Speaker: Mahsa Abbaszadeh Nakhost
Topic: Mahsa Abbaszadeh Nakhost
Time: Jul 27, 2021 11:00 AM Istanbul
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https://zoom.us/j/9937664491?pwd=R0FNalFFZUM0Wm9MaitiYWJrbVhodz09
Meeting ID: 993 766 4491
Passcode: 525871
Title: M.S.THESIS PRESENTATION: MPLEMENTING CONDITION-BASED
MAINTENANCE: OPTIMIZING MAINTENANCE
DECISIONS IN MULTI-COMPONENT SYSTEMS USING MARKOV DECISION PROCESSES
Abstract: Maintenance scheduling has been playing a pivotal role in many
industrial areas since unexpected failures result in costly actions to
bring the system back to the operating state. An advanced maintenance
policy is condition-based maintenance (CBM), which schedules the
maintenance actions according to the data collected from the system
inspections. In this study, we present a realistic discretization method
for a maintainable multi-component system that is subject to periodic
in- spection. We consider CBM policy and age-based maintenance policy
for critical components and non-critical components of the system,
respectively. We define a general cost structure including an operating
cost which is a function of system reliability, and we explain how this
operating cost must be assigned in discrete and continuous state space.
We use the Markov decision process (MDP) to find the optimal maintenance
policy for the discrete control problem. Using the MDP model, we prove
that the threshold policy is not always optimal, which is the most
well-known policy in the CBM literature. Finally, we propose two
policies, RL-KIT and RI-MIT, to implement the policy found by MDP in the
continuous environment. We show that either of these policies can be
optimal depending on the system of interest using simulation.
