110.1 110.2 110.3 110.4 110.5 110.6 110.7 110.8 110.9 110.10 110.11 110.12 110.13 110.14 110.15 110.16 110.17 110.18 110.19 110.20 110.21 110.22 Introduction Catastrophic Failure Models The Bathtub Curve Mean Time To Failure (MTTF)Average Failure Rate A Posteriori Failure Probability Units for Failure Rates Application of the Binomial Distribution Application of the Poisson Distribution The Exponential Distribution The Weibull Distribution Combinatorial Aspects Modeling Maintenance Markov Models Binary Model for a Repairable Component Two Dissimilar Repairable Components Two Identical Repairable Components Frequency andDuration Techniques Applications of Markov Process Some Useful Approximations Application Aspects Reliability and Economics
Oklahoma State University
Reliability engineering is a vast ﬁeld and it has grown signiﬁcantly during the past ﬁve decades (since World War II). The two major approaches to reliability assessment and prediction are (1) traditional methodsbased on probabilistic assessment of ﬁeld data and (2) methods based on the analysis of failure mechanisms and physics of failure. The latter is more accurate, but is difﬁcult and time consuming to implement. The ﬁrst one, in spite of its many ﬂaws, continues to be in use. Some of the many areas encompassing reliability engineering are reliability allocation and optimization, reliability growthand modeling, reliability testing including accelerated testing, data analysis and graphical techniques, quality control and acceptance sampling, maintenance engineering, repairable system modeling and analysis, software reliability, system safety analysis, Bayesian analysis, reliability management, simulation and Monte Carlo techniques, Failure Modes, Effects and Criticality Analysis (FMECA), andeconomic aspects of reliability, to mention a few. Application of reliability techniques is gaining importance in all branches of engineering because of its effectiveness in the detection, prevention, and correction of failures in the design, manufacturing, and operational
1Some of the material in this chapter was previously published by CRC Press in The Engineering Handbook, R. C. Dorf, Ed.,1996.
© 2000 by CRC Press LLC
INFORMATION MANAGEMENT SYSTEM FOR MANUFACTURING EFFICIENCY
t current schedules, each of NASA’s four Space Shuttle Orbiters must ﬂy two or three times a year. Preparing an orbiter for its next mission is an incredibly complex process and much of the work is accomplished in the Orbiter Processing Facility (OPF) at Kennedy Space Center. The average “ﬂow” — thecomplete cycle of refurbishing an orbiter — requires the integration of approximately 10,000 work events, takes 65 days, and some 40,000 technician labor hours. Under the best conditions, scheduling each of the 10,000 work events in a single ﬂow would be a task of monumental proportions. But the job is further complicated by the fact that only half the work is standard and predictable; the other halfis composed of problem-generated tasks and jobs speciﬁc to the next mission, which creates a highly dynamic processing environment and requires frequent rescheduling. For all the difﬁculties, Kennedy Space Center and its prime contractor for shuttle processing — Lockheed Space Operations Company (LSOC) — are doing an outstanding job of managing OPF operations with the help of a number of processinginnovations in recent years. One of the most important is the Ground Processing Scheduling System, or GPSS. The GPSS is a software system for enhancing efﬁciency by providing an automated scheduling tool that predicts conﬂicts between scheduled tasks, helps human schedulers resolve those conﬂicts, and searches for near-optimal schedules. GPSS is a cooperative development of Ames Research...