The purpose of this paper is to present a mathematical model for forming maintenance teams that maximizes knowledge sharing while minimizing maintenance costs. The model aims to improve operational efficiency and reduce downtime in maintenance operations. The study also explores the impact of knowledge sharing on team performance and overall maintenance outcomes, providing a comprehensive tool for maintenance managers to enhance team effectiveness and productivity.
This study proposes a mathematical programming model for effective maintenance team formation, aiming to maximize knowledge sharing and minimize maintenance delay costs. To solve the model, the logic-based Benders decomposition method was employed. A simulation-optimization framework, using historical maintenance data, was applied to evaluate the model's performance prior to implementation. This approach integrates theoretical modeling with practical application in real-world maintenance environments, showcasing its versatility and applicability across industries.
The implementation of the proposed model demonstrated significant improvements in key maintenance performance indicators, such as mean time to repair (MTTR), system availability, and overall productivity. The case study revealed that the model effectively boosted maintenance team effectiveness by reducing operational costs and optimizing team collaboration.
This research presents a novel approach to maintenance team formation that integrates knowledge sharing to enhance team performance. The proposed mathematical model optimizes team composition while simultaneously reducing maintenance-related costs, leading to significant improvements in operational efficiency. Additionally, by introducing a simulation tool, this study provides organizations with a means to validate results before implementation, offering a practical decision-making resource for maintenance managers.
