Quality Management Improvement in Wiring Harness Production through the Six Sigma DMAIC Approach: A Case Study at PT. XYZ

Authors

  • Gabrielle Rebecca Christisa Politeknik Negeri Batam Author
  • Fandy Bestario Harlan Politeknik Negeri Batam Author

Keywords:

DMAIC, p-chart, Six Sigma, continuous improvement, quality management, wiring harness

Abstract

Intense competition in the automotive component industry requires manufacturers to manage product quality systematically in order to sustain customer satisfaction and control operational costs. PT. XYZ, an automotive wiring harness manufacturer in Indonesia, experienced a decline in quality performance, as its defect rate rose from 0.61% in 2022 to 0.95% in 2023. This study aims to assess the current quality condition of wiring harness production, identify the root causes of the dominant defects, and formulate managerial improvement and control actions using the Six Sigma approach. A descriptive qualitative case study design was applied, with data collected through interviews, direct observation, daily production reports, and company documentation. The data were analyzed following the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle, supported by a Pareto chart, a proportion control chart (p-chart), fishbone diagrams based on the man, machine, method, and material (4M) factors, and the 5W+1H technique. The results show that connector broken and terminal tip arrangement defects were the two dominant defect types, accounting for 28.9% of all recorded defects, and that the average defect proportion between August and October 2023 was 7.6%. The root causes were insufficient operator understanding and self-checking, unprotected assembly stands and damaged aprons, rushed handling methods, and fragile materials. Improvement actions, namely operator retraining, protective pads on the assembly board, revised work standards, and a maximum material stock level of 80%, reduced the defect percentage by 2.90%. These findings indicate that DMAIC can serve as a managerial tool for quality decision-making in labor-intensive assembly operations.

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Published

2026-10-31