The present industrial environment needs proper maintenance for effective functioning of the system underlining the need for an optimal maintenance planning. Maintenance planning is a complex and an inherently stochastic process. This paper presents maintenance planning problem for a process industry. The problem is formulated to determine which of the possible actions viz. maintenance or replacement is to be carried out for the subsystems during the planning period. Maintenance is carried out by analyzing improvement in the parameters (viz. MTBF & MTTR) during the planning period. The objective is to minimize the present value of total costs that are incurred by the decision taken during the planning period. The problem is effectively solved by hybrid genetic algorithm (HGA) technique.
Flow shop is a kind of job shop in which jobs have the similar process sequence. Flows shop scheduling problem (FSP) comes under NP (Non polynomial) hard category which means hardness of the problem will increase as much as the number of jobs increases. In FSP there will be a n! possible sequences can be formed if we take n as number of jobs. Everyday flow shop will receive different set of jobs, schedulers have to make decision as quick as possible. A wrong decision in FSP may result in huge loss to the organization. Generally, most of the literatures about the flow shop are single objective but in real life single objective will not be suitable because the real world problems are multi objective in nature. Multi objective flow shop scheduling (MOFSP) is necessary to satisfy wide expectations of different people. In this study MOFSP is going to be handled and a computer based user interface model is going to be developed. A Mixed Integer Linear Programming (MILP) model also going to be formulated as per the required objectives. Comparison of single objective and multi objective problem's results are going to be analyzed and the procedure using Spreadsheet with User Friendly Interface (SUFI) going to be developed and verified.
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