I finally got some time to collect my thoughts about Wednesday’s virtual conference. There was a bit of Rockwell Automation at the PTC LiveWorx. Wednesday was Rockwell’s turn with ROKLive–the latest, and virtual, iteration of its distributor education series RSTechED and RATechED.
At times over the years, journalists, editors, and writers were not invited to TechEDs. Then they invited us and we sat in sessions. They’ve tried a few executive education days during these events–usually June and usually alternating between Orlando and San Diego. This year was to have been co-located with new partner PTC’s event–until Covid-19 and quarantine.
I received an invitation and link to check out the Digital Transformation track. (Although a refresher on programming PLCs, networking, and drives would have been OK, too.)
This was pretty high level with former P&G vp and consultant Tony Saldanha, Microsoft’s Caglayan Arkan, Gartner’s, Ivar Berntz, LNS’s Matt Littlefield, Cisco’s Paul Didier, and at the end of the day two presenters from Rockwell, Mick Mancuso and Jeff Botsch. There were many more. Some time slots had two speakers and some had three.
A few speakers got pretty high-leveled, but many practical tips came out.
On the one hand, OEE came out a few times. I’m not a fan–mostly because of data collection methodology. You cannot use OEE as a comparison because within the formula are many definitions and common definitions plant-to-plant seldom exist. In fact, one Rockwell presenter acknowledged as much.
While Saldanha was speaking, he mentioned that MRP II (or its ideas) was still in widespread use. That is disheartening. I learned and implemented that way back in the late 70s. I’d hope that everyone had moved way past that by now.
Tips I gleaned from the talks
- We’re benchmarking the wrong companies, you’re competitors are likely to be startups
- When looking for digital transformation projects, look for the 10x opportunities
- Focus on solving problems, not just applying technology
- Consider business objectives first
- People are key, and be aware of workforce issues such as turnover, retirements, training (and I should add diversity)
- Key is to develop agile plants and agile supply chains
- Develop healthy change management processes
- Pay attention to governance issues
I have several more virtual conferences this week. I miss meeting the people, but these have not been as painful as I feared.
There is nothing like a crisis to spur innovation. The Covid-19 pandemic is not an exception. My Inbox runneth over with announcements—all good. Many are safety related, but this innovation reminds us that the controls and automation sector—both suppliers and manufacturers—plays a vital role in bringing vaccines and new therapies to market.
Honeywell announced Fast Track Automation, a combination of proprietary technology innovations for the life sciences industry that enables vital vaccines, treatments and therapies to move from regulatory approval to full production in as little as two months depending on process requirements. The solution incorporates process automation elements that can be configured in a virtual environment, then implemented rapidly once a therapy is approved and ready to be produced for public distribution.
By the way, this reflects a trend in the industry toward packaging products and solutions to make implementation easier and bette for the user.
Fast Track Automation is a response to the global COVID-19 outbreak, which has highlighted the need to accelerate delivery of medical solutions and devices to patients by focusing on ensuring more efficient production and testing capabilities along with facilitating strengthened supply chain. Life sciences manufacturers are leading the race against time to overcome the pandemic through innovative science. At the point in time when clinical trials are nearing completion, the ability to rapidly pivot and scale up to meet production demand will severely test existing technology infrastructures.
The most efficient way to ramp up the production of potential therapies is to facilitate development of commercial-scale manufacturing earlier, while treatments and prevention therapies are still in clinical trials. Fast Track Automation has been designed to be used in development applications in as little as two months, and then to help manufacturers scale up to full production immediately after the appropriate regulatory approvals are granted.
“Honeywell has provided the life sciences industry with consistently innovative advancements in automation technologies, systems and services for over 30 years, and Fast Track Automation offering is one of our most valuable offerings to date,” said Cynthia Pussinen, vice president and general manager, Life Sciences, Honeywell Process Solutions. “Our solution allows for end-to-end manufacturing process and data visualization, providing real-time visibility and predictive insights while offering benefits like enhanced audit-readiness and data integrity, minimized regulatory risk, increased operational efficiencies and reduced rejects and waste.”
