Transforming Tofu Quality Control: Integrating Statistical Process Control, Ishikawa, and Interpretive Structural Modeling for Superior Outcomes

Abstract

In a highly competitive market, maintaining high product quality is essential for maintaining customer satisfaction and loyalty. Producers are famous in East Java and face the challenge of ensuring consistent quality products through strict production processes. Know that as easy products broken and soft, needy control of careful quality to meet hope consumers about freshness, texture, and quality in a way whole. Although traditional control methods often fail to overcome the production complex that causes a disabled product. This research proposes integrating Statistical Process Control (SPC), Ishikawa diagrams, and Interpretive Structural Modeling (ISM) to improve control quality. SPC makes it possible to monitor and control production processes in real-time, identify deviations, and repair deviations. However, the SPC limitations include a focus on quantitative data and post-incident detection problems. To overcome root problems, the Ishikawa diagram categorizes the reasons for potency as material, machine, method, power work, and environment. ISM prioritizes action repair based on impact and relationship. Approach This integrated approach provides comprehensive solutions to improve the quality of knowledge. In this study, the control process quality was evaluated using SPC, the cause of defects was identified using Ishikawa diagrams, and priority action repair was performed via ISM. Findings show that SPC directly effectively monitors process control, the Ishikawa diagram identifies main defects, and ISM prioritizes impactful action improvements, emphasizes excessive additions to subtraction materials, and improves health workers’ and mixing process material standards. Approach integrated possible identification of additional problems and improved the quality strategic makes a significant contribution to enhancing product quality knowledge.