Quality issues enroll as one of the most important aspects which needs to be avoided in a factory. When a product has quality issues always the economic losses for the company are experienced. The paper approaches manufacturing steel sector and presents the methodology used to classify the quality issues detected to coils in hot strip mill (HSM) factory. The algorithm was developed in python software language and tested on data sets from the plant site. The method used proves the efficacity of the algorithm through the quality issues classification identified on HSM. rnAlso, the HSM represents one of the most important components from a steel factory. Any kind of issues that may occur on HSM production line has direct impact on finished products, which may conduct to big economic losses to the company. In this paper, a method for coils issues classification is described. The dedicated software was created in phyton language and after months of tests was installed to the operators computers for a quick quality issues identification.
Primary Language | English |
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Subjects | Software Quality, Processes and Metrics |
Journal Section | Articles |
Authors | |
Early Pub Date | December 18, 2023 |
Publication Date | November 30, 2023 |
Published in Issue | Year 2023 |