A Discrete Event Simulator to Support Maintenance Decision-Making considering Economic and Environmental Sustainability

Maintenance plays a crucial role in sustainability by influencing sustainable practices both through its own actions, which entail inherent flows and consequences, and through its impact on the performance of maintained assets across the triple bottom line. To manage maintenance from a sustainable perspective, appropriate indices able to represent environmental assessment results in an aggregated and synthetic way are necessary, along with rational decision-making tools able to simulate different maintenance alternatives considering various sustainability dimensions. This work builds upon a methodology that integrates Sustainability Indices and RAM Analysis to evaluate the environmental and economic impacts of maintenance activities. Specifically, a Discrete Event Simulator is developed, combining Petri Nets modeling with a design pattern to generate Monte Carlo simulations in Python. Through the application of the proposed methodology to a proof of concept, we demonstrate the simulator's capability to evaluate both the environmental and economic impacts of various maintenance activities. The obtained results highlight the potential applicability of the approach to industrial systems, emphasizing its contribution to the advancement of sustainable maintenance practices.