Quality control analysis in tofu production using Lean Six Sigma and Design of Experiments to reduce defects

This research focuses on the quality issues faced by a micro, small, and medium enterprise (MSME) in the food sector, specifically in tofu production. The production process still generates defective products, with a defect rate of 2% to 3% per day. Further observations identified several types of waste in the production process, including overproduction, defects, motion, waiting, transportation, and overprocessing, with defects being the most dominant. To address this issue, this study applies to the Lean Six Sigma method to control product quality. Through analysis using a questionnaire on the seven types of waste, five Critical to Quality (CTQ) factors were identified: dirty defects, splitting defects, hole defects, size defects, and color defects. The study also analyzes the production cycle time, revealing a lead time of 9 hours and 50 minutes, with a total value-added time of 7 hours and 49 minutes. The Defects Per Million Opportunities (DPMO) value is 5,605.31, and the sigma value is 4.0364, indicating that product quality is at an average industry level. An improvement plan was formulated using an experimental design. The proposed improvements were implemented by setting the soybean soaking time to 4 hours, the boiling time to 30 minutes, and the coloring time to 2 hours. After implementation, the percentage of defective tofu products decreased from 2.13% to 0.32%. These results demonstrate that applying the Lean Six Sigma method significantly enhances product quality and production efficiency for the MSME.

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Publication Details

Journal
Journal Industrial Servicess
Published
2025-03-13
DOI
https://doi.org/10.62870/jiss.v10i2.29642
Primary Topic
Quality and Supply Management
Type
article
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article

Quality control analysis in tofu production using Lean Six Sigma and Design of Experiments to reduce defects

Dyah Lintang Trenggonowati, Asep Ridwan, Nuraini Nuraini
Journal Industrial Servicess
Quality and Supply Management
article

Quality control analysis in tofu production using Lean Six Sigma and Design of Experiments to reduce defects

Dyah Lintang Trenggonowati, Asep Ridwan, Nuraini Nuraini
article en

Abstract

This research focuses on the quality issues faced by a micro, small, and medium enterprise (MSME) in the food sector, specifically in tofu production. The production process still generates defective products, with a defect rate of 2% to 3% per day. Further observations identified several types of waste in the production process, including overproduction, defects, motion, waiting, transportation, and overprocessing, with defects being the most dominant. To address this issue, this study applies to the Lean Six Sigma method to control product quality. Through analysis using a questionnaire on the seven types of waste, five Critical to Quality (CTQ) factors were identified: dirty defects, splitting defects, hole defects, size defects, and color defects. The study also analyzes the production cycle time, revealing a lead time of 9 hours and 50 minutes, with a total value-added time of 7 hours and 49 minutes. The Defects Per Million Opportunities (DPMO) value is 5,605.31, and the sigma value is 4.0364, indicating that product quality is at an average industry level. An improvement plan was formulated using an experimental design. The proposed improvements were implemented by setting the soybean soaking time to 4 hours, the boiling time to 30 minutes, and the coloring time to 2 hours. After implementation, the percentage of defective tofu products decreased from 2.13% to 0.32%. These results demonstrate that applying the Lean Six Sigma method significantly enhances product quality and production efficiency for the MSME.

Journal Industrial ServicessVol. 10(2)
Sultan Ageng Tirtayasa University (ID)
Openalex Percentile: Top 67%
Quality and Supply Management
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Quality control analysis in tofu production using Lean Six Sigma and Design of Experiments to reduce defects — Dyah Lintang Trenggonowati, Asep Ridwan, et al. · Journal Industrial Servicess (2025) | TGRS Research Map | TGRS