Abstract
Objective: In manufacturing setup, limited budget is allocated for each system. In order to increase reliability of the system, redundancy is allocated within given cost constraints. Objective of this paper is to come out with the best optimal solution and increase their liability of a system under cost constraint in a manufacturing plant. Methods: In this paper Heuristic Algorithm (HA) and Constrained Optimization Genetic Algorithm (COGA) are used to optimize constrained Redundancy Allocation Problem (RAP) in a manufacturing plant. These methods are used to allocate the best redundancy strategy for each subsystem with a view to increase the reliability of the system under cost constraints. Best optimal solution is reached by comparing results of CPU time taken by these two methods. Findings: Generally RAP is a NP hard problem and a non-linear integer programming problem, which is difficult to solve. Both methods are applied and comparison between reliability of both the methods is made on the basis of which result obtained by COGA is 0.8632 which is found better against HA which is 0.8380. Application: Results applied in the manufacturing plant which resulted in the increase of reliability by using best redundancy strategy.
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