From Predictive to Prescriptive Maintenance in Power Generation: An Integrated Five-Layer Framework Validated through Systematic Comparative Analysis
Dari Pemeliharaan Prediktif ke Prescriptive di Pembangkit Listrik: Five-Layer Framework Terintegrasi Dengan Validasi Menggunakan Systematic Comparative Analysis
DOI:
https://doi.org/10.21070/ups.8962Keywords:
Prescriptive maintenance, Systematic literature review, Systematic Comparative Analysis, Prescriptive Maintenance FrameworkAbstract
Prescriptive maintenance (RxM) has emerged as a strategic evolution in power generation, advancing beyond reactive and predictive approaches by leveraging technologies associated with Industry 4.0. The potential of RxM lies in its ability to support proactive and data driven decision processes. However, existing frameworks remain fragmented and lacking the modularity in complex and variable power plant environments. This study conducts a systematic literature review guided by five research questions to explore the conceptual foundations of RxM, the enabling technologies that support its application including the Internet of Things, machine learning, digital twins, and deep reinforcement learning, the structural components that define its architecture, the primary challenges to its implementation, and the strategies used for validation. Based on these findings, a modular and adaptive RxM framework is developed and conceptually validated using a systematic comparative analysis against seven benchmark studies. The proposed framework integrates cloud-edge computing infrastructures, advanced analytical layers, multi criteria evaluation mechanisms, and iterative feedback processes. The comparative results emphasize the framework's ability to support integrated and responsive maintenance strategies while remaining compatible with industrial platforms. Its design supports both new and existing operational environments, allowing gradual integration without requiring complete system replacement. This study offers a generalizable reference model that can guide organizations seeking to transition from predictive to prescriptive maintenance in power generation. Future research should prioritize field implementation, real time validation, and alignment with broader industry goals including environmental sustainability, transparent artificial intelligence, and improved protection of digital infrastructure
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