Is it Time for a New Manufacturing Operating Model?

Is it Time for a New Manufacturing Operating Model?

For 30 years since the advent of the Purdue University Computer Integrated Manufacturing (CIM) Model, also referred to as the Purdue Enterprise Reference Architecture (PERA),  manufacturing companies have thought of their business processes and supporting applications as a hierarchy – a pyramid – that starts on the shop floor and goes to the corporate executive offices. This manufacturing operating model has become the basis for most systems deployment strategies. See Figure 1. Now it might be time to challenge this assumption.

Is it Time for a New Manufacturing Operating Model?
Figure 1: PERA Model; source Wikipedia

This hierarchical model has been cemented into manufacturing architecture with standards like ISA95, which has become the most common model defining shop floor application functionality. Conferences and symposia have featured numerous papers on “shop floor-to-top floor integration.”  With the “if it isn’t broken, don’t fix it” mentality so common in manufacturing, the CIM pyramid looks like it may well stand as long and solidly as the pyramids of ancient Egypt. But, with the emergence of the Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and the advanced analytics now available with a data anywhere and everywhere model, it may well be time for the CIM pyramid to get leveled.

The Appeal of the Pyramid

When digital technology came to manufacturing, it first appeared in the corporate finance and accounting systems. With the advent of integrated circuits, the digitalization of process control systems began in earnest. Next came the minicomputer and then the personal computer, which made computing on the shop floor practical. The differences in the openness, communications protocols, and programming of each type led to a natural stratification. 

To promote the adoption of digital technology, Dr. Theodore Williams at Purdue University led a team that both examined the nature of this stratification as well as refined how technology was being deployed. He promoted a way to tie it all together to provide “computer integrated manufacturing” or CIM. Interestingly, the natural layers of the Purdue model also aligned well with the hierarchical organizational structures common in manufacturing in the 20th century. This natural alignment made the Purdue model easy to understand which is why it became so entrenched as a manufacturing operating model.

The Explosion of IIoT and AI Changes Everything for Manufacturers

In the last five or six years the rapid ascendance of wireless communications, smart devices, and anywhere connectivity, the Industrial Internet of Things (IIoT), and artificial intelligence (AI) have emerged as technologies that can effectively handle the vast amounts of data now being generated by manufacturers. The proliferation of IIoT devices has changed the manufacturing landscape and is now challenging the manufacturing operations model. 

At the same time, geopolitical upheavals such as the coronavirus pandemic have forced manufacturers to rethink the way they do business. With work-from-home and social distancing restrictions, the idea of a rigid manufacturing operations model has fallen by the wayside. Organizations are striving to be more agile. The idea that all information must flow up or down a predefined path is no longer manageable. Instead, the long-sought-after concept of making available the right information to the right person at the right time is now an imperative. As operations continue to become more agile, peer-to-peer networks that are adaptive and agile themselves are emerging as a new best practice.

A Historical Perspective 

We can look to the past to better understand why clinging to an existing model can inhibit modernization and change. In the 1800s factories were either powered by water wheels, turbines, or steam engines. These point sources of power resulted in factories that had a centralized power source which then utilized line shafts and belts to power all the machinery. It was then practical to compactly locate these as close to the power source as possible, resulting in cramped and often unsafe factories.

These factories also had to be located close to moving water either as the power source or for the steam engines. When the electric motor was first introduced, it simply replaced the existing single steam or water turbine. It wasn’t until engineers realized that multiple, smaller motors could eliminate the shafts and belts while improving plant safety.   

The Emergence of an Alternative Manufacturing Operating Model 

There are many parallels between electricity as a technology disruptor and what is now possible from the IIoT and advanced computing technologies. Manufacturers can now leverage vast amounts of data to gain insights and manage operations processes in different ways – previously not considered possible. The first stage of today’s digital transformation has been to simply replace components of an existing operating architecture. The next stage is to rethink how to better manufacture new products with greater value, for less cost. 

Smart devices that operate anywhere are now empowering manufacturers to rethink the way they operate and maintain their facilities just as electricity did over 125 years ago. Where are you at with your business transformation – still in stage 1, or have you moved on to exploring new ways to grow your business or product suite? Will your manufacturing applications be able to support this new model or are they built assuming that the CIM pyramid will stand as long as the real ones have?

Whitepaper: Digital Manufacturing

Recent Ransomware Attacks Against Manufacturers Highlight the Need for Business/Government Security Collaboration

Ransomware Attacks

The last several months have resulted in several major industrial cybersecurity (ICS) incidents, primarily ransomware attacks. This highlights the challenges in using technology in manufacturing today. The reality for manufacturers is that it is virtually impossible to insulate your plant from a cybercriminal determined to breach your systems.  Of course, you should do your utmost to select and implement the most secure technology you can find. Putting in place a robust cybersecurity program will limit potential exposure to a ransomware attack. Lastly, providing training for employees is a smart defense to help ensure your investments are fully utilized. 

