AI-Driven Enhancements for Asset Performance Management

This technical report discusses the application of artificial intelligence (AI) and machine learning in enhancing asset performance management within process manufacturing enterprises. It outlines the current state of AI usage, revealing that while condition-based maintenance is common, a minority of organizations effectively utilize AI to improve maintenance practices. The report details the findings from a survey of industry experts, highlighting that 63 percent of respondents have implemented advanced analytics and AI for asset performance improvement. It also emphasizes the need for AI functionality to provide early warnings and prevent failures, ensuring asset availability aligns with performance goals. The report further examines the challenges of integrating AI into existing systems, noting the technical debt incurred by relying on in-house platforms. Additionally, it discusses the importance of developing a comprehensive asset performance strategy that incorporates AI capabilities, supported by methodologies such as the Scaled Agile Framework (SAFe) to enhance collaboration between IT and operational teams.