To Everything There Is A Season

What if the time has come to rethink all these specific silos and strategies that we build software solutions around?

Folk/rock group The Byrds popularized a Pete Seeger tune in the 1960s, “To everything (turn, turn, turn) there is a season (turn, turn, turn) and a time for every purpose under heaven.” 

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.

HMI/SCADA can become IoT enabling software expanding beyond the normal visualization role. Types of MES software break the bounds of traditional silos. Not just quality metrics, OEE calculators, or maintenance schedulers, what if we thought of MES as operational intelligence bringing disparate parts together? These can provide managers of all levels the kind of information needed for better, faster decision making.

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 StarTrek. With them are always discussion about which is best.

The IT companies I have worked with fixated on predictive. 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 was also known as scheduled maintenance. Management sends technicians out on rounds on a regular basis with lube equipment and meters to check out and 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. 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.

Software At Center Stage of Rockwell Automation Event

Taking the third trip to Orlando in four weeks, I felt that I should know the TSA agents by first name. Rockwell Automation held its annual software training and bash formerly RSTechEd now called ROKLive. Not only was this the first after a Covid hiatus, it also celebrated the recent addition of Plex Systems and its cloud-based MES platform. 

Plex was acquired some nine months ago. This event offers the Plex community some continuity while bringing them into the Rockwell Automation fold. About 1,500 people attended filling the Loews Sapphire Lake resort in Orlando and its many meeting rooms for updates and lab training.

Rockwell CEO Blake Moret did not attend in person, instead sending a video for part of the opening keynotes. He talked of the company’s focus on helping customers along the path of productive, resilient, agile, and sustainable. He noted that Rockwell as a manufacturer itself knew the power of IT and OT working together. Rockwell’s strategy focuses include its core products, software & services, and industry focus.

Brian Shepherd, sr. Vice president software and control, emphasized these pillars under the “Connected Enterprise Production System”: optimize production, empower the workforce, manage risk, drive sustainability, transformation.

Rockwell Automation through acquisition has entered the 3D system emulation arena. However partner company Maplesoft representatives showed me its simulation application. It looks powerful. Also on the show floor was old standby Spectrum Controls showing a cool connectivity multi-port module that takes in serial protocols such as DF1 or Modbus and exports Ethernet. If you are constructing a connected enterprise, you will need connectivity devices.

I took a look at the future on the show floor and some follow-up sessions on FactoryTalk Hub and its Design Hub, an internal Rockwell development taking control design to the cloud. It will be more formally unveiled at Automation Fair later in the year, but this powerful cloud-based application brings benefits such as collaboration and version control to Rockwell’s Design Studio offering. Operate Hub, the Plex SaaS MES and operations offering, and Maintain Hub, the Fiix CMMS in the cloud complete the FactoryTalk Hub solution. Three years ago no one would imagine my writing about Rockwell and the cloud in the same sentence. Not only has the technology progress but so has acceptance of users.

Rockwell and Plex released a few news items.

Rockwell Automation Named a Visionary; Plex Systems Named a Leader in 2022 Gartner Magic Quadrant for Manufacturing Execution Systems

Analyst firm Gartner unveiled its MES Magic Quadrant. Included companies always rush to get the word out. Rockwell Automation announced it has been named as a Visionary for its FactoryTalk ProductionCentre and Plex Systems named as a Leader for its Smart Manufacturing Platform. Congratulations to each.

Plex Systems Announces Modularization of its Smart Manufacturing Platform to Scale with Business Needs

Plex Systems announced a new modularization approach for its Smart Manufacturing Platform to enable accessibility and scalability for digital transformation in manufacturing. This approach, enabled by Plex’s innovative cloud-native platform, more closely aligns with customers’ needs as they build their smart manufacturing technology strategy, including a focus on flexibility, quick implementation, and ease of entry with a path to grow.  

