Maintenance lifecycle cost analysis through Agent-Based Simulation

Abstract

Proper maintenance management allows companies to reduce failures and breakdowns while keeping high asset productivity. Several variables and uncertainties affect the selection of the optimal maintenance policy, and the one that might seem more cost effective in the short-term, might reveal having a total higher cost over the complete asset lifecycle. In this sense, the use of simulation to quantify the maintenance costs over the entire asset lifecycle can be helpful, allowing companies to test different scenarios and compare their result in a dynamic way, looking at long-term effects instead of short-term ones. The paper proposes an agent-based simulation model that allows to quantify the total costs associated with different maintenance policies, as well as computing productivity and important maintenance indexes to help companies in evaluating the most suitable maintenance strategy, being it used internally, or as a selling point for maintenance services towards customers.