When the Toyota Way meets Industry 4.0
Society has reached a point where we can push a button and be immediately flooded with technical and managerial information. All of this is very convenient, of course, but if we are not careful, we risk losing the ability to think. We must remember that, in the end, it is the individual human being who must solve problems.
- Eiji Toyoda, “Creativity, Challenge and Courage”, Toyota Motor Corporation, 1983.
In the 1990s, Toyota's principles for production equipment became “simple, slim and flexible,” which some people might interpret as “go slow on adopting new technologies.” In the modern era of light-speed technological change, especially in the digital world, I believe that would be a mistake. The real message here is: adopt and adapt technology that supports your people and your processes. That is the starting point. Where are the real needs that technology can address to help you achieve your goals? This is a matter of pulling technology based on opportunity, rather than pushing technology because it is the latest fad.
This simple lesson becomes more relevant every day. It seems clear to me that technology in the digital age can support lean thinking. The point is to avoid the temptation to buy and implement the latest impressive digital tools instead of integrating technology in a structured way with highly developed people and processes.
Toyota's largest supplier, Denso, has made remarkable progress in adapting real-time data collection, the Internet of Things (IOT) and data analytics to support lean systems and amplify kaizen. At the heart of Denso's approach are people and their ability to sense reality and think creatively. Denso shows that technology has greater potential when there is a culture of continuous improvement and people are highly developed.
Raja Shembekar, vice president of Denso's North American Production Innovation Center, is the chief architect in the use of the Internet of Things. As a starting point, Raja benchmarked other companies considered technology leaders. He found a lot of what he called “IOT wallpaper” with little real application. Pretty monitors without real problem solving. He concluded that Denso needed to take responsibility and lead its own effort, starting by treating the plant in Battle Creek, Michigan, as a pilot site. He built a small team of roughly half IOT specialists and half people from the shop floor, such as quality managers who were good at software. Together, they began working on real problems that had been identified at the gemba.
For example, they have huge brazing furnaces, which are needed to make aluminum heat exchangers. It is critical to keep the temperature constant throughout the furnace, and they do this using twelve expensive fans, each the size of a table. If a single fan stops, it takes 12 hours to cool the furnace down from 700 degrees Celsius, 12 hours to replace the fan and another 12 hours to bring it back up. With small sensors on each fan and an IOT system, they can monitor the condition and alert maintenance when there is any degradation, long before a shutdown occurs. Once, Denso's data scientists reported to maintenance that a fan was going to fail in 58 hours and that they should replace it. Raja explained: “Maintenance didn't believe it, but we asked them to change it anyway. They took the fan out and saw that half of the blades had disintegrated. They were completely shocked that they had no idea this was happening and that we were able to provide that prediction.”
In another example, they focused on directly assisting the operator in an automated assembly process with robots. We are used to the idea of operators filling in a control chart with upper and lower control limits and taking action before the process goes out of control. This system continuously develops a control chart in real time. While watching it, we noticed a few minutes beforehand that the process was going out of control, and the operator made an adjustment, quickly correcting the problem.
A more ambitious project that reveals the TPS focus is automated standardized work support. Raja found a Stanford professor who was working on “motion technology.” A camera films a person and can analyze the data in real time with AI, breaking down, for example, actions into work steps. Raja saw the potential to revolutionize standardized work and collaborated with the professor, who now has a thriving company. This will sound familiar to anyone with experience in standardized work – steps and times versus takt, operator balance charts and, in fact, real-time auditing that identifies deviations from standardized work. The analyst doesn't need to waste time creating all those spreadsheets and can identify every case in which the line stopped, or every case in which there was some kind of deviation from the standard, and go back and watch the video. What was the operator really doing at that moment? This technology is attracting broad interest around the world – including at Toyota.
Does technology hinder, replace or enhance?
A key question, ever since I began studying the impact of computer-integrated technology in the 1980s, is: does technology hinder, replace or enhance? And the answer is that it depends on the management philosophy. Consider two different approaches: the mechanistic and the organic. From a mechanistic perspective, the value of technology is clear – replace people, monitor those who remain and control them with clear instructions on what to do. Implement technology quickly and broadly to remove the unpredictable human element.
