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[Data Science Case] Stabilization of Quality and Variation Factor Analysis by AI
I want to lead to improvements in manufacturing conditions! A case of developing a model to predict variations in inspection results.
We would like to introduce a case study in the manufacturing industry that enabled the stabilization of product quality and analysis of variability factors through AI. In the quality inspection tests for drive system products, there was a challenge to analyze the variability factors of inspection results using the data obtained from the tests, with the aim of improving manufacturing conditions and other aspects. To address this, we developed a model to predict the variability of inspection results using measurement conditions of the quality inspection tests, design information of the manufactured products, and dimensions of components as features. By analyzing the parameters of this model, we interpreted the factors and linked them to improvements in manufacturing conditions. 【Case Overview】 ■Industry: Manufacturing ■Business: Quality Inspection ■Challenges: Factor Analysis, Improvement of Inspection Efficiency, Production Efficiency ■Analytics/AI Solution ・Developed a model to predict the variability of inspection results *For more details, please refer to the PDF document or feel free to contact us.
