Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production

Preventive maintenance (PM) is a maintenance program with activities created at a determined interval or according to certain principles, designed to reduce the likelihood of failure or deterioration of item performance. This aims to improve overall reliability and system availability. In this resea...

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Vydané v:Sustainability Ročník 15; číslo 1; s. 239
Hlavní autori: Alhamad, Khaled, Alkhezi, Yousuf, Alhajri, M. F.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.01.2023
Predmet:
Aquatic resources
Cogeneration power plants
Comparative analysis
Desalination
Electricity
Energy
Energy development
Energy industry
Genetic algorithms
Heuristic
Integer programming
Kuwait
Linear programming
Maintenance and repair
Maintenance costs
Manufacturing
Optimization
Power plants
Preventive maintenance
Saline water conversion
Scheduling
Turbines
Water-power
Kuwait
ISSN:2071-1050, 2071-1050
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Shrnutí:Preventive maintenance (PM) is a maintenance program with activities created at a determined interval or according to certain principles, designed to reduce the likelihood of failure or deterioration of item performance. This aims to improve overall reliability and system availability. In this research, a preventive maintenance schedule (PMS) was designed for electricity and desalination of water in power plants, subject to meeting relevant constraints. The proposed methodology is used to generate a PMS for the boilers, turbines, and distillers. A nonlinear integer programming (NLIP) model was employed to address this problem. The results of the proposed method were compared with the PMS for a power station in Kuwait. The results were better in terms of the volume of production and in terms of the gap between the available production and demand in order to continue providing consumers with electricity and water without a shortage in the event of a breakdown in equipment. It produces an improvement of 12.12% and 16.58% respectively, for water and electricity. Furthermore, the sensitivity and robustness of the proposed method were analysed by increasing the maintenance duration for some equipment, increasing the demand, and adding various additional conditions. In addition, a comparison of additional conditions with a binary problem method in terms of computer time for the search for an optimal solution was carried out, where the model provided an optimal solution in a reasonable time. Among the most important benefits that the user can obtain for this technique are extending the life of the equipment, increasing efficiency, and reducing expenses.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2071-1050
2071-1050
DOI:10.3390/su15010239