M.S.THESIS PRESENTATION: MPLEMENTING CONDITION-BASED MAINTENANCE: OPTIMIZING MAINTENANCE DECISIONS IN MULTI-COMPONENT SYSTEMS USING MARKOV DECISION PROCESSES

Date/Time
Date(s) - 27/07/2021
11:00 - 13:00

Categories No Categories


 

Speaker:  Mahsa Abbaszadeh Nakhost

 

Topic: Mahsa Abbaszadeh Nakhost

 

Time: Jul 27, 2021 11:00 AM Istanbul

 

Join Zoom Meeting

 

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.