製程參數回饋與成型品質監測技術 2023/07/13

簡介 Introductions

• 本技術結合製程參數與AI深度學習，解決傳統產業的品質分析大多仰賴現場人力檢測與巡檢，導致無法提供穩定生產造成大量不良品生產之問題。透過蒐集產品從設計、製造與品管等製程的大數據，分析後得到有意義的分群視覺呈現，可用於回饋現有製程之問題或預測將發生的狀況。
• This technology combines process parameters and AI deep learning to solve the problem of relying on manual inspection of quality analysis in traditional industries, which results in unstable production and a large amount of defective products. By collecting big data on product design, manufacturing, and quality control processes, meaningful clustering and visual presentation can be obtained through analysis. This can be used to provide feedback on existing process problems or to predict potential incidents.

特色與創新 Characters and Innovations

• 透過AI的製程參數地圖分析，不須經由人工檢測或者機器視覺等方式就可判別產品之好壞。
• 製程參數地圖結合異常檢測技術、降維技術、機器學習方法、結合現場專家知識，可提供直觀的肇因分析與即時警示工具，避免不良品持續生產所造成的浪費。
• Through AI process parameter mapping analysis, product quality can be determined without the need for manual inspection or machine vision.
• The process parameter map combines on-site expert knowledge, anomaly detection techniques, dimension reduction techniques, and machine learning methods to provide intuitive root cause analysis and real-time alert tools, avoiding waste caused by the continuous production of defective products.

應用與效益 Applications and Benefits

• 可廣泛應用於能取得產品設計、製造與品管等製程參數的產業如射出成型、汽機車零組件、3C/3K等製造業。
• This can be widely applied to industries that can obtain process parameters in product design, manufacturing, and quality control, such as injection molding, automotive and motorcycle components and 3C/3K manufacturing.

聯絡 contact

• 李韋辰  Wei-Chen Li
• TEL: 886-3-5916670
• FAX: 886-3-5915939
• E-mail: Jeecool@itri.org.tw

製程參數回饋技術 Process Parameter Feedback Technology 

成型品質監測技術 Molding Quality Monitoring Technology

製程參數回饋與成型品質監測技術人機介面 

Process Parameter Feedback and Molding Quality Monitoring Technology HMI