Fast Track Automation leverages the power of the cloud, virtualization, batch software running in the controller, flexible assignment of computing power, remote asset management from a data center, and efficient, fast-track lean project implementation.
The technology prepares manufacturing automation designs in parallel with clinical trials to ensure production is ready to go once a medical therapy is approved. Manufacturers can even use the system to digitize manual steps during clinical trials to better consolidate and analyze data and more seamlessly prepare electronic submissions for regulatory body review and approval. Manufacturers can then use that data to prepare the final production automation design. Additionally, the system can be quickly scaled up or down depending on needed changes and demand.
Fast Track Automation is available now.
I never thought I’d sit at home in front of a screen for most of a day (7 am CDT until 3:45 pm CDT) although part of the time I was on my iPhone driving to an errand still watching. In fact, I answered a survey from my friends at Rockwell marketing with a neutral-to-negative view of these virtual conferences. I was actually hoping for the trip to Boston. My wife and I celebrate one of those landmark anniversaries Friday, and I thought Boston would be a good place to celebrate. <sigh>
However, PTC assembled a great group of speakers. The internal speakers were professional quality presenters. Even the weakest presenter of the day was superior to many I see live. Of course product enhancements were emphasized, but thought leadership about where both PTC and Rockwell Automation were heading (Rockwell is an investor and CEO Blake Moret got the unenviable final speech slot) formed the backdrop.
PTC CEO Jim Heppelmann interwove his vision of the company and industry with a variety of product roadmaps and use case examples. To speak “PTC” one had best learn to spell “SaaS”. He enumerated four skills enhanced by cloud-based, or SaaS, applications. Mobility and resiliency; Flexibility–supply chain and production; Bringing digital technology to front-line workers; and, Remote Monitoring (something I’ve been talking to many people about lately).
Going forward, Heppelmann discussed adding AR to IoT and AI leading to “Spatial Computing” and “Spatial Analytics”. PTC has products and applications going in that direction. Listening to him, I immediately saw possibilities.
You can follow my Twitter thread (@garymintchell) for other thoughts of the day. Aside from PTC executives laying out product and application roadmaps, presentations relevant to the day and well done were from Rana el Kaliouby, CEO of Afectiva and author of Girl Decoded (excellent story told on Tim Ferriss blog) who discussed emotional intelligence for technology; Kimberly Bryant told the story of Black Girls CODE–powerful; Nir Eyal discussed ideas on product development from his book Hooked (but I preferred his book Indistractable); and Stacey Higgenbotham, who is the IoT journalist. I think I saw seven of the eight presentations. I think I need an adult beverage!
Moret talked of the many benefits Rockwell Automation has provided to customers through its partnership with PTC and acquisitions of PTC partners. Many years ago, I saw some demos of Rockwell working with CAD/PLM supplier trying to bring that technology and automation together. Siemens did it by acquiring UGS quite a few years ago. That integration seems to have succeeded, but it was rough going for a while. Meanwhile, aside from the important benefits of ThingWorx from PTC, OnShape, the CAD SaaS application, combined with Vuforia products, ThingWorx, and acquisitions in the simulation area potentially make Rockwell extremely competitive in that market.
I think we are seeing PTC and Rockwell Automation breaking out in a new way that is exciting.
[Note: I am an independent writer and thinker, not an analyst who it paid by the companies.]
Suppliers of manufacturing technology have been working diligently for the past couple of months to craft responses to the pandemic engulfing the world. They call these Covid-19 responses. I call them an upgrade to workplace safety. We conquered many safety issues from machines to processes to ergonomics and worker environment. These steps protect workers from each other—or that tiny unseen molecule that can cause much suffering.
This release is from Siemens. In brief:
- Leveraging its software and hardware, Siemens has developed a unique workplace distancing solution that helps manufacturers to simulate and manage employee exposure risks while enabling productivity throughout their facilities
- Combination of Siemens’ SIMATIC Real Time Locating Systems and Xcelerator portfolio help enable customers to manufacture with confidence and future-proof their operations
As preparations are made for what Siemens is calling the “next normal”, manufacturers must consider additional dimensions of employee safety, including the establishment of production environments and workflows that address physical distancing requirements.
