Calixto - Gas and oil reliability engineering : modeling and analysis

The oil and gas industry is a competitive market that requires high performance in plants that can be translated to high availability, reliability, and maintainability for equipment. Today, this expectation of high reliability is extended to equipment suppliers and is also required of equipment companies. Therefore, reliability engineering tools are very important to this industry and have contributed greatly to its success in the last several decades.

Reliability engineering should be applied systematically in the oil and gas industry to maintain high performance. To meet this goal, reliability management must be a part of daily operations. Reliability management includes life cycle analysis, accelerated testing, reliability growth analysis, DFMEA (design failure mode analysis), FMEA (failure mode analysis), RCM (reliability centered on maintenance), RBI (risk-based inspection), ReBI (reliability-based inspection), ReGBI (reliability growthbased inspection), ORT (optimum replacement time), RAM (reliability, availability, and maintainability) analysis, human reliability analysis, FTA (fault tree analysis), ETA (event tree analysis), LOPA (layers of protection analysis), SIL (safety integrity level) analysis, and bow tie analysis.

All of these techniques must be included and managed from the project phase to the operational phase. Moreover, when equipment is being developed accelerated testing analysis, reliability growth analysis, and DFMEA are highly important for supporting product development and achieving a reliability target.

It is important to apply such tools and to do so it is necessary to have historical failure data to input into the analysis. However, for companies with operational plants, platforms, and other facilities, quantitative and qualitative techniques are required during different phases of the life cycle. In project and operational phases, FMEA, RCM, RBI, ReBI, ReGBI, ORT, RAM analysis, and human reliability analysis can be applied to support decisions for achieving and maintaining high performance in plants, including high availability and reliability. In addition, safety is one of the most important considerations in the oil and gas industry, and quantitative risk analysis tools, such as FTA, ETA, LOPA, SIL, and bow tie analysis, can be implemented during the project and operational phases and supported by life cycle analysis with safe functions such as layers of protection.

This book discusses all of these techniques and includes examples applied to the oil and gas industry.

describes the methodology used to deal with historical failure and repair data, the type of data (complete, censored, and interval), how to obtain information from specialists, and how to turn historical data into probability density function (PDF) parameters and reliability functions. Thus, different methods used to define PDF parameters, such as the plot, rank regression, and maximum likelihood methods, are discussed. The different types of PDFs, such as exponential, Weibull, lognormal, loglogistic, normal, logistic, Gumbel, gamma, and generalized gamma, and their parameter characteristics, are also discussed including the importance of confidence limits.

describes the importance of qualitative (HALT and HASS) and quantitative accelerated testing with different types of methods such as Arrhenius, Eyring, inverse power law, temperature-humidity, temperature-nonthermal, general loglinear, proportional hazard model, and the cumulative risk model. In addition, reliability growth analysis methods, such as Duanne, Crow-Ansaa (NHPP), Lloyd-Lipow, Gompertz, logistic, Crow extended, and power law, are discussed. These methods are described mathematically with examples and graphs.

describes how to apply qualitative approaches such as DFMEA and FMEA to understand failure modes and their causes and proposes recommendations to eliminate them. In addition, maintenance and inspection tools such as RCM and RBI are presented with examples. Additionally, quantitative methods used to define inspections, such as ReBI and ReGBI, and optimum replacement time are discussed with examples.

presents step-by-step instructions for implementing RAM analysis methodology and covers the different availability concepts and sensitivity analysis methods for assessing maintenance, stock, and standby policies including logistics issues. In addition, different plant case studies are presented to illustrate these concepts and show different applications