Enhancing Asset Management in Gas Distribution Predictive Maintenance and Data-Driven Decision Making

ABSTRACT

This review paper explores the evolving landscape of asset management in the gas distribution sector, focusing on integrating predictive maintenance and data-driven decision-making. The study begins by examining the limitations of traditional asset management approaches and introduces the concepts of predictive maintenance and advanced data analytics as modern solutions. It delves into the technological advancements that underpin these practices, including sensors, IoT devices, machine learning, AI, and big data analytics. The paper further highlights the numerous benefits of predictive maintenance, such as cost efficiency, enhanced reliability and safety, and the prolonged lifespan of assets. Additionally, it discusses future directions and emerging trends, such as the integration of AI and blockchain, the impact of regulatory changes, and the role of predictive maintenance in promoting sustainability. The review concludes that adopting predictive maintenance and advanced technologies is essential for optimizing asset management, ensuring operational reliability, and achieving sustainability goals in the gas distribution industry.

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WSN 201 (2025) 149-160

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