Using Regression Analysis for Automated Material Selection in Smart Manufacturing

In intelligent manufacturing, the phase content and physical mechanical properties of construction materials can vary due to different suppliers blanks manufacturers. Therefore, evaluating composition for implementing a decision-making approach in material selection using up-to-date software is topical problem smart manufacturing. article aims develop comprehensive automated approach. The proposed method based on use normalization probability approaches linear regression procedure formulated matrix form. As result study, analytical dependencies were developed. Based hypotheses about impact properties, was proven qualitatively quantitively carbon steels from AISI 1010 1060. achieved results allowed an arbitrary particular group by its properties. Overall, criteria helpful engineering, industrial engineering purposes.