A Study on Problem Identification of Production Optimization Based on Extenics and Theory of Constraints

With the rapid development of intelligent manufacturing and complex systems engineering, industrial systems have become increasingly complex, and their problems show multi-level, dynamic, and coupled characteristics. Based on Extenics and the Theory of Constraints (TOC), this paper classifies complex system problems into three layers: real problems, bottleneck problems, and core problems, and proposes a corresponding identification and optimization method. Specifically, a real problem identification method based on implication analysis, a bottleneck problem identification method based on basic-element modeling and correlation functions, and a core problem analysis method based on the Current Reality Tree and implication analysis are developed. A systematic path from system goal identification to constraint localization and key contradiction resolution is then formed. A manufacturing production-line case is used to verify the feasibility and effectiveness of the proposed method. The results show that the integration of Extenics and TOC can support the systematic identification and resolution of complex system problems, and provide useful insights for problem analysis and optimization decision-making in industrial engineering and intelligent manufacturing.