Quality Issue Classification by Using Dedicated Data Analysis Software Created in Phyton Language

Abstract

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.

Keywords

• Telescopicity
• Hot strip mill
• Coils
• Data analysis
• Algorithms
• Distance lasers sensor

References

1. Choi, Y. J., & Lee, M. C. (2009). A downcoiler simulator for high performance coiling in hot strip mill lines. International Journal of Precision Engineering and Manufacturing,10(2), 53-61.
2. Degner, M., Mentrup, H. C., Messner, K. L., U. Muller, U., & Thiemann, G. (1999). Measuring the end-face profile of hot-rolled coils. Stahl und Eisen, 119(10), 87-89.
3. European Standard EN 10051 .(1991). Continuously hot-rolled uncoated plate, sheet and strip of non-alloy and alloy steels – tolerances on dimensions and shape. https://genorma.com/en/project/show/cen:proj:19766