Developing Quality Control Charts for the Control Points of a Food Product
Monitoring the production process is a critical issue for improving the quality of product and for reducing the costs regarding external failures. Quality control charts are often used to visualize measurements on the process during the monitoring activities. This paper presents a case study based on the use of advanced charts, Cumulative Summation (CUSUM) and Estimated Weighted Moving Average (EWMA) charts, for visualizing the control points of a particular chicken product in fast-food industry. Furthermore, GM (1,1) and GM (1,1) Markov models were built to generate predictions to see the trends and future values to maintain a follow-up procedure for the fluctuations in the process performance. In this context, three control points are considered that are weight of the chicken wings, sterilizer temperature, and grid-pan temperature. The findings provide a significant feedback for the efficiency of the corresponding processes. Results show that the methodology selected to develop these charts has an important impact on creating an effective quality control process.
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