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Sunday, May 28, 2023

The Genius of the Toyota Production System Explained

So much has been written about the Toyota Production System (TPS) that you may be wondering why in this day and age were the focus of most of this blog is on digitalization and Industry 4.0, I am bringing this topic back up? It should be no surprise that regardless of the paradigm shift that is going on Lean and the principles of TPS are still real and valid. The reason is that under all the tactical concepts that we in general refer to as "Lean Manufacturing" it addresses a basic characteristic of all manufacturing systems and that is that they are inherently chaotic! In fact they are a special type of chaotic system called Complex Adaptive System or CAS, a topic that I believe is critically important to understand in these transformational times.

McElroy, Mark. (2000). Integrating Complexity Theory, Knowledge Management, and Organizational Learning. Journal of Knowledge Management. 

Before explaining what Chaos and CAS are and why I believe this to be true, I wanted to state the conclusion. The genius of TPS is that the concepts and strategies that it employees are directly built to use the characteristics of the CAS to its advantage, ie to increase value and productivity. The two fundamental concepts that are central to Lean and TPS that back this hypothesis are:
  • Understanding that adaptability to change is critical. Lean provides for effective management small deviation and big changes with a focused and controlled manner with strong discipline, clear objectives and effective execution. Examples are Andons, Kaizen, Gemba, Hoshin Kanri, Poke Yoke, etc. that are designed to provide an effective way to deal with the repeatable patterns (good or bad) within the system.
  • Understanding the boundaries between chaotic dynamics and order. Lean strives to coral the unpredictable nature of CAS by making a discrete non linear system more linear. Reducing batch size, making value flow, JIT, Heijunka, Kanban, SMED, etc. makes the system more continuous and less discrete and therefore more predictable.
In order to better understand this premise, I really need to provide a primer about Chaos and Complex Adaptive Systems. First a disclaimer - this is a diverse and complex topic and the following explanation is very high level and simplistic. Chaos sometimes is confused with randomness, however it is different. Here is a simple comparison:




Unpredictable Path

Unpredictable Pattern

Unpredictable Path

Predictable Pattern

Predictable Path

Predictable Pattern

This means that systems that exhibit chaotic behavior are impossible to predict but they have predictable patterns that repeat. On a side note; we as humans are very good at identifying patterns, which means we are inherently very good at operating in chaos. That is also what AI is good at and why its application in manufacturing context is so interesting and offers so much potential. 

As mentioned a CAS is a special type of chaotic system that exhibit chaotic dynamics and emergent behavior and includes of course our favorite system the manufacturing organization. Other examples of CAS are weather, traffic, ant colonies, the stock market, social and organizations. A CAS behaves and evolves according to three key principles:
  • Order and control is emergent. The overall behavior of the system of elements is not predicted by the behavior of the individual elements. There is a natural transition between equilibrium points through environmental adaptation and self-organization.
  • The system's history is irreversible or irreducible. Irreversible process transformations cannot be reduced back to its original state. They evolve and their past is co-responsible for their present behavior.
  • The system's future is often unpredictable. Non linear and therefore not predictable but yet have repeatable identifiable pattern. Predetermined patterns within their complexity describe potential evolutions of the system. 
OK, now with this information we can reflect on what this means in the context of Lean and TPS. Jim Womack famously defined the 5 principle of Lean as a result of studying TPS and how it works. By looking at how each of these principles is directly designed to use the characteristic of a CAS the genius of TPS is revealed.
Lean Thinking (1996), James P. Womack and Daniel T. Jones
  • Identify Value: This is in fact not directly related to the manufacturing being a CAS, it is really just a sound business principles. I.e. make sure to have clear objectives and know what to focus on- similar to Deming's "consistency of purpose". Identifying the value stream provides the framework for prioritization of how and where to optimize.
  • Map the Value Stream: Understanding the value creation process and the details in the value stream helps in understanding the specific key attributes that impact the behavior of the system. In a CAS there are dependencies between key attributes and specific patterns that indicate either good or bad behaviors. This is to understand what in the value stream may trigger unwanted states, ie.e the famous "butterfly effect". For example the rectangles drawn on the weather forecast indicating that a Tornado is likely.   
  • Create Flow: Make sure that the production value stream flows since systems that flow are continuous and more linear in contrast to nature of discrete "stop and go" type of behavior. Reducing the unit size (one piece flow) eases flow, with the smaller the unit the better. Without consistent flow the system becomes more non-linear and may exhibit catastrophic patterns. For example getting stuck behind the guy who can't out of the way when boarding a plane (exemplified by Mythbusters). 
  • Establish Pull: Consistent flow can be nearly guaranteed if you pull rather than push the elements of the system. It secures blockages are identified immediately and removed, simply because you can't pull with something in the way. Think what happens when you are behind two trucks overtaking on a highway causing traffic to backup.  
  • Seek Perfection: This principle is to ensure that we can keep the CAS in states that we can predict. By striving to keep the manufacturing system as close as possible to linear (consistent flow) we can predict and guarantee performance and behavior. However it also provide tools to identify unwanted patterns and ways to quickly address states that are undesirable.     
Toyota has always advocated a cautious approach to new technology and that is a a problem. The n-1  approach to technology advocated by Lean (the use of proven technology, not the latest and greatest) is sometimes used as an excuse to maintain status quo. In these times of change with all the new digital technology available this seemingly puts Lean companies at a disadvantage. However if you approach these technologies as a way to Lean, to reduce waste, to create flow and execute pull then the value of the technology can easily outweigh the risk. In addition the n-1 concept was really meant for production equipment, i.e. to not increase the risk of interrupting the production flow and quality issues.