From an organic systems perspective, the value of technology is very different. When combined with highly developed people motivated by the goals of serving the customer and helping the company, it can multiply kaizen – faster and better.
Raja made it clear which side he was on. Denso's focus was not to use technology to get rid of people, although he had no doubt that, over time, fewer people would be needed in the factory. Although there were cases in which a closed-loop technical system automatically diagnosed and corrected problems, there were many problems that required human ingenuity and intervention. In fact, Raja is certain that people's skill requirements need to grow:
“We will always need people, but their skill level needs to change completely over time. Technology provides data that allows associates and team leaders at the gemba to provide a much higher level of decision making. In the past, they just filled out paperwork, but by the time they had done all that, they had no time or energy to really understand the data. If they wanted to see trends from, say, five days ago or across people, it simply wasn't possible. What this system provides is what we now call fast PDCA. We can no longer have a PDCA that takes 3 weeks. We want a PDCA done before the end of the shift.”
At Denso in Japan, they operate on the belief that IOT does not take people out of the loop, but provides people with superior information about the process. The power of big data and artificial intelligence is to give the operator just-in-time information that they previously had to guess at. But Denso expects the operator to use that information creatively to find the root cause and solve the problem through kaizen. Denso calls this “collaborative creation and growth of humans, things and equipment.” An irony may result from this. Historically, an important role of industrial engineers was to reduce the number of workers needed. Now, technology may enable workers to eliminate the industrial engineers.
Balancing adoption of the latest technology with effectiveness
Toyota is a technologically advanced company and has been for decades – turn off its computer systems and you will shut the company down. But Toyota is not interested in being fashionable and making the adoption of new technologies an end in itself. Just as Toyota refuses to schedule in a way that pushes parts made by one department to another, it also refuses to allow the information technology or advanced manufacturing technology department to push technology onto the departments that do the value-added work of designing and building cars. Any information technology must pass the acid test to see if it really supports people and processes and prove that it adds value before being broadly implemented. And then ownership of introducing the new technology falls to existing management. They will run it, they will be accountable for meeting the goals and they must lead the introduction.
The problem, as I see it, is that people who live in the software world seem to believe that if they can do a demonstration based on a simulated example, it will translate perfectly into solving real problems. That is the thinking that got many companies into trouble in the 1980s. And that was the situation Raja found in the 21st century when he was exploring Industry 4.0 software. I was skeptical before talking with Raja about the bold concept of a fully automated factory with everything being run by internet connections, big data and AI – and Raja confirmed my suspicions that it could be a lot of flash in the pan. On the other hand, I also understood the power of the technology. I am now convinced that it is here to stay, and that includes the technologies that were missing from the first failed attempts to computerize factories in the 1980s. It seems they were not completely wrong about the potential; they were just too far ahead of their time.
It also became clear, from seeing what Raja has been doing at Denso's Battle Creek plant, that Industry 4.0 is not a disruptive force that makes TPS irrelevant, but an enabler that builds on the culture and thinking of TPS. After all, the Internet of Things necessarily includes things. And if the things are poorly designed, poorly planned and poorly maintained, the software will not solve the problem.
The difference between Denso and the companies that are creating electronic wallpaper seems to be a matter of mindset. Denso starts with the problem and then builds the social and technical systems to help solve the problem. It builds on its existing culture of disciplined execution and problem solving. Without that, companies are forced to throw technology on the table and hope it works. The principles of TPS will not disappear from a company like Denso, but the way the factory operates at the junction of TPS and IOT will be very different.
I was fascinated by the IOT technologies I saw at Denso, but in the back of my mind I could not help thinking about the concerns of the Toyota Production System. TPS forces people to think deeply to solve problems. Will computer systems make us lazy thinkers? How can we marry the powerful information coming out of computers with people's creativity in developing and testing ideas for improvement?
I was encouraged by Akio Toyoda's thoughts. He clearly sees the possibility of combining the best of new technology with the creativity of thinking people. In a recent speech he said:
“Two concepts – automation with people and just-in-time – are the pillars of TPS. What both have in common is that people are at the center. I believe that the more automation advances, the more the skill of those who use it will be put to the test. Machines cannot improve unless people improve too. Developing people with skills that can match machines and senses that surpass sensors is a fundamental part of the Toyota approach.”