Despite these preventive measures, you must also prepare for the eventuality that your facility, division, or company may ultimately fall victim. This means that you need to have a plan that is already in place where know in advance who you can work with from the government to recover your operations quickly while minimizing the costs to do so. 

The Colonial Pipelines ransomware attack initially focused on Colonial paying the ransom, and while the FBI was able to recover the majority of it, the incident created supply chain disruptions that rippled throughout the US.  According to the company, The Colonial Pipeline provides roughly 45 percent of the fuel for the East Coast. You need to ensure if you are hit you can achieve a resolution that minimizes the disruption while working with authorities to minimize the financial downside. Collaborating with the appropriate government agencies now and advocating for a strong national industrial cybersecurity program is in a manufacturer’s best interest.

Forewarned is Forearmed

The US government has funded extensive cybersecurity research, much of it through the MITRE Corporation, a not-for-profit entity that manages six Federally Funded Research and Development Centers. One of the outputs of this research is the MITRE ATT&CK Framework. This free and accessible framework provides a knowledge base of ICS threats, current activity, and models of attacks. 

To properly defend against ICS threats is to fully understand the scale and scope of the threats. By modeling your environment and running it through the ATT&CK protocols, a manufacturer can be in a much better position to not only defend against attack but also how to respond more effectively and reduce exposure. 

Read more about cybersecurity threats, Aerospace Manufacturing Cybersecurity is More than Classified Design Information

An Ounce of Prevention is Worth a Pound of Cure

Once you understand your vulnerabilities the first task should be to implement preventative tools to both put policies and protocols in place to minimize exposure and then to put in place detection and prevention technology.  Putting tools in place without the proper staff education and support will effectively negate the security investment and likely result in a breach.  

Your technology architecture plays an important part in your security profile.  Proper architecture, populated with solutions from suppliers that themselves prioritize security, is your best defense against penetration.  Of course, good backup and recovery practices are an important part of your cybersecurity program. But, as recent events have shown, cybercriminals are relentless, and threats are constantly evolving. 

Consequently, another part of your cybersecurity program must be a continual reevaluation of threats and exercises to test your response capabilities. In that way, if an incident does occur, you can respond quickly to minimize exposure. 

Government Involvement is Essential with Ransomware Attacks

Often companies are reluctant to involve authorities during a cyber incident because of a fear of bad publicity or further attacks. If your car is stolen and you don’t report it to the police, the odds of you recovering the vehicle are virtually nonexistent.  The same applies to these cybersecurity incidents. 

Failure to work with appropriate authorities after ransomware attacks virtually guarantees that you are setting yourself up for further exploitation. But just as a strong neighborhood watch program in cooperation with local law enforcement can reduce the probability of your car being stolen, working with Federal cybersecurity agencies, appropriate to your industry, can be an effective part of your overall defense strategy. 

Manufacturers should also have a strong interest in encouraging government action as a preventative measure as well. It is in your company’s best interest if cybercrime is vigorously prosecuted. The international aspect of most cybercrime requires Federal action. Make it a priority to support legislation that puts cybersecurity on par with other national defense interests.

Inevitability of Smart Manufacturing

How Lessons Learned from the Coronavirus Pandemic Can Drive Future Growth

How Lessons Learned from the Coronavirus Pandemic Can Drive Future Growth

Manufacturers had to make several adjustments to function throughout the 2020/21 COVID-19 pandemic. As we look to the future when work-from-home, restricted travel, and social distancing mandates go away, the technology investments that were made to operate during the pandemic should not be thrown out the window. Many of those investments delivered new capabilities and efficiencies that should be carried forward as manufacturers look to the future.  Here are four lessons learned from the coronavirus pandemic that I have observed that can be leveraged to drive new growth opportunities. Given all that has been done to change how we work – is there a way to get more value from all this investment? 

Moving from Remote Work to Sharing Expertise and Working Anywhere

During the pandemic, our industry had to come to grips with enforced lockdowns that relegated many of their staff to a work at home or remote working model. Companies that invested in video conferencing, collaboration, and secure networking technologies so technical, support, and supervisory employees could access corporate systems. 

As vaccination adoption starts to get us closer to “normal,” avoid the temptation to return to business-as-usual. Manufacturers should leverage this remote access to improve the quality of their workforce as well as making the expertise of their most skilled staff more widely available. 

Learn more in my recently published Forbes article, Why Digital Investment Is A Smart Bet In Facing Today’s Manufacturing Labor Shortage.

