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 Atsushi Yamada, Manager within the Glocal Strategy Promotion Department, about his experience working with the IndustrialML platform, the manufacturing industry, and how using a smart factory system can improve the manufacturing processes.
From your perspective, how useful is the IndustrialML platform to your workflow?
Without the dashboard, if something is wrong with a machine or after we’ve adjusted to a device, we go onsite and look, listen, touch, and feel. But with the dashboard, we can check the situation and see real-time data while in the office.
How about the workflow of the machine operators themselves?
For the operator, it is less about numbers and more about physically looking at the condition of the pipes and checking the situation as they make them. That is how it is commonly done. So, with the trends in that data, if they could check on that, they could see the product quality situation, monitor the machine’s condition, and maintain it.
What platform function do you use the most daily?
At Daiwa Steel Tube Industries, it would be the zinc plating furnace. It’s a furnace that melts metal. We monitor the temperature on the dashboard and check the trends. If it’s gradually going down, that means there’s a problem somewhere in the machine, and I ensure that a ticket has been issued to maintenance.
Did you have a say in the development and implementation of the system within the factory?
Something I am involved with in the development is the actual data that is displayed on the platform. This data comes from connecting devices in the factory to the platform, and my central role is ensuring the device’s connection and the platform’s data collection.
How was your workflow within the factory before the platform’s implementation?
Before we had the platform, we would gather data by looking, listening, and touching. We’d go onsite and manually collect data for that moment, for example, every hour or 30 minutes. Now, it’s not just points of data from those moments; it’s data that is constantly being measured. The real-time element is a very big advantage.
Many articles have been written about the aging workforce within the manufacturing industry, how can factories make themselves more attractive to the next generation?
Even within this factory, there are many older people in their 50s and 60s. There are more and more factories like this, not just in Japan but worldwide. And one big issue with this is the transfer of technology. How to pass on this knowledge to younger people? I think that’s a big issue. I think this platform, and things like job tickets, through skillfully using tools like that, the knowledge and experience of the older people can be efficiently transferred to the younger people; so that even with fewer young people, they can still handle it. I think that is important.