TY - JOUR ID - 66285 TI - Step Change Point Estimation in g and h Control Charts in Healthcare JO - Advances in Industrial Engineering JA - AIE LA - en SN - AU - Amiri, Amir Hossein AU - Sogandi, Fatemeh AU - Rafiei Tabatabaei, Azadeh AD - Department of Industrial Engineering, Shahed University, Tehran, Iran Y1 - 2018 PY - 2018 VL - 52 IS - 1 SP - 1 EP - 12 KW - Healthcare KW - g and h Control Charts KW - Maximum Likelihood Estimator KW - Statistical Process Control KW - Step Change Point Estimation DO - 10.22059/jieng.2018.134403.1008 N2 - Estimating the real time of a change point in process is one of the main purposes in the statistical process control. On the other hand, it is important to estimate the change point in healthcare processes regarding the relation between quality engineering and hospital epidemiology. Hence, in this paper, maximum likelihood estimators are proposed in g and h control charts for healthcare systems. We applied Monte Carlo simulation to assess the proposed approaches in terms of accuracy and precision. In addition, there are provided the corresponding cardinality sets and coverage probabilities based on logarithm of the likelihood function. Results indicate that the proposed estimators have a satisfactory performance under different shifts. UR - https://aie.ut.ac.ir/article_66285.html L1 - https://aie.ut.ac.ir/article_66285_4da3a596b70f3e08f0fe27db900c056f.pdf ER -