Pro Manual! Variability Management in Processes and Excel Statistical Analysis Methods
I will provide a detailed explanation of the procedures for statistical analysis (t-tests, correlation analysis, regression analysis, experimental design) using MC processing data.
<Training and Seminar Planning for Young Engineers> Explanation of Practical Statistical Analysis Methods for Use in the Field Statistical Quality Control (SQC) should not be seen merely as a subject of study for statistical experts; it must be manageable enough for those conducting analyses in the manufacturing field to effectively utilize even simple methods (such as QC tools). For example, the Seven QC Tools are techniques for analyzing phenomena numerically and quantitatively, allowing anyone to quickly understand issues through visualization and making explanations easy. However, it can be quite challenging to master advanced technical problems involving hypothesis testing and estimation, correlation analysis, regression analysis, experimental design, multivariate analysis, and the Taguchi method (quality engineering). Recently, it has become possible to conduct analyses without complex calculations by using the statistical analysis functions in EXCEL. This explanatory document will provide a detailed guide on managing variability in manufacturing processes and quality improvement methods using statistical analysis techniques, specifically focusing on practical procedures for conducting statistical analyses (t-tests, correlation analysis, regression analysis, experimental design) using MC processing data.
- Company：高崎ものづくり技術研究所 ゴウドウガイシャタカサキモノヅクリギジュツケンキュウショ
- Price：Other
