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Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
Published on: December 13, 2016
Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production
Jozef Svetlík1, Peter Malega2, Vladimír Rudy2
1Department of Manufacturing Machinery and Robotics, Faculty of Mechanical Engineering, The Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
Abstract:
This paper describes the enhancement of the existing predictive system of quality management in the processes of metallurgic manufacturing. Specifically, it addresses steel-strip manufacturing. The main quality management innovation is the transition from the current methodological process of a single-step defect evaluation to a two-step evaluation. A two-step defect check of the strip's surface involves checking for defects during the hot-rolling process first, and double-checking it during the process of pickling. These defects are detected in a well-established process of camera imaging in the production process. The recorded image is then processed mathematically to find the degree of defect correlation in those processes. The two-step evaluation enables a more detailed focus on a particular defect and its position on the strip. Decisions concerning further processing are based on defect evaluation, for instance, whether a rework is necessary to maximize the product utilization and minimize the eventual negative impact of the defect on production equipment. A crucial aspect is also the reduced probability of failures in the manufacturing process.
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