg (now CEO) and Carl Gould (now CTO).
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.
In short
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.
The most optimistic trend I see in our market concerns cooperation and collaboration. There’s a lot of that going on. Here’s one I didn’t really see coming—the Industry IoT Consortium (IIC) and the International Society of Automation (ISA). They recently announced the IoT Security Maturity Model (SMM): 62443 Mappings for Asset Owners, and Product Suppliers, and Service Suppliers.
“This new guidance adds the service provider role. It extends the previously published IoT Security Maturity Model (SMM): Practitioner’s Guide to provide mappings to existing 62443 standards and specific guidance for the asset owner, product supplier, and service provider roles,” said Ron Zahavi, Chief Strategist for IoT standards at Microsoft and IoT SMM co-author.
The IIC IoT SMM helps organizations choose their security target state and determine their current security state. By repeatedly comparing the target and current states, organizations can identify where they can make further improvements.
The ISA99 committee developed the 62443 series of standards, which the International Electrotechnical Commission (IEC) adopted. The standards address current and future vulnerabilities in Industrial Automation and Control Systems (IACS) and apply necessary mitigation systematically and defensibly. The ISA/IEC 62443 standards focus on maturity, but only on the maturity of security programs and processes.
“Achieving security maturity targets can be difficult to put into practice without concrete guidance,” said Frederick Hirsch, co-chair of the IIC ISA/IIC Contributing Group. “These 62443 mappings enable practitioners to better achieve security maturity by relating IIC IoT SMM practice comprehensiveness levels to ISA/IEC 62443 requirements. In this way, IACS asset owners and product suppliers can achieve appropriate maturity targets more easily.”
Eric Cosman, co-chair of the ISA99, said, “While standards such as ISA/IEC 62443 are needed to codify proven and accepted engineering practices, they are seldom sufficient. Joint efforts such as this provide the practical guidance necessary to promote and support their adoption.”
Pierre Kobes, a member of both ISA99 and IEC Technical Committee 65, said, “It is not about more security but about implementing the appropriate security measures. IoT SMM: 62443 Mappings for Asset Owners and Product Suppliers helps companies select the adequate security levels commensurate with their expected level of risk.”
You can download IoT SMM: 62443 Mappings for Asset Owners, Product Suppliers and Service Providers from IIC and ISA websites. You will find a complete list of the contributing authors in the document. Work is underway to add the service provider role to the document in a future revision.
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.
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
