학술논문

Statistical Distribution Component Decomposition Method for Manufacturing Quality Control by Using Variational Inference Method
Document Type
Conference
Author
Source
IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society Industrial Electronics Society (IECON), 2020 The 46th Annual Conference of the IEEE. :2629-2635 Oct, 2020
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Manufacturing
Quality control
Gaussian distribution
Temperature measurement
Production
Monitoring
Data models
machine learning
variational inference
statistical distribution
quality control
Language
ISSN
2577-1647
Abstract
This paper proposes a method of decomposing the statistical distribution of manufacturing-condition (e.g., pressure, temperature, and consumable usage time) monitoring data into multiple components using the variational inference method to find the cause of defective products and take measures to control quality. The data come from multiple manufacturing resources (e.g., machines and workers) assumed to be compatible as production capabilities, but some of which are related to the occurrence of defective products. The proposed method determines defective manufacturing resources by calculating their responsibilities for the statistical distribution components with high defective rates. Evaluation results using a dataset modeling actual production lines indicate the effectiveness of the method.