The Near-Optimal Preventive Maintenance Policies for a Repairable System with a Finite Life Time by Using Simulation Methods

2011 ◽  
Vol 6 (3) ◽  
Author(s):  
Chun-Yuan Cheng
2012 ◽  
Vol 225 ◽  
pp. 534-539
Author(s):  
Aisyah Razana Mahayudin ◽  
Mohamed Tarmizi Ahmad ◽  
Fairuz Izzuddin Romli ◽  
Amzari Zhahir

System maintenance is necessary to prolong the operational life of a system. There are four types of maintenance policies which are corrective, preventive, scheduled and predictive (conditioning based maintenance). However, this paper focuses on preventive maintenance and corrective maintenance policies. In general, the goal of preventive maintenance is to retain the system at its good operating conditions before the occurrence of any failure while corrective maintenance is done as a result of the system’s operating failure. This paper investigates the effects of maintenance activities for Engine Indication and Flight Instruments subsystems of the avionics system of a general aircraft. The simulation of the maintenance process is done using Monte Carlo and Discrete Event simulation methods for different preventive maintenance interval (PMI).


Author(s):  
María Carmen Carnero ◽  
Andrés Gómez

The aim of this chapter is to select the most suitable combination of maintenance policies in the different systems that make up an operating theatre: air conditioning, sterile water, power supply, medicinal gases, and operating theatre lighting. To do so, a multicriteria model will be developed using the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) approach considering multiple decision centres. The model uses functional, safety, and technical-economic criteria, amongst which is availability. Mean availability for repairable systems has been measured to assess this criterion, using Markov chains from the data obtained over three years from the subsystems of a hospital operating theatre. The alternatives considered are corrective maintenance; preventive maintenance together with corrective maintenance by means of daily, weekly, monthly, and yearly programmes; periodical predictive maintenance together with corrective maintenance; and corrective together with preventive and predictive maintenance.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.


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