Process improvement in the patternshop production unit: Analysis of error prevention strategies using Poka Yoke and Polca techniques

Purpose: In the highly competitive textile industry, errors occurring in the model shop department, which represents the starting point of production and a key determinant of quality, lead to material waste, increased costs, and delays in delivery times. In this study, the integration of Poka Yoke techniques, which provide a proactive approach aimed at preventing errors before they occur, and the POLCA system, which balances bottlenecks within the production flow, was examined. The aim of the study is to evaluate the optimization of processes in the model shop department, the minimization of error rates, and the reduction of operational excellence and quality-related costs. Materials and Methods: The research is based on a field study conducted in the model shop department of a textile factory operating in the Malatya Organized Industrial Zone. POLCA, a material control system designed for high-mix and low-volume production environments, was utilized to ensure a balanced process flow. In order to physically and visually prevent human-related errors at their source, Poka Yoke techniques, one of the lean manufacturing tools, were integrated into the system and implemented. Findings: It was observed that errors are unavoidable even in production systems equipped with advanced technological infrastructure. However, through the integration of Poka Yoke and POLCA techniques, it was determined that the process flow within the model shop department became more balanced and production errors were minimized. It was also identified that the time and costs spent on corrective actions after errors were operationally optimized through this proactive approach. Conclusion: Our field data indicate that the combined implementation of Poka Yoke and POLCA systems is more effective than standalone applications or traditional methods in eliminating bottlenecks in textile model shop processes, preventing material waste, and maintaining delivery schedules. This integration offers a strategic solution for reducing quality-related costs by minimizing error rates.