Modeling and simulation for inventory management of repairable items in maintenance systems. (November 2022)

• Record Type: Journal Article
• Authors: Saeed Osman, Mojahid F
• Is Part Of: Simulation. Volume 98:Number 11(2022)
• Page Start: 1013
• Page End: 1037
• Publication Date: 2022-11
• Subjects: Simulation modeling -- maintenance system -- repairable items -- inventory system -- reordering policy -- uncertainty modeling -- parametric analysis; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/00375497221099549
• Languages: English
• ISSNs: 0037-5497

Abstract

Simulation models have become promising methods to investigate and improve real-world systems. This paper describes the development of effective simulation-based models for maintenance systems in a manufacturing environment whereby production lines send their faulty but repairable items to a repair shop. The proposed models aim at investigating the centralized storage of repaired items with three replenishing strategies, lot-for-lot ( L4L ), economic order quantity and reorder point ( Q-R ), and minimum-maximum order level ( s-S ) reordering policies of repairable items with backordering allowance in a risk-free and flexible manner to effectively manage the procurement of new repairable items and control three inventories of repairable items, repaired ready-for-use, new, and faulty awaiting repair. The models take into account the uncertain environment of maintenance systems and the probabilistic nature of the failures, repair times, and lead times of repairable items. The demand for repairable items in these three inventories is both stochastic and dynamic. A simulation case problem is presented to demonstrate the suitability and applicability of the proposed simulation models and to study the influence of different parameters on performance measures using parametric analysis. The main results are the vital decision-making insights provided by the developed models about the three reordering policies and the three inventories of repairable items. These managerial insights are essential for achieving minimum inventory costs and maximum service levels.