AI-Driven Integrated Maintenance for Rotating Equipment: Connecting Condition Monitoring, Instrumentation, and Diagnostic Systems

Abstract The rapid evolution of artificial intelligence (AI) presents a transformative opportunity for enhancing the reliability and efficiency of rotating equipment in the oil and gas industry. This paper presents a case-driven exploration into the integration of AI-powered diagnostics and predictive maintenance systems across instrumentation, condition monitoring, and operational feedback loops. Using three real-world failures from one of Kuwait's oil refinery companies as reference points involving a nitrogen compressor package, a turbo expander in the NGL-1 plant, and a high-speed gearbox. We demonstrate how an AI-integrated maintenance approach can overcome the limitations of traditional methods. The study highlights how diagnostic latency, human oversight, and fragmented data systems delay recovery and compromise asset integrity. It proposes a consolidated AI framework that correlates data from process instrumentation, DCS/PLC/ESD, and condition monitoring tools to enable real-time fault isolation, root cause analysis, and predictive maintenance actions which transforming Kuwait's Vision & Global technological and Financial hub under Vision 2035. The government's investment in digital infrastructure, AI partnerships, and mega-projects have paved the way for advanced industries to thrive. Oil and gas remain the economic backbone of Kuwait, and Kuwait's oil and petroleum companies are racing to modernize legacy systems. Integrating AI into rotating equipment maintenance is a strategic response to national ambitions and international competitiveness. This manuscript will also describe about the future plans of this Ai-Driven maintenance framework and what are the extra inputs that will effect the frameworks decision on the maintenance of the equipment's as well as a full integration on the process control of the refinery's process as to keep the equipment running at an optimal setting to give longevity to Kuwait oil refineries' assets insuring that the company will save large sum of money in maintenance expenditures.