Integrated Lean Six Sigma and Statistical Quality Control to Enhance Production Quality in the Beverage Manufacturing
DOI:
https://doi.org/10.59188/eduvest.v6i2.52481Keywords:
Lean Six Sigma, Statistical Quality Control, Beverages Industry, Process Capability, DMAICAbstract
Continuous quality improvement is fundamental to maintaining competitiveness in the beverage processing industry, particularly in developing countries where process variability often leads to operational inefficiencies. This study aims to examine the implementation of Lean Six Sigma (LSS) integrated with Statistical Quality Control (SQC) as a comprehensive strategy to enhance production quality in a selected Indonesian beverage company. The research was conducted using purposive sampling and followed the DMAIC (Define, Measure, Analyze, Improve, and Control) framework to identify, measure, and mitigate causes of volume variation in bottled products and improve process yield. Quantitative analysis was performed on production records using control charts, process capability indices (), and defect probability calculations. The results showed that prior to improvement, the process capability index () was 0.722 for 350 mL bottles and 0.636 for 450 mL bottles, with a rejection rate of approximately 3.00%, indicating poor process control. After a series of corrective actions, including mold and filler vacuum adjustments, the increased to 1.430 for 350 mL bottles and 1.338 for 450 mL bottles, while the rejection rate declined significantly to 0.562% and 0.438%, respectively. The findings demonstrate that the integration of LSS and SQC substantially improves process capability, reduces production waste, and enhances product quality. This study provides novel empirical evidence on the application of Lean Six Sigma in the beverage industry context and contributes both theoretical and practical insights into the use of data-driven quality approaches to achieve sustainable manufacturing excellence.
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