Operator-integrated cluster analysis for production quality control

Abstract

The paper introduces the Quality Clusters for Operators (QC4O) approach, aimed at improving quality control strategies in modern manufacturing. It identifies a dual challenge: The lack of communication between data analysts and operators, along with the insufficient integration of their respective methodologies, hindering the acceptance of novel control strategies. To address these challenges, the paper proposes integrating modern machine learning-based methods with methods used by operators, enhancing usability and acceptance. This integration aims to facilitate better communication and expedite quality decision-making. The approach is demonstrated through its application in hairpin stator production, representing complex manufacturing systems.