Its important to understand how digital technology can be used to support a Lean system. Remember the new paradigm offers an order of magnitude productivity increase and herein lies key motivator. Digital transformation needs to support a lean system, it has provide additional tools in the Lean toolbox. Digital technology can be catalyst to a Lean organization where continuous improvement happens faster and more effectively and that is how the "order of magnitude increase" is realized.

So the genius of TPS is simply put that Toyoda understood behavioral dynamics of his manufacturing operation even without knowing its a CAS and was able to put together a management strategy to directly impact the characteristics of the system with optimization in mind. When operational principles are nicely aligned with the science behind it there its not a surprise that its successful. We should now do the same to transform lean operations with digital tools so that we can hit the digital transformation jackpot. 

Saturday, May 20, 2023

How Electricity Goes Around the Bend & Where is the Electricity Manager?

The Ghost Town

I recently was on a motorcycle ride to Bodie, a gold rush ghost town in California that is now a state park. I was fortunate enough to be with Mark, who apart from running motorcycle adventure rides, who is also is a bit of a gold rush history buff. He told a story about how electricity was perceived during the boom days at Bodie.

Electricity first came to the gold rush mining towns in the California desert of the Eastern Sierras in the 1890s and it was, as you would expect, quite a spectacle. It brought with it a major change in the way gold was mined and processed and offered great productivity increases.  At the the time there was a common misconception that the electricity power lines had to be run straight because the electricity would shoot out if it there was a bend in the line. Basically it could not flow around a bent or wire that changes direction.  Here is a bit more background from Chat GPT: "Did people believe that electricity can't flow through a bent wire in the gold rush towns?"

"One popular misconception of the time was that electricity followed the path of least resistance. In this context, the notion that electricity could not flow through a bent wire might have arisen. People might have believed that the bent shape of the wire created a higher resistance, hindering the flow of electricity."

Considering that this was a new technology that was brought to remote towns where the living, to say the least, was hard and dangerous such a misconception seems reasonable. Yet we can draw some striking similarities with this scenario and the introduction of digital technologies to manufacturing plants. Manufacturing plants are operational islands where financial survival is always a top priority and digital technology is not fully understood, or maybe understanding it is not the most important priority. Like electricity in the gold rush town, its hard to relate to a new technology that has lofty and even ungrounded promises such as "a fundamental change to how we live and operate" and "an order of magnitude productivity increase".

Managing Electricity

During the 2nd industrial revolution, where we transformed from steam to electricity all plants had an "Electricity Manager". Again Chat-GPT for some wisdom: "what was the role of the electricity manager during the 2nd industrial revolution?"

"Overall, the role of an electricity manager during the Second Industrial Revolution involved overseeing the generation, distribution, and management of electricity. Their responsibilities encompassed technical, safety, operational, and financial aspects to ensure the reliable and efficient supply of electrical power to support industrial and societal advancements during this transformative period."

So clearly we do not have this role in our manufacturing plants today, we simply pay for electricity as a service. Does this sounds eerily similar to the current roles of CIO or CDO in managing digital technology? What is the destiny of IT organization and CIOs? Will XaaS (Anything as a Service) become common place and make IT redundant?

Oh the Skepticism

I tell these stories to most skeptics that I meet in an attempt to explain that a new paradigm requires new thinking. We will not be able to experience productivity increases until we realize that what we have at our hands is so different than anything we have seen before. In other words electricity does flow around bent wires, data is safe in the cloud, citizen developers can build complex systems, you can validate a solution in hours, control of democratized technology is easy, IIoT can be safe, it's also for all size companies, etc. Oh and one more that is quite controversial; MES, LIMS, WMS, etc. are not digital technologies - they are relics of the previous industrial age (industry 3.0). They are what steam was to electricity!

