Stochastic Petri Nets Maintenance Modeling of a Butter Oil Processing Plant

Preventive Maintenance (PM) has been playing a key role in the reliability and sustainability of industrial operations by preventing the failure of various components resulting in a breakdown. Further, this breakdown in industrial operations inhibits the scale and goals of production thereby affecting financial growth. Butter oil is one of the most consumed oils in the world, so its production in processing plants should be monitored and optimized maintenance schedules for the equipment should be adopted which affects the production in a plant. In the present paper, the preventive maintenance (PM) modeling of the butter oil processing plant is carried out using Stochastic Petri nets (SPN). The optimal preventive maintenance schedules are decided under the various constraints of maximizing availability, minimizing cost, and maximizing revenue generation. The programming package Mathematica is used to solve the complex equations of the framework in maximizing the availability, revenue per unit, and minimizing cost. The efficacy of the model is assessed by performance parameters of plant availability and maintenance cost. It is found from investigations that the system availability could be increased from 0.81 to 0.91 and the cost could be reduced from 40 to 32%. Hence, it is concluded that the implementation of preventive maintenance schedules could be useful in achieving production goals.