By leveraging remote access, manufacturers can recruit and have access to a much larger pool of potential employees who may not wish to relocate to your location but have the skills you critically need. At the same time, you can leverage your newly developed collaboration platforms to allow the best-of-the-best of your experts to share their expertise across your organization and extended value chain.

Sustaining Safety and Operational Best Practices 

Another one of the lessons learned from the coronavirus pandemic is how to operate with greater safety and hygiene. The mandated social distancing, contact tracing, sanitation, and masking requirements we have been practicing led our customers to invest in technologies such as RFID, Wi-Fi, or GPS technologies to enforce social distancing rules. This data helped to aid in contact tracing when positive exposures occurred. Visual recognition technology investments helped to enforce masking requirements in some plants. 

Artificial Intelligence (AI) and other technology investments such as robotics helped some manufacturers develop and deploy automation that helped reduce the need for human interaction and reduce sanitation requirements.

Learn more about the increasing role of AI in manufacturing by reading this article, Artificial Intelligence (AI) in Manufacturing: The Revolution is Here.

All these investments can be leveraged to maintain the labor productivity and safety gains that were achieved during the pandemic. Auto-detection of proper safety equipment use, using tracing technologies to enforce human to automated machine interlocks, and expansion of the use of robots, can all further improve safety and productivity gains.

Leveraging Cloud and Remote Support to Reduce Technical Debt

While Manufacturing Execution Systems (MES) have been migrating to the Cloud for several years, the pandemic accelerated this trend. With travel restrictions precluding on-site installation of upgrades or new systems, Cloud deployment became a way for manufacturers to gain access to the latest capabilities during COVID-19. Those utilizing a cloud-native application architecture not only benefit from their initial Cloud investment, but as each iterative version of the software is deployed in the Cloud, access is immediate to incremental improvements as well.

When coupled with the ability to rely on remote support or a cloud-hosted MES application, technical debt can be minimized.  Manufacturers that have not yet migrated to the Cloud should do so as soon as possible. Those that did should strive to take advantage of new product capabilities as they are introduced to foster a continuous improvement culture in their operations – a necessary attribute in the journey to identify future opportunities for growth.

Remaining Resilient and Agile

Perhaps one of the biggest lessons learned from the coronavirus pandemic was that manufacturers had to become far more resilient. The need to adapt quickly to a rapidly evolving environment became paramount. From labor and working situations to supply chain challenges, manufacturers that survived the pandemic had to be more agile as CDC guidance and local regulations continued to change as the pandemic evolved. 

When we return to what our new “normalcy” becomes, manufacturers should avoid the temptation to return to “business as usual”. While bringing the entire workforce back to the plant or office may seem like a way to simplify operations and get them back to pre-Covid performance, the odds are that you will forfeit much of the agility your company developed over the last 18 months.

I would propose that the greatest lesson that smart manufacturers will have learned from the pandemic is that they can be more agile and adapt faster to change and challenges – much more so than previously considered. This realization opens the door to new business and growth opportunities that might now be possible with minimal additional new investment. Those that constantly strive to maintain that agility and leverage it will be rewarded, starting by staying ahead of their competition.

Digital Thread Guide

Artificial Intelligence (AI) in Manufacturing: The Revolution is Here

Artificial Intelligence (AI) in Manufacturing: The Revolution is Here

Depending on whom you ask, artificial intelligence will either be the dawn of a bright new era, or the end of humanity. Many smart people have taken the more pessimistic view. The late Stephen Hawking in 2014 believed that AI poses an existential threat. The philosopher Nick Bostrom has been raising the alarm for years, writing and speaking extensively about the possible dangers of AI. Others say AI will usher in a new age of prosperity, with people living longer and healthier lives. Wealth will be generated by machines, and people will be freed from the drudgery of existence. The truth will likely come in somewhere between. But make no mistake, like many other aspects of life, AI in manufacturing is coming fast, and it will be a revolutionary force. In fact, it already is.

The Thirst for Data is Being Driven by Artificial Intelligence

Just look around. Just like AI in manufacturing, the use of Artificial Intelligence is increasing year by year across virtually every industry. Computers currently do the majority of trading on Wall Street, bartering millions of trades per second based on AI algorithms running on neural networks, informed by machine learning, in buildings housed as close as possible to the stock exchange because even at the speed of light, a few city blocks can make a difference. AI is using nanoseconds to make pennies per trade and generate millions in profits.

Automation and computing power now commonly rules in domains once thought to be the sole province of humans. Take chess, for example. In 1997, the IBM computer Deep Blue defeated the world’s greatest chess player at the time, Garry Kasparov. Within fifteen years, computers were unbeatable by human players. And in 2017, Google’s Deep Mind project unveiled the AlphaZero chess program. It was told the rules of chess and given four hours to practice by playing millions of games with itself. It then proceeded to crush the reigning computer champion, Stockfish, 28 to 0 (with 72 draws). What it learned, all by itself, was a new approach to chess that has changed the theory and practice of the game at the highest levels.

