Estimation and Optimization for System Availability Under Preventive Maintenance

doi:10.1109/ACCESS.2022.3204394

Estimation and Optimization for System Availability Under Preventive Maintenance

2022-01-01

12

OA

AI

Umar Muhammad Modibbo

A

Abdullah Ali H. Ahmadini

I

Irfan Ali *

DOI：10.1109/ACCESS.2022.3204394

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摘要

En 中文

Engineers design systems to be reliable and work to fulfil their missions without failure for a specific period. However, the system components deteriorate with time and lead to its failures. A frequent system failure increases the management costs, hence posing a challenge to decision-makers. Therefore, for the avoidance of frequent system failures, preventive maintenance is necessary. The objective of any manufacturing firm is to maximize profit and minimize costs. The interval for preventive maintenance can be optimized if the system's availability is maximized and its cost function minimized. This study evaluates the availability and cost function for a continuous operating series-parallel system under a fixed time environment. A multiobjective model is formulated to maximize the availability and minimize the cost function of the system. The study illustrated a numerical example and solved using goal programming (GP), fuzzy goal programming (FGP), genetic algorithm (GA), and particle swarm optimization (PSO) techniques. The results are compared using a robust statistical test and, the PSO proves to be better. A simulation study was carried out further to evaluate the availability and cost function using R and MATLAB packages.

Keyword:

Maintenance engineering

Reliability

Optimization

Particle swarm optimization

Cost function

Preventive maintenance

Markov processes

Availability constraints

cost function

exponential distribution

series-parallel system

particle swarm optimization

preventive maintenance policy

Estimation and Optimization for System Availability Under Preventive Maintenance

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