Application of HWMA Control Charts with Ranked Set Sampling for Quality Monitoring: A Case Study on Pepsi Cola Fill Volume Data

Abstract

This case study explores the implementation of the Homogeneously weighted moving average (HWMA) control chart, which is improved by the ranked set sampling (RSS and MRSS) to track the quality of the processes within a real industrial environment. Based on Pepsi Cola fill volume data generation, we show how sample rank set sampling is more effective at detecting process mean changes than the classical HWMA chart under simple random sampling. The comparison demonstrates that the proposed schemes make the out-of-control conditions known more in advance providing a more sensitive and reliable method of quality monitoring. The findings support the practical importance of using HWMA charts in conjunction with ranked set sampling methods, especially in those industries in which measurements are expensive but ranking is cheap and easy. The case study highlights the possibility of enhanced operational performance and early identification of failure in the production of beverages with improved statistical process control practices.