The Evolving Nature of Artificial Intelligence 

So far, these are all examples of Artificial Narrow Intelligence (ANI), or special-purpose AI. The next step would be Artificial General Intelligence (AGI), machines that are able to reason, plan, and comprehend like a human about any subject. That kind of AI is still at least a few decades away, but a different kind of machine intelligence is all around us right now. 

Elon Musk says that we’re cyborgs already, linked to our phones and other devices. Not physically linked—yet—but linked, nonetheless. The next step would be to implant AI enhancements into our skull, and yes, there’s a procedure worked out for how that might be done, and how the chip could interact with our brain.

AI in Manufacturing Driving Development

This is all fascinating to think about, but does any of it relate to manufacturing today and the next few years? I think it does, and more than just a little bit. 

It’s only fitting that manufacturing is a key driver of applied AI. After all, manufacturing has been the economic force behind robotics development for decades, from the early tape-fed NPC machines to today’s industrial robots with vision, mobility, arms, and the ability to make simple decisions. Robots and AI are not equivalent, but they converge on the factory floor, where automated systems have been evolving more and more intelligence over the years.

More importantly, the collective power of these systems is growing exponentially. With the IIoT, intelligent robots increasingly linking to other intelligent robots. And, they’re all reporting up the line to digital platforms including Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) systems. The connectivity is even extending to executives with smartphones and tablets who can access data analytics and manufacturing intelligence applications to see trends, identify correlations, predict outcomes, and guide decisions. 

When you consider the prevalence of machine learning being in more and more applications, it soon becomes clear that AI is already on the shop floor. The modern manufacturing decision-maker is the personification of Musk’s virtual cyborg with digital tools now an essential ingredient to success.

What Will be Next?

The impact of AI’s exploding digital power is being felt throughout the manufacturing world. But, it is more than another technology. AI in manufacturing is changing how we work and think, sometimes profoundly, in the executive suite as well as on the factory floor. In fact, a new term is emerging, “hyper-automation,” which is taking task automation to the next level by incorporating processes spanning multiple departments and automating responses, all being made possible with the use of AI.

So, will human-looking robots be sitting in the corner office someday soon, giving orders to other robots in metal cubicles? Somehow, I don’t think that’s what the future holds. What does seem inevitable, however, is that we will continue to rapidly adopt AI technology to help us make better decisions, faster. I know that’s true, because that’s what humans have always done with technology ever since the first tool was invented. It’s what we do.

As far as where artificial intelligence will eventually lead, in manufacturing and elsewhere, we’ll have to wait and see. But we may not have to wait as long as we think.

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iBase-t Launches Knowledge-Centered Service to Support Customer Growth

iBase-t Launches Knowledge-Centered Service to Support Customer Growth

Knowledge-Centered Service Program supports iBase-t software solutions with quick resolution to customer inquiries

FOOTHILL RANCH, Calif. – Aug 3, 2021 iBase-t, the company that simplifies how complex products are built and maintained, today announced the launch of a Knowledge-Centered Service (KCS) program that is intended to simplify resolution of customer support inquiries. As a self-service support program, its aim is to improve support productivity as iBase-t continues its growth trajectory. 

The KCS methodology, as defined by the KCS Academy, establishes a knowledge platform to accelerate the successful outcome of customer support issues. By documenting and sharing issues as they arise, a valuable repository of usage intelligence will be available as a customer reference tool. Further, this information can then be incorporated into future product releases. 

The program has already yielded significant results, including:

  • 50% improved average time to resolution
  • 30% increase in first contact resolution
  • 20% improvement in customer satisfaction

Over the past 90 days, overall iBase-t customer satisfaction has increased to 91 percent, an improvement that was made possible by this and other new programs launched by the Company over the first half of 2021.

“By simplifying how complex customer support knowledge is captured and shared, we can be sure our customers can have their needs taken care of in the fastest way possible, and on their schedule,” said Scott Baril, Chief Customer Officer at iBase-t. “This is further testament to our continued investment in business systems and processes that improve our customers’ experience, while at the same time support the company’s scale of growth now underway.”

About iBase-t
iBase-t is a software company that simplifies how complex products are built and maintained. Founded in Southern California in 1986, iBase-t solutions ensure digital continuity across manufacturing, quality, and maintenance, repair, and overhaul (MRO) operations on a global scale. The iSeries, powered by Solumina, is a cloud-native platform that establishes a digital ecosystem to drive innovation and improve operational performance. With offices in the U.S., UK, France, and India, iBase-t customers include Lockheed Martin, Northrop Grumman, Rolls Royce, Pratt & Whitney, and Textron. Learn more at