TY - JOUR ID - 7413 TI - Approximating the step change point of the process fraction non conforming using genetic algorithm to optimize the likelihood function JO - Journal of Industrial and Systems Engineering JA - JISE LA - en SN - 1735-8272 AU - Hosseini, Raziyeh AU - Amirzadeh, Vahid AU - Yaghoobi, Mohammad Ali AU - Mirzaie, Hojjat AD - Department of Statistic, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran AD - Department of Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran AD - Department of Computer Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran Y1 - 2014 PY - 2014 VL - 7 IS - 1 SP - 118 EP - 128 KW - Quality Control KW - Statistical process control KW - Change point KW - Genetic algorithm KW - np chart DO - N2 - Control charts are standard statistical process control (SPC) tools for detecting assignable causes. These charts trigger a signal when a process gets out of control but they do not indicate when the process change has begun. Identifying the real time of the change in the process, called the change point, is very important for eliminating the source(s) of the change. Knowing when a process has begun to change simplifies the identification of the special cause and consequently saves time and expenditure. This study uses genetic algorithms (GA) with optimum search features for approximately optimizing the likelihood function of the process fraction nonconforming. Extensive simulation results show that the proposed estimator outperforms the Maximum Likelihood Estimator (MLE) designed for step change regarding to speed and variance. UR - https://www.jise.ir/article_7413.html L1 - https://www.jise.ir/article_7413_419b00d741f39f075bb3a319e041e92f.pdf ER -