An integrated approach to improve effectiveness of industrial multi-factor statistical investigations
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CEUR Workshop Proceedings
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An approach was developed for computer statistical analysis of big, multi-dimensional arrays of technology parameters and industrial product qual-ity indexes. It provides fully objective, mathematically comprehensive, scien-tifically grounded and physically interpretable description of the manufacturing factor effects on the performance of an industrial product. The approach inte-grates a basic Data Mining exploratory technique, multiple regression models construction and Monte-Carlo simulations. The approach was applied to indus-trial statistical arrays investigations for the ASTM A514 steel. The results ob-tained are in a good accordance with the known Material Science data and were confirmed in industry
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Miroshnichenko, V., & Simkin, A. (2020). An integrated approach to improve effectiveness of industrial multi-factor statistical investigations. Computer Modeling and Intelligent Systems (CMIS-2020) : proceedings of the Third International Workshop. CEUR Workshop Proceedings, 2608, 526–535.
Miroshnichenko V., Simkin A. An integrated approach to improve effectiveness of industrial multi-factor statistical investigations. Computer Modeling and Intelligent Systems (CMIS-2020) : proceedings of the Third International Workshop. CEUR Workshop Proceedings. 2020. Vol. 2608. P. 526–535.
Miroshnichenko V., Simkin A. An integrated approach to improve effectiveness of industrial multi-factor statistical investigations. Computer Modeling and Intelligent Systems (CMIS-2020) : proceedings of the Third International Workshop. CEUR Workshop Proceedings. 2020. Vol. 2608. P. 526–535.