Analysis of Bread Production Quality at SMEs Industry using Statistical Process Control (SPC)

Authors

  • Tessa Zulenia Fitri Universitas Bengkulu
  • Rama Dani Eka Putra Universitas Bengkulu
  • Nia Arfina Foci Department of Mechanical Engineering, Faculty of Engineering, Universitas Bengkulu, Indonesia
  • Muhamad Yasin Departement of Mechanical Engineering, Universitas Bengkulu, Indonesia
  • Muhammad Arif Munanda Departement of Mechanical Engineering, Universitas Bengkulu, Indonesia

DOI:

https://doi.org/10.31004/jestm.v5i2.281

Keywords:

MSMEs, Bread Quality, SPC, Control Chart, Pareto Diagram

Abstract

XYZ Industry is a micro-enterprise engaged in bread production. However, defects such as burnt bread, irregular shapes, and inconsistent weights are still frequently found during production, which affects customer satisfaction and production efficiency. This study aims to analyze and optimize bread production quality using the Statistical Process Control (SPC) approach. The methodology includes data collection over 20 production days, analysis using Pareto diagrams, p control charts,  and R charts, and cause and effect diagrams. The findings indicate an average defect rate of 4.79%, with burnt bread being the most prevalent defect (30%). The p control chart identified several days with assignable variation, while the  and R charts revealed that the bread weight process was statistically in control. The main causes of defects were related to human factors, machine limitations, and the absence of standardized procedures. Recommendations include establishing standard operating procedures (SOPs), conducting operator training, and procuring supporting tools. The consistent application of SPC is expected to enhance both the quality and efficiency of production

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Published

2025-09-01

How to Cite

Tessa Zulenia Fitri, Rama Dani Eka Putra, Foci, N. A., Yasin, M., & Munanda, M. A. (2025). Analysis of Bread Production Quality at SMEs Industry using Statistical Process Control (SPC). Journal of Engineering Science and Technology Management (JES-TM), 5(2), 180–188. https://doi.org/10.31004/jestm.v5i2.281