An improved Hotelling's T 2 chart for monitoring a finite horizon process based on run rules schemes: A Markov‐chain approach

Author(s):  
XinYing Chew ◽  
Michael Boon Chong Khoo ◽  
Khai Wah Khaw ◽  
Ming Ha Lee



1986 ◽  
Vol 18 (1) ◽  
pp. 123-132 ◽  
Author(s):  
I Weksler ◽  
D Freeman ◽  
G Alperovich


2010 ◽  
Vol 106 (3) ◽  
pp. 303-309 ◽  
Author(s):  
Chao Liang ◽  
Guang Cheng ◽  
Devin L. Wixon ◽  
Teri C. Balser


2018 ◽  
Vol 15 (2) ◽  
pp. 247-266 ◽  
Author(s):  
Guglielmo D’Amico ◽  
Ada Lika ◽  
Filippo Petroni


2017 ◽  
Vol 1 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Mahmut REİS ◽  
Hurem DUTAL ◽  
Zeynep KAYRAK


2008 ◽  
Vol 01 (01) ◽  
pp. 15-21 ◽  
Author(s):  
Shu-Qin Zhang ◽  
Ling-Yun Wu ◽  
Wai-Ki Ching ◽  
Yue Jiao ◽  
Raymond, H. Chan


Author(s):  
Khalid Alnowibet ◽  
Lotfi Tadj

The service system considered in this chapter is characterized by an unreliable server. Random breakdowns occur on the server and the repair may not be immediate. The authors assume the possibility that the server may take a vacation at the end of a given service completion. The server resumes operation according to T-policy to check if enough customers have arrived while he was away. The actual service of any arrival takes place in two consecutive phases. Both service phases are independent of each other. A Markov chain approach is used to obtain the steady state system size probabilities and different performance measures. The optimal value of the threshold level is obtained analytically.



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