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Journal of materials processing technology, 290, 116972.

https://www.sciencedirect.com/science/article/pii/S0924013620303939

■ Researchers

Jeongsu Lee

Smart Liquid Processing R&D Department, Korea Institute of Industrial Technology

Young Chul Lee, Jeong Tae Kim

■ Abstract

Although die-casting is one of the most popular mass production processes of precise metal parts, the manufacturing environment of the die-casting factory remains at the traditional level. In this study, we developed three core technologies to realize a smart-factory platform for die-casting industry: 1) a novel cost-effective product-tracking technology to obtain high-quality process data providing individual product information, 2) an advanced process data acquisition system that considers process failure, and 3) a fault detection module based on an artificial neural network. Our newly developed systems for the die-casting process were verified using 1500 test production. Based on the pilot production data, we developed a fault detection module with the pre-processing of time series temperature and pressure measurement data. The developed fault detection module shows 96.9 % accuracy for untrained data. The technologies developed in this study are expected to be a promising smart-factory platform to reduce the defect rate and production cost in die-casting industry.

• Die-castin
• Fault detection
• Smart factory
• Artificial neural network
• Industrial data acquisition

• [신진연구자] 이정수(Jeongsu Lee)(가천대학교 기계스마트산업공학부 조교수)