Eliminating contamination issues in manufacturing of nutritional products using six sigma approach
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Date
2018-01
Open Access Location
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River Publishers
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This is an Open Access journal [...] All Open Access articles are published and distributed under the Creative Commons Attribution-Non Commercial 4.0 International (CC BY-NC 4.0).
Abstract
The industry of nutritional products and premixes does not forgive poor quality. It is crucial manufacturers get product right the first time. However, the quality in this industry is always under threat of contamination issues with out-of-specifications and foreign matter impurity being always on the radar of quality control. Six Sigma approach is renowned for improving quality through eliminating variation. It focuses on critical processes that affect the quality for internal and external customer. This paper aims to describe the journey of improving the quality management through development and application of Six Sigma framework using carefully selected tools, specifically tailored for medium-sized food manufacturing business in Auckland, New Zealand. This facility is experiencing contamination issues in their products due to nonconformance with the standard specifications on ingredient quantity or presence of foreign matter within the end product. Defective products have caused a spike in late deliveries and rejections, spoiling the long-earned reputation amongst loyal customers. A framework is developed that embodies Six Sigma methods Define, Measure, Analyze, Control and Improve for food manufacturing business. Using this framework, the study achieves the optimization in loading, mixing and blending processes as well as product packaging. The results describe the improvement in meeting manufacturing standards, on-time deliveries and reduction of rework and waste. This research provides direction to other small- medium-sized food manufacturing companies in enhancing quality management through eliminating variation in the production processes by effectively adopting the Six Sigma framework.
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Journal of Industrial Engineering and Management Science, 2018, 2017 (1), pp. 225 - 240