Integrated maintenance scheduling inventory policy adjustment considering back order disruptions using joint optimization approach

Abstract

PurposeThe purpose of this paper is to present an integrated strategy for inventory control and preventive maintenance planning for a single-machine production system with increasing failure rates.Design/methodology/approachThere are three scenarios for solving presented model. The strategy is such that the production component is placed under maintenance as soon as it reaches the m level or in the event of a malfunction earlier than m. Maintenance completion time is not predictable. As a result of periodic maintenance, a buffer stock h is held and the production component starts to produce from period A with the maximum throughput to satisfy demand and handle the shortage. A numerical algorithm to find the optimal policy is developed. The algorithm is implemented using MATLAB software.FindingsThe authors discovered that joint optimization mainly reduces production system costs. Cs is holding cost of a product unit during a unit of time. The authors consider two values for Cs, consist of, Cs = 1 and Cs = 2. By comparing the two cases, it is concluded that by reducing the cost from Cs = 2 to Cs = 1, the optimal scenario does not differ. The amount of decision variables decreases.Originality/valueThis paper is the provision of a model in which the shortage of back order type is considered, which greatly increases the complexity of the problem compared to similar issues. The methods for solving such problems are provided by the numerical algorithm, and the use of buffers as a way to compensate for the shortage in the event of a complete shutdown of the production line which is a very effective and efficient way to deal with customer loss.

Maintenance work management process model: incorporating system dynamics and 4IR technologies

“…Babaeimorad et al . used joint optimization approach to model the integrated maintenance scheduling inventory policy adjustment (Babaeimorad et al ., 2022). Furthermore, the mathematical model of Babaeimorad et al .…”

“…Several scholars modelled different elements of maintenance management aiming at cost reduction gains. Babaeimorad et al used joint optimization approach to model the integrated maintenance scheduling inventory policy adjustment (Babaeimorad et al, 2022). Furthermore, the mathematical model of Babaeimorad et al determined the inventory level and preventive maintenance planning for a single equipment production system with increasing random failures.…”

“…Furthermore, the mathematical model of Babaeimorad et al determined the inventory level and preventive maintenance planning for a single equipment production system with increasing random failures. The scholars highlight that decision-makers can minimize the total operating cost using decision variables such as production capacity quantities, maintenance costs, and machine failure distribution (Babaeimorad et al, 2022). Zul-Altfi Ismail conducted a case study on the requirements of maintenance management systems to improve ineffective maintenance management systems.…”