TY - GEN
T1 - A Numerical Study on the Structure of Optimal Preventive Maintenance Policies in Prototype Tandem Queues
AU - Kim, Taehyung
AU - Morrison, James R.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - While high levels of automation in modern manufacturing systems increase the reliability of production, tool failure and preventive maintenance (PM) events remain a significant source of production variability. It is well known for production systems, such as the M/G/1 queue, that optimal PM policies possess a threshold structure. Much less is known for networks of queues. Here we consider the prototypical tandem queue consisting of two exponential servers in series subject to health deterioration leading to failure and repair. We model the PM decision problem as a Markov decision process (MDP) with a discounted infinite- horizon cost. We conduct numerical studies to assess the structure of optimal policies. Simulation is used to assess the value of the optimal PM policy relative to the use of a PM policy derived by considering each queue in isolation. Our simulation studies demonstrate that the mean cycle time and discounted operating costs are 10% superior.
AB - While high levels of automation in modern manufacturing systems increase the reliability of production, tool failure and preventive maintenance (PM) events remain a significant source of production variability. It is well known for production systems, such as the M/G/1 queue, that optimal PM policies possess a threshold structure. Much less is known for networks of queues. Here we consider the prototypical tandem queue consisting of two exponential servers in series subject to health deterioration leading to failure and repair. We model the PM decision problem as a Markov decision process (MDP) with a discounted infinite- horizon cost. We conduct numerical studies to assess the structure of optimal policies. Simulation is used to assess the value of the optimal PM policy relative to the use of a PM policy derived by considering each queue in isolation. Our simulation studies demonstrate that the mean cycle time and discounted operating costs are 10% superior.
UR - http://www.scopus.com/inward/record.url?scp=85081139429&partnerID=8YFLogxK
U2 - 10.1109/WSC40007.2019.9004706
DO - 10.1109/WSC40007.2019.9004706
M3 - Conference contribution
AN - SCOPUS:85081139429
T3 - Proceedings - Winter Simulation Conference
SP - 2281
EP - 2291
BT - 2019 Winter Simulation Conference, WSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Winter Simulation Conference, WSC 2019
Y2 - 8 December 2019 through 11 December 2019
ER -