Combining its hardware and software, Siemens has created a new solution that enables companies to quickly and efficiently model how employees interact with each other, the production line and plant design. The new solution also enables organizations to build an end-to-end digital twin, in order to simulate worker safety, iterate on and optimize workspace layouts and validate safety and efficiency measures to help future-proof production lines.
With Siemens’ SIMATIC Real Time Locating Systems (RTLS), companies can continuously measure distances between workers, provide real time visual feedback to employees regarding their spacing from others and create a log of all movements and interactions over time. In this way the Siemens’ SIMATIC RTLS continuously facilitates safe distancing while providing numerous additional benefits.
Combining Siemens’ SIMATIC RTLS with a digital twin of the actual manufacturing environment permits companies to model and simulate how employees interact with the equipment and each other, enabling them to iterate and optimize safety and productivity in the short term, and validate a redesign of the entire operation before more costly physical changes are made.
“We are helping our customers create a safe work environment, which is extremely important as they look to produce efficiently and reliably under unprecedented circumstances,” said Tony Hemmelgarn, President and CEO of Siemens Digital Industries Software. “The combination of real time distancing management and digital simulations will help companies maintain safe work environments today and make educated decisions about ongoing and long-term optimization.”
In order to implement this solution, Siemens’ SIMATIC RTLS transponders are embedded in badges which are worn as personal protective equipment by all employees. RTLS receivers placed throughout the operation can then continuously track and record workforce movement. When two employees are in a risk scenario (e.g., less than six feet apart), their badges will display a warning, alerting them to the situation.
The data collected over time can be analyzed to identify “hot spots” where risk scenarios occur frequently. Such situations become easily actionable via the digital twin, which is provided by Siemens’ Tecnomatix Process Simulate and Plant Simulation software. Utilizing the collected data, new manufacturing layouts or workflows can be simulated until one is determined to provide the desired outcomes, which can then be implemented in the physical operation.
Beyond this, manufacturers can add traceability to the solution through Siemens’ on-premise solutions or an application such as Siemens’ Trusted Traceability Application on MindSphere, the cloud-based, open IoT operating system from Siemens, which helps enable rapid, comprehensive contact analysis in the unfortunate event of an actual workplace illness. All movement and contact with the affected employee can be visualized, enabling rapid notification of those who came into close contact and selective (rather than site-wide) deep cleaning of exposed physical environments.
“Siemens is providing a powerful, rapidly deployable solution that helps manufacturers take control of their operations and achieve better safety, productivity and cost outcomes today and in the post-Covid era,” said Raj Batra, President of Digital Industries for Siemens USA. “Our solution consists of proven technologies that can begin delivering results for most manufacturers in one to two weeks.”
Interact Analysis’s new report on the market for predictive maintenance highlights the potential for a new relationship between component manufacturers, OEM machine builders, and end users.
- By 2024, the market for predictive maintenance in motor driven systems is forecast to reach a valuation of $906.1 million
- Enhanced demand for remote monitoring as a result of COVID-19 means there will be no slowdown in market growth
- SaaS is likely to be the main business model for provision of predictive maintenance, and also eases concerns over data ownership
Interact Analysis, my new favorite market research firm, has announced an in-depth examination of the predictive maintenance market. It forecasts a boom in the sector, propelled by the emergence of smart sensors able to monitor crucial parts of a motor-driven system that are not covered by legacy maintenance devices and methods. Advanced smart sensors will allow delivery of viable cloud-based predictive maintenance service packages using a SaaS business model.
One reason I like Interact Analysis right now is methodology. In addition to 40+ hours of primary research interviews, Interact Analysis has utilized data from national manufacturing surveys, as well as data developed for other research areas. This data, combined with the information gathered from interviews, is the base at which estimates are developed.
The report shows that the market for predictive maintenance in 2019 was $117.5 million, largely made up from legacy predictive maintenance products such as portable monitoring devices. Many of these devices will maintain strong growth in the coming decade but will be used in tandem with new technologies such as smart sensors, the latter fueling an expected boom in market value of predictive maintenance technology, up to almost $1 billion in 2024. The significant fall in price of the capacitive based microelectromechanical systems (MEMS) found in Smart Sensors will be one of the drivers of this market.
