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Engineering Reliability (ASA-SIAM Series on Statistics and Applied Probability) (ASA-SIAM Series on Statistics and Applied Probability)
By Richard E. Barlow
Engineering reliability concerns failure data analysis, the economics of maintenance policies, and system reliability. This textbook develops the use of probability and statistics in engineering reliability and maintenance problems. The author uses probability models in the analysis of failure data, decisions relative to planned maintenance, and prediction relative to preliminary design. Some of the outstanding features include the analysis of failure data for both continuous and discrete probability from a finite population perspective, probability models derived from engineering considerations, an introduction to influence diagrams and decision making, and use of the operational Bayesian approach. The approach is fresh and interesting; it is motivated from problems in engineering and physical sciences and uses examples to illustrate the methodology. These examples, along with the use of real failure time data, will help the reader apply the techniques to real industrial situations.
By Richard E. Barlow
- Publisher: Society for Industrial Mathematics
- Number Of Pages: 219
- Publication Date: 1998-04-01
- ISBN-10 / ASIN: 0898714052
- ISBN-13 / EAN: 9780898714050
- Binding: Paperback
Engineering reliability concerns failure data analysis, the economics of maintenance policies, and system reliability. This textbook develops the use of probability and statistics in engineering reliability and maintenance problems. The author uses probability models in the analysis of failure data, decisions relative to planned maintenance, and prediction relative to preliminary design. Some of the outstanding features include the analysis of failure data for both continuous and discrete probability from a finite population perspective, probability models derived from engineering considerations, an introduction to influence diagrams and decision making, and use of the operational Bayesian approach. The approach is fresh and interesting; it is motivated from problems in engineering and physical sciences and uses examples to illustrate the methodology. These examples, along with the use of real failure time data, will help the reader apply the techniques to real industrial situations.
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