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When traditional or innovative maintenance policies are applied, the effectiveness of the actions carried out is highly influenced by the possibilities to isolate in the shortest time the faulted items. Fault isolation is directly related to the troubleshooting process adopted and impacts on the time needed to carry out the maintenance actions. Through the adoption of suitable maintenance policies, supported by an effective troubleshooting process, the mean time to repair of the single equipment can be reduced, system availability increased and the life cycle cost of the whole system decreased. In this paper the authors present a modelling procedure, based on Monte Carlo method for generating failure occurrence times of basic items, to simulate the troubleshooting process and to identify optimal solutions taking into account an a priori defined cost function. Such probabilistic approach has been applied to a case study and the results are presented and discussed in the paper.