Authors: J. Carlos García-Díaz; Francisco Aparisi
Addresses: Applied Statistics, Operations Research and Quality Department, Universitat Politècnica de València, Camino de Vera S/n, Building 7A, 46022 Valencia, Spain ' Applied Statistics, Operations Research and Quality Department, Universitat Politècnica de València, Camino de Vera S/n, Building 7A, 46022 Valencia, Spain
Abstract: In some applications of quality control charts it is very important to quickly detect small or moderate shifts in the characteristic that is being monitored when process control starts. In such cases, CUSUM charts with fast initial response (FIR) perform very well. However, optimal performance of a CUSUM-FIR chart is only achieved when the best set of chart's parameters is found. This paper deals with the optimisation of CUSUM-FIR charts to maximise performance for detecting a given process mean shift. The optimisation is carried out using genetic algorithms, and user-friendly software has been developed to promote the use of optimised CUSUM-FIR charts in industry. An extensive set of numerical results is presented to test the effectiveness of CUSUM-FIR optimised chart in detecting small and moderate shifts in the process mean. The results are compared numerically with other similar control charts using the average run length (ARL). An example is presented to illustrate the application of CUSUM-FIR optimised chart. [Received: 8 November 2010; Revised: 7 March 2011; Revised: 28 June 2011 Revised: 12 April 2012; Accepted: 21 May 2012]
Keywords: statistical process control; SPC; cumulative sums; CUSUM; CUSUM-FIR control charts; fast initial response; genetic algorithms; parameter optimisation; process monitoring; process mean; quality control.
European Journal of Industrial Engineering, 2014 Vol.8 No.1, pp.69 - 89
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 18 Feb 2014 *