I like their methodology and analysis—except for forecasting. Predicting future sales is so fraught with uncertainty that I take it as an interesting guide. Evidently sensor manufacturers reported doubling of sales over the two previous years. Look at the numbers and you can see that Interact assumed that doubling to continue through 2024.
When I read through the report synopsis, I was struck by the reliance on smart sensing as a foundation to the market growth for predictive maintenance. I missed a point. They have detected the beginnings of a trend that I have not yet seen. Software-as-a-Service applied to these intelligent devices. Selling the data, not the sensor, so to speak. I’m interested in your feedback on this development. And whether it can drive this market to a billion dollars.
Back to the report:
Smart sensors, which typically monitor sound, temperature, and vibration, may not provide the depth of data offered by some legacy devices, but they have significant advantages. Whereas most legacy devices are attached to motors, IA predicts that only 53% of smart sensors will be attached to motors by 2024. The rest will be attached to other machine components which are also subject to the wear and tear of daily use. This means that the application of predictive maintenance will be far more widespread in the factories of the future.
Blake Griffin, lead analyst on predictive maintenance at Interact Analysis, says: “Smart sensor technology coupled with IIoT capabilities give component manufacturers and OEM machine builders the scope to offer end users an anticipatory service package. For most providers of predictive maintenance, the logical business model will be software as a service. A side benefit of SaaS is that it ties all technologies together under a single solution – thereby eliminating concerns regarding data ownership. Additionally, advancements in embedded machine learning will improve the ability for predictive maintenance to be installed in new or non-standard applications that are less well understood, further fueling growth.”
Adrian Lloyd, CEO of Interact Analysis, adds: “Modern predictive maintenance technology is currently at the beginning of an exponential growth trajectory. Now is a more important time than ever for suppliers to understand key trends at play so they may work at carving out their share of this market – forecast to be worth nearly $1 billion by 2024.”
Griffin further explained the background in a Blog Post. Following are some excerpts.
What are Smart Sensors?
Smart sensors are a fairly new technology that are placed on equipment to gather various data points, most commonly vibration and temperature measurements. Smart sensors then transmit this information wirelessly to a data collector or gateway. When analyzed, this data is particularly useful for assessing the health of equipment as usually the level of vibration and temperature increases as equipment becomes faulty.
How is this Different from Condition Monitoring?
In a traditional condition monitoring system, very little effort is made to determine when equipment will fail, instead relying on set parameters to determine when an asset is at risk of failing. The problem with this approach is that it limits the number of applications which can be monitored. If parameters must be set for an alarm to be triggered, those parameters must be well understood. This decreases the reliability of these systems in applications that are not well understood.
For predictive maintenance to be performed, a level of intelligence must exist somewhere in the plant infrastructure, whether in the form of software, hardware or even application expertise by an experienced operator. A historical log of how the equipment being measured has performed must be utilized to assess if it is trending towards a failure. Increasingly, machine learning algorithms are being utilized to enhance the understanding of the application being measured. This technology utilizes the historical data produced by the smart sensor to better understand and recognize patterns. Having an automated solution for pattern recognition allows for quicker and more reliable detection of anomalies within the data. This not only expands the number of applications able to be monitored beyond just well understood ones, it also increases the amount of time operation managers have to resolve a piece of equipment that is trending towards failure.
Key Driver: A Push for the Realization of Digitalization and IIOT
The most important trend impacting industrial automation is the digitalization of these systems and the equipment within. Over the last 6-7 years, remarkable breakthroughs in technologies that help improve plant efficiency, productivity and reliability have been developed, although uptake so far has been challenging due to the cautious nature of end users when it comes to adopting new technologies.
While these vendors have released software and services aimed at harnessing the benefits of IIoT, it is clear that in order to make use of these solutions, a substantial increase in the number of connected devices is needed. Smart sensors represent an important piece of this puzzle. Since the advent of smart sensors, major automation vendors like ABB, Siemens, WEG, and Nidec have all released their own versions, presumably recognizing the enabling behavior of this technology. We expect this trend to continue as the product is desperately needed in order for manufacturers to begin generating tangible benefits from IIoT technology.