Abstract
The injection molding industry is a key field in the manufacturing industry which is projected to expand and improve national competitiveness. However, the domestic injection molding industry is currently experiencing several difficulties, including the aging of skilled engineers and lack of investment in new technology. To address these challenges, this study aims to establish ways to reduce the time and cost required for quality inspection by quickly identifying defects in the injection molding process through defect-prediction and defect-cause analysis using an artificial intelligence algorithm. In addition, by identifying the relationship between major explanatory variables and explanatory variables for defects, we intend to establish a quantitative analysis through fundamental cause analysis of defects to implement a smart factory with an advanced response.
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