IML Insights – Kazuhiro Yamasaki, Daiwa Steel Tube Industries

A video excerpt of our interview with Kazuhiro Yamasaki, Managing Director of Factory Operations at Daiwa Steel Tube Industries in Tochigi, Japan.

The IML Insights team took a trip to Tochigi, Japan, to Daiwa Steel Tube Industries, a steel tube manufacturing company founded in 1932. We had the opportunity to sit down with Kazuhiro Yamasaki, Managing Director of Factory Operations, and talk about his experience working with the IndustrialML platform, the manufacturing industry, and how using a smart factory system can improve manufacturing processes.

As a director, you see both the field and the office, so please tell us how you utilize a smart factory system and the advantages of doing so.

Mr. Yamasaki: Basically, understanding the current situation. The great advantage is that we can all understand what is happening now. From my standpoint, I don’t look at every single detail, but on the other hand, I want to know what is happening wholly, and I think it is a great advantage to be able to see what is happening in various places in real-time.



If not a smart factory platform, what is the alternative?

Mr. Yamasaki: We still do this from time to time, but I think we have to check with each person individually. We confirm each case separately. On the other hand, if we forget to confirm, that’s the end of it, so this platform is beneficial.



What are some of the operational and challenging initiatives you are undertaking as a managing director? What is the biggest challenge you face at the moment?

Mr. Yamasaki: The challenge for the factory as a whole is to pass on skills. We are old-fashioned people, so it is a challenge to pass on skills from one person to another or to hand down skills because we depend on others.



What do you feel is the effective part of using a smart factory system?

Mr. Yamasaki: There are several things, but I think the most important thing is quantification since it is a system. We are trying to use numerical values to judge various things, and I think it is good that we can quantify what used to be judged simply by the senses or human judgment. When we give instructions to the people who actually do the work, a ticket is issued, and they work based on that ticket. I think it is good that the system works in a structured way.



The IML platform has several functions, can you share an example of how it has actually been useful to you?

Mr. Yamasaki: At this point, we don’t have any solid examples yet, but I think there are many possibilities. If I had to pick, for example, we have the roll order sheet out in the ROC, but the order of the rolls is fixed, and in the past, I would have had to ask people where the work directives were, but now it’s convenient because I can check them anywhere.



I recall that the furnace temperature is a rather recent development.

Mr. Yamasaki: It is very helpful to know the current temperature of the pre-heater and the temperature of the furnace, as these affect the lifetime of the furnace.



What do you think the real-time data display and the audio and video displays are doing to optimize on-site operations compared to what they were before they were implemented?

Mr. Yamasaki: For example, in terms of voice, it has improved communication. All you have to do is speak first. I think this is a great idea. Looking at video feeds, there are two major benefits. One is that if you see the entire manufacturing line, you can see the movement of people. You can see people gathering in departments where problems are likely to occur. The other is to look at it from a micro perspective. It becomes possible to judge whether this product is good or bad. I have great expectations for this kind of technology. When you are actually watching the video in real-time, you can see that “Oh, it has stopped!” I can tell when I see the video in real-time. And from there, the alarms of the system go off. Then you can see what the exact problem is. I can see why the alerts are coming out in rapid succession, saying, “There is an error in this part of the system.” In this case, it says that the amperage of the DS motor is very low. What’s wrong with this? This is related to the galvanizing process. If so, the cause-and-effect relationship becomes clearer little by little. I think it’s good to be able to understand the cause-and-effect relationship by using numerical values.



At the moment, all on-site workers are under your supervision and receive real-time work instructions via alerts. Can you tell us a bit about this?

Mr. Yamasaki: First, I can give instructions to each person based on their position. Not vague instructions, but clear instructions. If you can provide more specific instructions with a numerical value, then, in a sense, you can do something different until that instruction arrives. For example, the entire team can have time to think about various improvements. I think it is very effective to be able to make that time. Until now, we had to stay on-site and keep an eye on the condition of the tube mill. But now that the system is watching over it instead, we can do something different during that time. So, it allows people to make time for what they are supposed to be doing. Whether or not to do so may be a decision to be made at that time, but on the other hand, I think that creating such an environment is a very effective measure for the future.



It is also connected to the passing on of skills that you mentioned earlier.

Mr. Yamasaki: For example, when there is a change in what to produce, some people start preparing five or ten minutes in advance. The time it takes may differ from person to person, but there must be best practices, and if the time is short, it is not good enough. First, clarify the standards to ensure quality with safety as the top priority. This will then be developed horizontally, and everyone can do it. Once that time is clarified, other things can be done until that time. Something like that.



Looking 10 years ahead, can you imagine how the IML platform will be utilized in the future and what it will actually be useful for?

Mr. Yamasaki: It is difficult to say exactly what will happen 10 years from now, but in a simple vision, DSTI will coexist with AI with IML’s help.  Japan’s population is shrinking and the number of people is decreasing, so it is very difficult to do what is physically demanding. So, as much as possible, we should leave to systems or AI what can be entrusted to them, and let human beings do what only human beings can do. The knowledge and wisdom that we have now will be absorbed into the system. This is the way it will be, and I would like to make it that way.



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