The challenge that I face on a daily basis is how to dispel the myths of digital technology and relieve the skepticism that is inherent in most manufacturing organizations? This is in the perspective of the bigger challenge that is how do we plan to transform industry so they can start capitalizing at the order of magnitude productivity gains. In the words of Søren Kierkegaard: "Life can only be understood backwards; but it must be lived forwards."

Saturday, May 6, 2023

Are we seeing the return of the Custom MES, or is it something else? (Re-Posted)

The role of MES in the Industry 4.0 reality is a topic of debate and a source of critical misinformation. In general MES belongs to the era of automation and computer integrated manufacturing, i.e. Industry 3.0. MES or MoM came about in the 1990s to solve the challenges of coordinating and executing work on shop floors with the advent of computers. It really is a relic of the previous industrial era.

The challenge of coordinating and executing work on shop floors however has not changed. Manufacturing is increasing in complexity and the need to adapt to changing business requirements is accelerating. At the same time the advancement in computer technologies have ushered a new digital era that we now call Industry 4.0. How do we solve the shop floor operational challenge with these new technologies?

Are these new digital technologies making it attractive and maybe even necessary to develop custom manufacturing systems solutions, or custom MESs? For years we have advocated that companies focus on their core business competencies and leave the software development to expert best in class software companies. There are many horror stories of companies that are stuck supporting custom built software that is running their critical operations, why build and spend millions maintaining in house developed systems?

Yet the need to tailored solutions for shop floor operations is still valid and in fact even more critical as the rate of change to the business environment coupled with operational complexity increases. It seems like a case of history repeating itself since that is how MESs started in the 80s, however technologies have vastly evolved since. With the digital technologies that are now available we are going well past the simple ability to customize. We are taking a very different approach that is operations and human centric. It allows us to rapidly create tailored solutions that increase productivity by supporting frontline operators for each specific operation and activity.

This allows companies to once again opt to develop custom solutions to solve their manufacturing systems needs. Yet this time around they do not look like MES of the past, they are not custom solutions that are unique and require high cost and effort to manage and maintain. In the digital era solutions are built rapidly by the people that are closest to the operations, they are tailored to the frontline operator and help increase their productivity and all of this in a Cloud-Edge infrastructure that allows easy management and governance. There are a number of forces at play that are causing this to happen.

Emerging digital technologies, specifically no-code cloud based SaaS platforms provide user friendly ways to build tailored digital content with very quick ramp-up times. I.e. you don’t need software development skills. There is a real business need to get the promised productivity gains from these digital technologies. In other words organizations have allocated money and people to get things moving in their digital transformation.

The new generation of workforce comes from the digital age (i.e. digital natives) and are used to in simple words, just download an app for that. They are confronted with what they see as antiquated software systems that are not really user friendly and their reaction is to find another app. The new digital technologies aimed at the manufacturing operations space are in general human centered – they aim to solve (and support) what we as people do, whereas traditional MES is developed to automate a process.

Modern cloud and edge technologies provide a rich playing field for integration and capture of digital data to help bridge the digital divide. I.e. start capitalizing on productivity improvements while not having to decommission existing traditional systems.    

The transformational forces at play are unstoppable at this point. The high skill and expertise level required to implement and maintain the current IT/OT owned systems are becoming a thing of the past. The new tailored manufacturing solutions can be built at a unprecedented speeds by people that are closer to the actual manufacturing process. We will not have unique and specific monolithic systems for each department or business function. The future digital factory will be supported by a network of digital components, apps, edge devices and tools will have been composed in a iterative and agile process, ie bottom-up. Solutions will emerge and mature over time based on continuous improvement rather than a top-down design and development process. With that traditional hierarchical thinking and approaches such as ISA-95/88 will become less relevant unless they are adjusted to fit the new digital reality.

Are we then seeing a case of history repeating itself? Will we see a resurgence of home grown MES solutions that we will in a few years pay dearly to maintain or replace? The answer is yes but not what you might expect. There will be some level of custom software being built but at the same time what we will se are tailored solutions that do not carry the burden of the custom system of the past. Modern digital technologies such as no-code platforms are democratizing the manufacturing systems landscape. They are transforming manufacturing systems software development to a process of composing digital content for the shop floor. They are more of an engineering and operations toolset rather than an IT system. Again we might use the term MES but these new solution will really not look like anything that resembles current MESs, they will consist of digital content that support human operations and digitize all activities and process in the plant. They provide unprecedented levels of detail in the form digital data that is easy to use, analyze and interpret. They provide the foundation for digital maturity toward the predictive and adaptable states in Industry 4.0. Companies adopting these platforms will be able to accelerate their maturity and their digital transformation.

This is a reposting of an article in Engineers Outlook and is based on a previous post on this blog The return of custom built manufacturing software.