Global Plant Engineering - October 2010 - (Page 25)

Predictive diagnostics nuggets, Predictive Analytics operates on a real-time push model, identifying and flagging these subtle changes from expected behavior that have been verified to be actionable issues. Doing so, it identifies sensor, equipment and operational issues, and sometimes can identify issues weeks and months before failure. With these early warnings, operators can schedule appropriate maintenance or plan further investigation in context of the overall plant schedule. Hence, they avoid surprise equipment failures. Predictive Analytic technology is scalable to all critical rotating, non-rotating and process equipment, across the plant, across the fleet and across industries. It currently is being used in all sectors of power generation, including coal, combined cycle, nuclear, wind, hydro and in oil and gas, including upstream, gas transportation and downstream. In fact, approximately 50% of the U.S. power generation fleet uses it. Moving up the P-F curve Perhaps the easiest way of thinking about the advantages of Predictive Analytics is to review it in context of the P-F curve. Key points on the curve represent “Potential Failure” (P) and “Functional Failure” (F). Potential Failure occurs when events lead to component damage that needs repair. Functional Managing maintenance and repair activities against the cost of equipment failure with traditional condition-monitoring tools could yield a short time envelope. Failure occurs when equipment performance no longer meets design conditions and must be shut down for repair. Most reliability engineers use a “P-F curve” to visualize the activities of managing maintenance and repair activities against the cost of equipment failure. Before Predictive Analytics, with traditional condition-monitoring tools (e.g., vibration analysis), this could be a short time envelope, as indicated in Figure 2. Given the customized equipment models that automatically adapt to changes in load, ambient conditions and operating contexts, Predictive Analytics provides a more accurate assessment of the condition of each individual piece of equipment and earlier warning of developing issues. Quite simply, Predictive Analytics enables operators to provide extended lead time and enabling operators to fix small problems before they grow large or catastrophic. See Figure 3. Passing the baton to Predictive Diagnostics Predictive Diagnostics builds on the powerful foundation of Predictive Analytics, as

Table of Contents for the Digital Edition of Global Plant Engineering - October 2010

Global Plant Engineering - October 2010
Contents
Comment
Global Views
Hannover Messe Report
Asia Report
Americas Report
Winning the Race Against Equipment Failure
Take 8 Steps to Debug Process Control System
Optimize the Enterprise: Measurement, Empowerment, and Control are the Essential Ingredients
Air Apparent: Compressed Air Audits Let You Find the Leaks in Your System
The Promise of the Smart Grid: A Flexible, Dynamic Energy Management System
Europe Report

Global Plant Engineering - October 2010