Three examples of the new modular solutions include:

• New Product Introduction and Management: Maximize profitability and increase competitive position by reducing time to market and decreasing development costs.  Companies can manage the product and program lifecycle – from concept to completion – and effectively track new and existing products, including updates, retirement, and obsolescence.

• Labor and Workforce Management: Optimize labor schedule and costs while preserving delivery schedules through effective labor management, clear skills-to-required production capabilities, reduction of onboarding time, and programs for employee health and safety.

• Advanced Quality: Proactively manage supplier quality and compliance with integrated continuous improvement toolsets and extend quality processes throughout the full supply chain to promote a holistic quality culture both inside and outside the four walls of the organization.

Plex Systems Introduces Machine Learning to Help Companies Improve Demand Forecasting Accuracy

Plex Systems also announced new machine learning capabilities for Plex DemandCaster Supply Chain Planning (SCP), enhancing forecast accuracy to improve customer service at lower levels of inventory coverage.

Plex DemandCaster Supply Chain Planning unites business functions within the organization with their planning variables to solve inventory problems quickly and proactively, helping planners easily interpret data with automated statistical forecasting while enabling a continuous planning and execution feedback loop. Now, the addition of machine learning for DemandCaster SCP advances the automation of pattern recognition and the application of correlated related data to improve forecast accuracy. Higher forecast accuracies cascade through the supply chain planning process by reducing the need to carry extra inventories to buffer against uncertainties. 

New Name And Thinking For Hexagon Division

More than 800 people have gathered for the resumption of the ARC Advisory Group’s annual Forum in Orlando. Yes, that’s right, my second trip to Orlando in three weeks. And there is one more to come.

Based on just a few hours at the conference and one trip around the exhibition hall, the theme this year likely will be the future of process automation Information abounds, but this appears to be the interesting idea. Plus data. Data everywhere. More on that later as I’m working on an essay on data.

Only six companies took advantage of the assembled corps of writers to hold briefings today. Some things I’ve already written up from previous interviews. Some are embargoed until later. Here is an interesting announcement of a new name.

Hexagon AB has been on a buying spree. I don’t know when it will end, but I’m thinking not soon. It has a division called PPM that encompasses asset management. Executives said this change does not signify any portfolio changes, rather a new way of thinking about the newly aggregated companies.

The new division name is Hexagon’s Asset Lifecycle Intelligence division.

Mattias Stenberg, president of the division, said, “This evolution is driven by our customers’ needs to have real-time intelligence about their assets. This divisional name is reflective of our focus and expertise in supporting the entire asset lifecycle throughout the customer’s digital journey.”

The new division includes HxGN EAM (formerly Infor EAM), PAS Global, Jovix, and Innovatia Accelerator.

FDT Group Introduces FDT Unified Environment for Field to Cloud Data Harmonization

The HUG experience in Orlando is barely out of my system when I turned to Hannover Messe. No, I am not eating German food, well, at least not in Germany. Yesterday morning I sat in a 7 am (my time) press conference with OPC Foundation. More on that later. I have worked all afternoon consolidating about 20 press releases and interviews and decided at the end of the day to talk about the press conference / annual general meeting I attended virtually this morning. This from the FDT Group.

Steve Biegacki became Executive Director in January bringing experience with building this type of organization not to mention marketing and sales executive experience with both Rockwell Automation and Belden. Along with the Rockwell role he was a driving force behind ODVA and CIP. 

He pulled off his initial AGM at Hannover with his usual style backed with experienced staff. Pretty much like the organizations I’ve talked with this year, they didn’t let the pandemic slow the work cranking out valuable work. Biegacki will be leading a renewed marketing effort to explain benefits of the FDT 3.0 standard.

From today’s news: Device, system, and end users now benefit from an embedded unified environment unlocking universal device management, IT/OT convergence, data analytics, services, and mobility.

FDT Group, an independent, international, not-for-profit industry association supporting the evolution of FDT technology, introduced the FDT Unified Environment (UE), and developer tools based on the new FDT 3.0 standard to deliver next-generation FDT industrial device management system and device solutions for field-to-cloud IT/OT data harmonization, analytics, services, and mobility based on user-driven requirements for smart manufacturing in the process, hybrid, and discrete markets.

