This qualitative literature review explores "Dynamic Workload Adjustment in Condition-Based Maintenance: A Review of Robust Optimization Approaches for Production Systems." The study synthesizes recent advancements in condition-based maintenance (CBM) frameworks, focusing on the application of robust optimization techniques to enhance production efficiency and maintenance decision-making. The review highlights the importance of dynamic workload adjustment as a crucial strategy for aligning maintenance activities with fluctuating production demands, ultimately aiming to minimize downtime and optimize resource utilization. By analyzing eight key studies in the field, this review identifies the strengths and challenges associated with the implementation of robust optimization models in CBM practices. Key findings indicate that while robust optimization significantly improves maintenance outcomes, challenges remain in terms of complexity, required skill sets, and organizational culture. The review concludes by emphasizing the need for further empirical research and the exploration of hybrid models to fully realize the benefits of dynamic workload adjustment in diverse industrial contexts. This study provides a comprehensive overview that will aid researchers and practitioners in understanding and advancing condition-based maintenance methodologies.
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