Track 2 Session 1

9:10 to 10:10 a.m. Tuesday, June 7, 2011

Achieving Reliability from Data at Cerrejón Coal

There can be no reliability analysis without an adequate data sample, and there can be no systematic, verifiable improvement in reliability nor in operational economy without reliability analysis. Well-known obstacles impede the reliability engineer in his role to analyze maintenance data. The main problem lies in the difficulty in obtaining analyzable data samples. In this context, a "sample" is a collection of failure mode life cycles, and each life cycle is defined by a beginning and ending event. Although modern CMMS systems should provide the needed information, they rarely deliver data samples of adequate quality. Cerrejón Minería, an integrated mining operation in Colombia, South America, solved the information management problem by applying a Living Reliability Centered Maintenance (LRCM) process to its fleets of trucks, graders, dozers, scrapers and shovels.

This presentation describes a method wherein completed work orders capture the information required for reliability analysis. The "right" maintenance observations reference significant failure modes. Work orders link to records in a continuously growing RCM-structured knowledge base. Grouped and filtered knowledge-to-work order links, being instances of failure modes, provide the samples required by reliability analysis software tools and methods. LRCM software and related procedures facilitate the growth of knowledge, manage the work order-to-RCM relationship and generate samples for subsequent reliability analysis.

Key Words: RCM, Continuous Improvement, Reliability Analysis, CBM, Predictive Maintenance, Reliability Centered Maintenance

Murray Wiseman and Daming Lin

Optimal Maintenance Decisions (OMDEC)

Quebec, Canada

Juan Carlos Consuegra and Gerardo Vargas

Cerrejón Minería