
doi: 10.58286/31370
Cold rolled steel sheets are produced as relatively thin sheets with a thickness of 0.2mm to 2.0mm, and are manufactured through hot-rolled steel pickling, cold rolling, and heat treatment. In addition, cold rolled steel sheets generally have beautiful surfaces, and are widely used as exterior and interior materials for automobiles, home appliances, and building materials. However, cold rolled steel sheets, which are hot-rolled to a thickness of 2mm or less at room temperature, are the most difficult to manufacture among all steel products and require high-level technology. In any case, the final product of cold rolled steel sheets is first produced in sheet form, and since the length of this sheet reaches several kilometres, the ends of the sheets are usually welded together and shipped in coil form. However, due to the tension applied to this coil, the welded part often breaks, causing accidents that stop the production line. The problem at this time is that such production line stoppages act as a factor in increasing production costs, so it is important to monitor such defective conditions in advance and prevent accidents. Our customers are also well aware of these problems and are interested in developing cost-effective methods to solve them. In this paper, we tested whether we can solve this problem in real time by processing artificial defects on the test specimens provided by our customers. The experimental results have yielded some positive results and we are preparing to try to commercialize it by linking it to an actual production line. Through this presentation, we would like to discuss the problems that we could not anticipate and collect opinions related to the development of the system.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
