Joint Production and Maintenance Optimization of a Series-Parallel System with Quality-Contingent Demand

Making a reasonable and effective production plan is always an essential and challenging task in industrial production. A joint optimization model of production and maintenance is proposed in this paper, which considers the structural relationship between production units and the influence of the unit state on demand. A three-unit series-parallel system is selected to calculate the steady-state probability density function of the system, and the model is established by dividing different maintenance situations in one cycle. By analyzing the composition of expected cost and expected time in each situation, the expected cost rate is calculated by using renewal reward theory. The objective function of the model is to minimize the expected cost rate. The genetic algorithm is improved according to the model characteristics. The application of the model is illustrated by a case, and the sensitivity analysis is set to show the influence of different parameters on the decision-making results of the system, providing ideas for decision-makers. Finally, the contrast experiments show the advantages of the proposed model and method.

Automated summary

This paper proposes a joint optimization model that considers the relationship between production units and the influence of unit state on demand. The objective is to minimize the expected cost rate by analyzing the composition of cost and time and using renewal reward theory. The application of the model is illustrated through a case study, and sensitivity analysis is used to analyze the impact of different parameters on decision-making results.