Optimal Inspection Period for Protective Sensors: An Integrated Risk-Informed Multicriteria Optimization-Simulation Approach

Equipment failure is the leading cause of industrial operational disruption. Unplanned downtime equipment accounts for 11% of manufacturing revenue, highlighting the need for effective proactive maintenance strategies, such as protective sensors that can detect potential failures in critical equipment before a functional failure occurs. However, sensors are also subject to hidden failures, requiring periodic inspections to ensure proper functioning. This study proposes a novel, integrated, and generic multimethodological approach combining discrete event simulation, Monte Carlo, optimization, risk analysis, and multicriteria decision analysis methods to determine the optimal inspection period for a protective sensor subject to hidden failures. Alternative inspection periods are evaluated based on their risk-informed overall values, considering multiple conflicting Key Performance Indicators, such as maintenance costs and equipment availability. The optimal inspection period is then selected considering uncertainties and the intertemporal, intra-criterion, and inter-criteria preferences of the organization. The effectiveness of the approach is demonstrated through a case study applied at the leading Portuguese electric utility, replacing previous empirical inspection standards that did not consider economic costs and uncertainties, supported by an open, transparent, auditable, and user-friendly decision support system implemented in Microsoft Excel using only built-in functions and modeled based on the principles of Probability Management.