Driven by digital transformation use cases to support new Industrial Internet of Things (IIoT) business models, the standard has evolved to include a new distributed, multi-user, FDT Server application that includes built-in and pre-wired OPC UA and Web servers enabling an FDT Unified Environment (FDT 3.x) merging IT/OT data analytics supporting service-oriented architectures. The new Server environment deployable in the cloud or on-premise delivers the same use cases and functionally as the previous generation FDT hosting environment, but now provides data storage for the whole device lifecycle at the core of the architecture allowing information modeling and data consistency to authenticated OPC UA and browser-based clients (tablets and phones) for modern accessibility to address the challenges of IIoT.

“Collaboration and data harmonization are the keys to manufacturing modernization,” said Steve Biegacki, managing director, FDT Group. “FDT UE delivers a data collaborative engineering specification and toolset to enable modern distributed control improving operations and production reliability, impacting the bottom line for new IIoT architectures.  I’m proud to witness our first group of members showcasing their FDT 3.0 WebUI-based DTM prototypes mixed with 2.0 DTMs in the new Server and Desktop environments running IO-Link and HART here at Hannover Messe live and in person. To be present as a guest in the OPC Foundation booth to demonstrate field-to-cloud connectivity, OPC UA enterprise access and services along with mobile field device operation is one for industry history books. I especially want to thank Thomas Hadlich, FDT architecture and specification chairman, for leading the first FDT UE demo project; along with our front runner member companies for participating – Flowserve, Krohne, Omron, Magnetrol, Thorsis, CodeWrights, VEGA, Rockwell Automation, Turck, PACTware and M&M Software.”

FDT UE consists of FDT Server, FDT Desktop, and FDT DTM components. System and device suppliers can take a well-established standard they are familiar with and easily create and customize standards-based, data-centric, cross-platform FDT 3.0 solutions—expanding their portfolio offerings to meet requirements for next-generation industrial control applications. Each solution auto-enables OPC UA integration and allows the development team to focus on value-added features that differentiate their products, including WebUI and App support. FDT Desktop applications are fully backward compatible supporting the existing install base.

FDT 3.0 specification license agreements and developer toolkits are now available on the FDT website.

 

Emerson Condition Monitoring Software Expands Visibility to Asset Health

Emerson now bills itself as “global software and technology leader.” I may have pointed this out before, but I find it interesting that after years of asking major automation technology providers about software, Emerson, along with Rockwell Automation and Siemens, have brought software up to a point of being a major competitive advantage.

This news from Emerson highlights an update to its machinery health platform to enable customers to migrate to a more holistic, modern interface for condition monitoring. New support brings data from edge analytics devices directly to key personnel inside and outside the control room. 

Emerson has continuously evolved AMS Machine Works‘ condition monitoring technologies for better diagnostics at the industrial edge. Increased connectivity to external systems provides personnel with an intuitive, holistic asset health score supported by maintenance recommendations to help reliability teams quickly see what is wrong and how to fix it. Intuitive information and alerts are delivered directly to workstations or mobile devices to provide decision support, helping maintenance personnel make the best use of their time.

The newest version of AMS Machine Works adds support for Emerson’s AMS Asset Monitor, which provides embedded, automatic analytics at the edge using patented PeakVue technology to alert personnel to the most common faults associated with a wide range of assets. AMS Machine Works also supports open connectivity using the OPC UA protocol to make it easier to connect to external systems such as historians, computerized maintenance management systems, and more to help close the loop on plant support from identification to repair and documentation.

Predictive Maintenance Thoughts from IMC 2021

Terrence O’Hanlon and crew produced its annual International Maintenance Conference and Reliability 4.0 live in December in (mostly) sunny Florida. I attended IMC for the first time. The last time I attended one of his excellent events was around 2003 for a different company. This edition was as good as I expected. Plenty of informative keynotes and tech sessions, as well as, many networking opportunities.

