ABSTRACT
Chapter 6 introduces the concepts of condition-based and predictive asset monitoring for best practices in asset management. In this chapter, the ProcIndustries South Texas refinery transitions from reactive, corrective maintenance practices to a proactive condition-based preventive maintenance methodology. Performing calendar-based servicing of critical assets does not often align with degrading asset performance behavior and results in unnecessary costs. Using the enterprise industrial data infrastructure (EIDI), the refinery implements a condition-based maintenance program where the actual performance data determines maintenance activities. Industry best practices are presented for predictive maintenance, which estimates time-to-failure for critical assets based on historical performance data. And this chapter discusses the evolution of process control effectiveness. Empowering workers to make quicker decisions that impact plant operations and production is critical to effective business operations.
