Inventory management is becoming a critical aspect of maintenance-repair businesses. The goal of companies is to minimize inventory costs while maximizing service levels. The ability to perform these two conflicting situations at the optimum level provides various benefits to enterprises. This study offers a systematic literature review on spare parts management. The primary focus of this study is the literature on spare parts classification, inventory management, and warehouse management in the maintenance and repair industry over the last 14 years. The Systematic Literature Review included 118 studies that met the predetermined criteria and were examined within the framework of our research questions. We presented an overview of statistics, goals, inputs, methods, and findings. In addition, this study offers suggestions for future research by pointing to subjects that have not yet been studied or understudied in the literature. The variety of inputs in classification studies is increasing. While traditional inputs include cost, lead times, demand, usage, and failure rates, recent studies integrate strategic criteria such as supplier predictability, inventory policies, and order replenishment frequency. Classic methods considering criteria such as cost and criticality remain prevalent, while multi-criteria and machine learning techniques are increasingly applied. In inventory management studies, inventory and maintenance planning are mostly addressed separately, and the focus is frequently on cost minimization. Considering stochastic demand, joint maintenance and inventory planning, and multi-objective optimization may yield improvements. While new technologies such as blockchain and internet of things offer high potential for warehouse traceability, inventory movements, their adoption remains limited.
Inventory management Inventory classification Warehouse management Spare Parts Maintenance – repair
| Primary Language | English |
|---|---|
| Subjects | Industrial Engineering |
| Journal Section | Review Article |
| Authors | |
| Early Pub Date | October 17, 2025 |
| Publication Date | October 25, 2025 |
| Submission Date | May 16, 2024 |
| Acceptance Date | August 11, 2025 |
| Published in Issue | Year 2025 Early View |