SPEAKERS & SESSIONS

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SPEAKER

Murray Wiseman, President, LivingReliability Inc.

Murray Wiseman innovates in maintenance engineering, management, and consulting, with particular focus on using maintenance and operational data to achieve reliability. He founded and operated the world’s first web expert system- based commercial oil analysis laboratory. As a principal consultant at PricewaterhouseCoopers’ Centre of Excellence in Physical Asset Management he specialized in condition-based maintenance optimization. He is a RCM practitioner. He leads projects in condition-based maintenance optimization that achieve cost effective, safe increased equipment availability. He developed in collaboration with Carbones de Cerrejon the groundbreaking Living RCM (LRCM) process designed to achieve reliability from data. He is President of LivingReliability Inc., a software and consulting company dedicated to strategic reliability information and knowledge management. Murray holds a B. Eng. Mech. degree from McGill University.

VIDEO

SESSION

Achieving Reliability from Data
Track: Reactive to Proactive Decision Making
Murray Wiseman, President, LivingReliability Inc.

In a physical asset management process, an “optimal” decision policy will apply the right maintenance at the right time to the right components so as to achieve the highest possible enterprise profitability. Maintenance managers and engineers have long believed that within their data lie the secrets to achieving optimal decisions. That conviction has driven the growth of high technology services and tools that collect, display, manipulate, and store limitless quantities of data. However, most maintenance managers have grave doubts about the quality of the historical work order data stored in the enterprise asset management (EAM) system. They say that the data lacks veracity and consistency. Technicians often select the default code “other” when populating the drop down lists on work order form. We present the results of having applied a new process “living reliability centered maintenance” (LRCM) that ensures perfect transcription to the EAM database of the maintainer’s observations concerning the failure mode, its effects and consequences. . We’ll demonstrate a statistical method to build and verify optimized condition based decision model performance in achieving a stated corporate goal.