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"The optimal predictive  preventive  corrective and opportunistic maintenance policies play an important role in the success of sustainable maintenance operations  This study discusses a new energy efficiency-related maintenance policy optimization method  which is based on failure data and status information from both the physical system and the digital twin-based discrete event simulation  The study presents the functional model  the mathematical model and the solution algorithm  The maintenance optimization method proposed in this paper is made up of four main phases  computation of energy consumption based on the levelized cost of energy  computation of GHG emission  computation of value determination equations and application of the Howard   s policy iteration techniques  The approach was tested with a scenario analysis  where different electricity generation sources were taken into consideration  The computational results validated the optimization method and show that optimized maintenance policies can lead to an average of 38  cost reduction regarding energy consumption related costs  Practical implications of the proposed model and method regard the possibility of finding optimal maintenance policies that can affect the energy consumption and emissions from the operation and maintenance of manufacturing systems "
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