The 700 attendees were fewer than past years, but then the “international” part of IMC was a little lacking this year given the situation with Covid and traveling.

My goal was to take a deep dive into the nuances surrounding predictive maintenance. My sources in the IT and IIoT communities figured data was becoming readily available and predictive analytics were improving. Add those together and surely it was obvious that predictive maintenance was the “killer app” for them.

I didn’t see it quite that same way even while helping some of them write marketing pieces. It was time to learn more.

Condensing what I heard from several speakers, predictive maintenance was not the end goal. It was useful when connected into the plant’s workflow. It required decision making from experts and integration into the work of maintenance technicians.

Networking with other attendees often has more value than any other interaction. At dinner one evening, one long-time colleague told me another long-time colleague was there. I sat there and talked with Gopal GopalKrishnan with whom I had worked when he was at OSIsoft. He’s now with CapGemini. He introduced me to his layered approach to maintenance.

He first pointed me to a McKinsey study. Establishing the Right Analytics-based Maintenance Strategy,

The assumption that predictive maintenance is the only advanced, analytics-based use for Internet of Things (IoT) data in the maintenance world has created a great deal of misconception and loss of value. While predictive maintenance can generate substantial savings in the right circumstances, in too many cases such savings are offset by the cost of unavoidable false positives.

Then consider this thought from Emerson’s Jonas Berge.

We have a promising future of Artificial Intelligence (AI) ahead of us. But to be successful we must first learn to reject the fake visions painted by consultants eager to outdo each other. Most engineers don’t have a good handle on Al the way they have on mechanics, electricity, or chemistry. Data science has no first principles or scientific laws. It is very nebulous. So it can be hard to judge if claims made around analytics are realistic. Or you may end up using an overly complex kind of Al for a simple analytics task. It must be like the early days of thermodynamics and electromagnetism.

Now some additional thoughts from Gopal here and here:

As such, a layered fit-for-purpose approach to analytics can be extremely valuable when you also leverage simple heuristics – extracted from SME (subject-matter-expert) knowledge – with basic math and Statistics 101. You can also include first-principles physics-based calculations that require only simple algebra and make predictions by extrapolating trends – backed by sound engineering assumptions.

The takeaway – start with proven fit-for-purpose analytics before chasing AI/ML PoCs with all its attendant risks, and the false positives/false negatives indicated in the McKinsey post. Form follows function; AI/ML yields to simple analytics. The simpler ‘engineered analytics’ captures the low-hanging wins and provides the foundation and the data-engineering required for the AI/ML layer. The oft-heard “… just give me all your data, let’s put it in a data lake and we will figure it out…” is naïveté.

And a conclusion from McKinsey:

Luckily, while predictive maintenance is probably the best-known approach, there are other powerful ways to enhance a business’s maintenance-service organization and create value from analytics-based technologies. The two most valuable of these, we find, are condition-based maintenance and advanced troubleshooting.

And more from Jonas Berge:

The reason why the existing process sensors are insufficient is because by the time the problem is picked up by the existing process sensors, the problem has already gone too far. You need a change in a signal that indicates an event is about to occur. A pump bearing failure is a good example of this: by the time the bearing failure is visible on the discharge pressure it is already too late because it is a lagging indicator. You need a vibration sensor as a leading indicator where a change signals the bearing is starting to wear.

Lots of time and money can be saved if advanced sensors to collect the required data are put in from the very beginning. With the right sensors in place the AI analytics can do a fabulous job of providing early warning of failure.

I guess I’ll add that it’s not necessarily complex unless you choose to make it. But to say that predictive maintenance is the killer app is overly simplifying things to the point that you’d never really get anywhere—even to make IIoT and IT sales.

A better and more inclusive approach to market solutions could lead IT and OT/IT suppliers into more lucrative hardware, software, and services sales and profits.

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