Asset Complexity Based Benchmarks in Support of Reliability Improvement Program

Abstract

Abstract Successfully executing maintenance & reliability improvement programs on a complex pipeline asset network tends to be challenging. Influencing the factors that affect reliability performance usually involves elements of culture, asset management & operations, resource allocation, reliability and maintenance strategy and maintenance execution. Frequently, the focus of attention is placed primarily on tracking detailed reliability & maintenance performance (i.e. tool time, average time between failures, planned work, etc.) because they tend to be easier to understand and measure. When some of the other key factors potentially holding back the full realization of significant reliability improvements may be at the resource allocation level where usually measuring and benchmarking can be more challenging. In this sense, being able to benchmark different operating areas in terms of maintenance, reliability and resources allocation performance can help understand higher level factors driving less than ideal asset reliability performance. Supporting the implementation of a Reliability Centered Maintenance (RCM) program on a vast liquid pipeline network, multi-attribute decision making (MADM) techniques and concepts were used to create assessment models that based around the notion of complexity were then used to benchmark multiple operating regions. From these assessment models, derived benchmarking indexes such as maintenance technicians per equivalent complexity or maintenance budget per equivalent complexity were created and used in support of resource allocation discussions. The paper will describe the use of a MADM techniques, discuss how different complexity models were developed working in collaboration with multiple maintenance SMEs, discuss some of the analysis and findings of different regional benchmarks and also comment on some of the cultural challenges encountered when using and communicating quantitative benchmarks to influence and drive reliability improvements. Hopefully this paper will help other professionals in the industry understand how SME experience can be captured and transformed into assessment tools for use in benchmarking.