 Maintenance optimisation in a cement industry raw-mill system using genetic algorithmMl. Mahadevan and T. Paul Robert International Journal of Decision Sciences, Risk and Management, 2010, vol. 2, issue 3/4, 291-307 Abstract: This paper describes a maintenance optimisation framework for deriving optimal maintenance schedule for a process plant using genetic algorithm (GA). The two possible alternatives considered are: imperfect maintenance and replacement. The maintenance model incorporates both the corrective maintenance and preventive maintenance actions. GA search heuristic is used to optimise the choice of maintenance or replacement to achieve the minimum cost with target reliability. The model is evaluated by Monte Carlo simulation in terms of present value of the cost. The flexibility of the Monte Carlo method allows the inclusion of several practical aspects such as deteriorating repairs, aging and service variations. This study is carried out in the raw-mill section of a cement industry in Tamil Nadu, India. Keywords: maintenance planning; Monte Carlo simulation; genetic algorithms; GAs; aging; optimisation; cement industry; raw mills; maintenance scheduling; India; imperfect maintenance; replacement; maintenance modelling; corrective maintenance; preventive maintenance; deteriorating repairs; service variations. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdsrm:v:2:y:2010:i:3/4:p:291-307 Access Statistics for this article More articles in International Journal of Decision Sciences, Risk and Management from Inderscience Enterprises Ltd |
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