Optimization of Operational Risk in Ecuadorian Mining Using FMEA and Weibull Distribution to Reduce Critical Equipment Failures
Designing and implementing a preventive maintenance plan in the Ecuadorian mining industry requires systematic methodologies to reduce failures in crushing and grinding machines, improving operational availability and productivity. The main problem identified is reliance on corrective maintenance, with no historical failure records, which causes unexpected shutdowns. This study applies the FMEA (Failure Mode and Effects Analysis) methodology to evaluate the criticality of equipment using the Risk Priority Number (NPR), complemented with the Weibull distribution to model useful lifetimes. Key equipment such as the ball mill and jaw crusher at a mining beneficiation plant were analyzed. The results indicate that 25% of the subcomponents have NPR > 300 (unacceptable risk), mainly concentrated in structural elements subjected to severe operating conditions. A scenario analysis based on the fitted Weibull models and on reductions reported in the literature projects that implementation of the proposed preventive plan would reduce unplanned shutdowns by 40–50%, raising operational availability from the current 73% to approximately 90%; these figures are model-based projections and not post-implementation measurements. Weibull integration provides a robust statistical framework for the transition from reactive maintenance to predictive schemes, optimizing intervention intervals and extending the life of critical assets.