The owner and operator of 7,000 kilometers of rail track spanning multiple islands and regions in Indonesia, KAI initiated a digitalization and modernization project to facilitate predictive network maintenance, enabling smarter, data-driven asset management. Faced with data standardization issues, system integration, coordination difficulties, and scalability concerns, KAI’s initial software and maintenance approaches proved insufficient to meet their needs. They needed a comprehensive, integrated asset modeling and monitoring solution to ensure a more reliable, safer, and sustainable railway network.

Leveraging Bentley AssetWise and iTwin applications, KAI established a common data environment and digital twin that incorporated AI to detect risks early, optimize asset lifecycle, and support intelligent decision-making. Bentley’s applications facilitated predictive maintenance through real-time condition monitoring and seamless system integration that reduced railway track maintenance by two to four hours per segment, improving average efficiency by 25% to 40%. The synergetic digital solution extends asset life, lowers carbon emissions, and reduces material waste, supporting smarter, greener network planning and operations.