Selection of condition monitoring techniques using discrete probability distributions: a case study

The setting up of a condition monitoring program is considered a strategic decision owing to its influence on cost, safety, quality, and availability in an industrial plant. However, no previous structured analysis of the selection of condition monitoring techniques and their characteristics has been made, so further analysis is needed. This paper proposes a model for the selection of the most suitable condition monitoring technique to be set up in a subsidiary of a petrochemical plant. For this purpose, different criteria, indicators, and utility functions are defined; nine alternatives are proposed depending on the technological level of the condition monitoring program. The model applies the analytic hierarchy process to obtain a ranking of alternatives. Owing to the special characteristics of the decision, discrete probability distributions are defined. The final ranking is computed by applying the Monte Carlo method considering 2000 simulation trials. Finally, a sensitivity analysis is applied.