An Integrated Approach to Improve Effectiveness of Industrial Multi-factor Statistical Investigations

EasyChair Preprint 3003

Abstract

An approach was developed providing fully objective, mathematically comprehensive, scientifically grounded and physically interpretable description of the manufacturing factor effects on the performance of an industrial product, based on computer statistical analysis of the big, multi-dimensional arrays of industrial technological parameters. The approach integrates a basic Data Mining exploratory technique, multiple regression models construction and Monte-Carlo simulations. The approach was applied to industrial statistical data investigations for the ASTM A514 steel. The results obtained are in a good accordance with the known Material Science data and were confirmed in industry.

Keyphrases: Monte Carlo simulations, exploratory technique, multi-dimensional data, multiple regression models

@booklet{EasyChair:3003,
  author    = {Victoria Miroshnichenko and Alexander Simkin},
  title     = {An Integrated Approach to Improve Effectiveness of Industrial Multi-factor Statistical Investigations},
  howpublished = {EasyChair Preprint 3003},
  year      = {EasyChair, 2020}}