Reviving How To Make Things

Almost three years ago I wrote “Don’t Lose How To Make Things.”

In that post, I wanted to emphasize the risks of losing your expertise in the technology and skill required to make your product. Too many companies today seem to be bent on replacing those skills with financial ones.

Today I came across a fascinating article on Bloomberg’s site about how Toyota has come to the same conclusion.

You can read it here: ‘Gods’ Make Comeback at Toyota as Humans Steal Jobs From Robots.

In short, they have established workshops where workers manually produce parts that are normally made by automated processes.

A worker welds an automobile part in the chassis manufacturing department at a Toyota Motor Corp. plant in Toyota City.

The idea is to maintain understanding of how things are made so they do not lose the skill required to improve their production processes.

“Fully automated machines don’t evolve on their own,” said Takahiro Fujimoto, a professor at the University of Tokyo’s Manufacturing Management Research Center. “Mechanization itself doesn’t harm, but sticking to a specific mechanization may lead to omission of kaizen and improvement.”

One result?

In an area Kawai directly supervises at the forging division of Toyota’s Honsha plant, workers twist, turn and hammer metal into crankshafts instead of using the typically automated process. Experiences there have led to innovations in reducing levels of scrap and shortening the production line 96 percent from its length three years ago.

Toyota has eliminated about 10 percent of material-related waste from building crankshafts at Honsha. Kawai said the aim is to apply those savings to the next-generation Prius hybrid.

Today’s financially driven managers are unlikely to allow the space to experiment and learn. Instead, they want a deterministic process so next quarter’s results can be forecast accurately. It isn’t good to surprise the analysts.

At the same time, though, companies are pressing for things like “innovation.” That doesn’t happen in a breakthrough. It happens through the rigorous application of the skill of expanding knowledge. Once enough knowledge is accumulated, expertise develops and innovation follows.

Years ago, when I was working for a company making heavy equipment, one of our Japanese consultants (who had worked many years directly for Taiichi Ohno) urged our engineers to hand-form sheet metal parts – with hammers(!). We didn’t do it. But now I understand what he was trying to get us to do.

6 Replies to “Reviving How To Make Things”

  1. “Fully automated machines don’t evolve on their own…”

    Great line! They don’t grow which means they don’t learn from their mistakes, they don’t give suggestions for improvement, they don’t grow in confidence to challange the status quo, they don’t provide ideas that may increase revenue, they don’t inspire, lead, or help other machines to grow and get better, and so on.

    While we don’t make anything in my world of material handling and warehousing, I see this fascination with automation (like AGVs) all the time. Does it have its place? Yes. Should it be the first go-to solution? No.

    Speaking of automating the movement of materials/goods, I recently toured TMMK and I was surprised to see so many AGCs (automatic guided carts) moving subassemblies around.

    1. Jason –
      Yup.
      “Lean” people have created a reputation for being against automation.
      In reality, I think, “we” are against automating inefficiency as an excuse for not addressing it.
      In my work with a number of different areas in a single client, a common complaint is how much harder the work has become with the introduction of all of the new I.T. “tools.”

  2. I can’t tell you how many times I’ve seen poor performing and problematic automated equipment implemented by people who either didn’t know or didn’t even care to know the intricacies of the process they were automating.

    It’s all too common to simply throw a complicated, expensive bit of machinery (and/or software) at a problem rather than trying to understand it. Automation only works well when you use it to execute your best thinking not circumvent it.

    As they say, if you automate a wasteful process all you get is more waste, faster.

  3. I often wonder what is worse, taking automated steps at solving a problem with no understanding of the problem or taking no steps waiting for automation. Either way the opportunity to learn and understand goes by each day.

    Automation is great for completing the repetitive process when that process is not an impediment to reaching the next level of improvement. But if you want to improve people are going to have to know and understand the purpose of the automation in context of the surrounding process.

  4. One of the paradigms that has ushered in the problem of lost knowledge is that engineers have become project managers and not process managers. Keeping authority to improve and change with the innovators of the technology or automation in your organization is a way to keep things evolving. That requires a different approach to leadership.

  5. As a student that is going to graduate from the University of Rhode Island in the spring, I have learned a lot about automation and the fear that many people have that jobs become obsolete as robots fill their shoes. This article fascinated me because a consistent narrative that you hear is that AI and machines will replace humans completely. This article shows more that this does not have to be the case. Humans and machines can work together to achieve a level of production and knowledge that was not possible before. It was also interesting to see that in some cases, human labor can be more beneficial to a company. When you have a lean system in place, or if that is one your company is considering, it is crucial that humans have a working knowledge of all processes and how things work. Without it, continuous improvement and the identification of problems can be masked or hidden behind machinery. Sometimes, as people, I feel like we have a tendency to believe that machines are perfect and that once they are implemented, the only thing we have to watch is if it is running properly. I think that it is important to realize that machines are programmed to do what we tell them to do. So, even with machines, you have to continue to look at a process for ways to improve.

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