TY - JOUR ID - 21505 TI - Applying a change-point control chart based on likelihood ratio to supply chain network monitoring JO - Scientia Iranica JA - SCI LA - en SN - 1026-3098 AU - Zhong, J. AU - Hu, X. AU - Yang, Y. AU - Tu, Y. AD - College of Management & College of Tourism, Fujian Agriculture and Forestry University, Fuzhou, 350002, China. AD - School of Management, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China AD - Department of Management Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China. AD - Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, T2N 1N4, Canada. Y1 - 2020 PY - 2020 VL - 27 IS - 5 SP - 2529 EP - 2538 KW - supply chain network system KW - a serial-parallel multistage process KW - order completion time KW - state-space modeling KW - a change-point chart based on likelihood ratio DO - 10.24200/sci.2019.5626.1380 N2 - In this paper, a supply chain network system is viewed as a serial-parallel multistage process; and the application of a change point control chart based on likelihood ratio is explored to monitor this system. Firstly, state-space modeling is used to characterize complexity of the supply chain network system. Then, a change point control chart based on likelihood ratio is built to trigger potential tardy orders in the system. A case study is illustrated to indicate that the change point control charts can effectively signal process mean shift, and accurately estimate the change point and the out-of-control stage in term of power of detection and the accuracy of estimation of change point. We also investigate the effect of misspecified parameters of state space equations on the performance of the change point control chart. The results show that the performance of the change point control chart is relatively stable. UR - https://scientiairanica.sharif.edu/article_21505.html L1 - https://scientiairanica.sharif.edu/article_21505_befe94657dec0f42bcaf6dc88ff1b82d.pdf ER -