Optimization of Control Charts with Multi-Stage Sampling Using Genetic Algorithm
Volume 8, Issue 3, Autumn 2018, Pages 214-223
Zeynab Latifi, Asieh Salesi
Abstract Different types of process control methods exist for jointly monitoring of several quality characteristic. Recent studies have shown that multi-stage sampling control charts perform better in detecting shifts in process. Therefore, because of the efficiency of the joint mean and standard deviation charts with multi-stage sampling in detecting shifts in mean and standard deviation of the process, discussion and consideration of these charts is necessary. In this paper, the joint Double Sampling and Triple Sampling mean and standard deviation charts are introduced. The joint Statistical Design of these charts is formulated as an optimization problem and solved using a genetic algorithm.
Design of mean control and standard deviation diagrams by multiple sampling
Volume 7, Issue 1, Spring 2017, Pages 60-68
zaynab Latifi, Asieh Salesi
Abstract In statistical quality control, the concentration and dispersion of continuous quality characteristics in a process are usually examined simultaneously with the help of two graphs. In this way, the changes in each will be identifiable simultaneously. Due to the high efficiency of control graphs of mean and standard deviation with double sampling in rapid identification of mean changes and standard deviation of the process, discussion of this category of graphs seems necessary. In this paper, based on the results of designing mean control and standard deviation diagrams with double sampling, mean and control standard deviation diagrams with triple sampling are introduced. Statistical design of mean control and standard deviation diagrams with triple sampling is formulated as an optimization problem and to solve this problem, genetic algorithm is proposed.