IML Insights – Yumi Nakayama, Daiwa Steel Tube Industries

The IML Insights team took a trip to Tochigi, Japan, to Daiwa Steel Tube Industries, a steel tube manufacturing company founded in 1932. We spoke to Yumi Nakayama of the Glocal Strategy Promotion Department about her experience working with the IndustrialML platform, how to deploy a smart factory solution and the future of the manufacturing industry.

Can you tell us a little about your role within the factory?

In my day-to-day, I liaise with operators and management to identify issues and requests and communicate them to higher-ups, and if it’s something small that I can handle, I do what I can to respond. 

Has using the IML platform improved your workflow?

In my case, I am a desk worker, so I exclusively use the dashboard. Before, I had to go downstairs to the factory floor to see for myself if something was running. So, efficiency is a great benefit. It’s very convenient.

How are new systems and features implemented within the factory? 

We consider affinity and operability, and things like costs, to implement it in a way that best fits the site, so tests are conducted with the field operators to determine the most suitable system.

We have to do that because the people on site are busy, so we have to set certain standards for what they test. We make sure it fits their requests and is suitable for the environment. We also check security and whether it’s easy to use on both the user side and the management side. We look at it from those perspectives and consider whether it will reduce labor costs, save work time, and if it’s cost-effective. Things like that. 

How is it working with the IML team to implement features within the system? 

Everyone at IML is very friendly, so it’s easy for the people on our side to communicate our ideas, and we see how they implement those things, so as someone on the user side, it’s easy to communicate. We feel that they are eager to understand what we are thinking. That helps to build a better environment to use the system. Thanks to that, for the first time, the system has become a part of my every day workflow, I have come to think of it in this way.

How can a factory improve efficiency with a system like IML?

With the factory, it depends on how many sensors are installed, but you can see a list of all the figures that are measured by the sensors, and you can make alerts based on these figures. It helps get an overall sense of what’s happening.

When the system triggers alerts based on a numeric value, you can use this to ensure operation consistency, which reduces the cost of new operators. Because of these alerts, we can respond to problems and spot defective products before they occur. We can reduce the response time, the waste of material, and the number of people responding to the problem. It increases efficiency in many aspects.

What do you think of concerns that artificial intelligence and smart factory systems will completely replace human workers in the future? 

The areas in which people excel and the areas in which systems excel are different, so we can cover each other’s weaknesses and complement each other. I think that’s what will be needed in the future. When humans do a task, there are always things they forget. They can become less conscious of certain things. This sort of thing happens, so this is where AI and smart factory systems can help. It’s not a matter of suddenly replacing everything. It’s not about switching from human hands to machines but about switching what you can do a little at a time. The worker or operator handles things only people can do. I think that’s how things will change.

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