The aim of this course is to provide an analytical introduction to the core concepts of reliability and maintenance with emphasis on more advanced topics in statistical methods for reliability data and analysis of field reliability data, accelerated failure time data, software reliability modeling.

After completing this course, the students should

understand a general and advanced strategies that can be used for data analysis, modeling, and inference from reliability data;

critically analyze field-failure data, repairable system and recurrence data;

develop the capacity of modelling accelerating life tests data, degradation data;

comprehend maintenance and software reliability.

At the end of this course, the students will be able to understand

basic ideas behind product reliability, reasons for collecting reliability data and  distinguishing features of reliability data;

general strategy that can be used for data analysis, modeling, and inference from reliability data;

system reliability modeling, the distribution of system failure time as a function of individual component failure-time distributions, estimate system reliability, analysis of data with more than one failure mode;

typical data from repairable systems and other applications that have recurrence data, the combined use of simple parametric and nonparametric graphical methods for drawing conclusions from recurrence data;

applications of accelerated life testing, nonparametric and graphical methods for presenting and analyzing accelerated life test data;

degradation models, connection between degradation models and failure-time models, differences between degradation data analysis and traditional failure-time data analysis;

failure time regression models and prediction of reliability;

concept of maintenance, preventive and corrective maintenance.

some basic ideas of software reliability modeling;

Reliability concepts: Basic concept of reliability. Examples and features of reliability data. Strategy for collection, modeling, and analysis of reliability data. Models for continuous failure-time processes. Models for discrete data from a continuous process.

Component and system reliability concepts and methods: Location-scale-based distributions – concept and applications in reliability. Probability plots. Reliability block diagram, component reliability, system reliability, reliability of series and parallel systems. Failure mode. Competing risk model. Mixture model.

Analysis of repairable system and recurrence data: Intensity function, mean cumulative function, tests for recurrence rate trend. Models for perfect repair, minimal repair and imperfect repair – derivation and estimation.

Accelerated failure time models: Accelerating variables, life-stress relationships and acceleration models. Guideline for the use of accelerating models. Non-parametric and graphical methods for presenting and analyzing accelerated life test (ALT) data. Likelihood methods for analyzing censored data from an ALT. Suggestions for drawing conclusions from ALT data. Potential pitfalls of accelerated life testing.

Degradation data, models, and data analysis: Degradation data. Models for degradation data. Estimation of model parameters. Comparison with traditional failure-time analysis. Approximate degradation analysis.

Failure time regression models: Models fitting and applications in reliability.

Software reliability modeling: Concept of software reliability. Software reliability modeling and estimation. Software testing procedures. Prediction and management of software reliability.

Prediction of reliability: Motivation and prediction problems. Naive method for computing a prediction interval. Prediction of future failures from a single group of units and from multiple groups of units with staggered entry into the field.

Maintenance: Maintenance, preventive and corrective maintenance, optimum preventive maintenance – concept and applications.

Case studies: Analysis of field reliability data.

1)

Meeker, W. Q. and Escobar, L. A. (1998): Statistical Methods for Reliability Data, Wiley, N.Y.

2)

Nelson, W. (1990): Accelerated Testing: Statistical Models, Test Plans, and Data Analyses, Wiley, New York.

3)

Ansell, J. I. and Phillips, M. J. (1994): Practical Methods for Reliability Data Analysis, Clarendon Press, Oxford.

4)

Balakrishnan, N. and Rao, C. R. (Eds.) (2001): Handbook of Statistics, Vol. 20, Advances in Reliability, Elsevier, The Netherlands.

5

Blischke, W.R., Karim, M.R., and Murthy, D.N.P. (2011). Warranty Data Collection and Analysis, Springer-Verlag London Limited.

6)

Blischke, W. R. and Murthy, D. N. P. (2000) Reliability. Wiley, New York.

7)

Hamada, M. S., Alyson G. Wilson, C. Shane Reese and Harry F. Martz (2008): Bayesian Reliability, Springer-Verlag.

8)

Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data, Wiley, New York.

9)

Kobbacy, K.A.H and Murthy, D.N.P. (2008). Complex System Maintenance Handbook, Springer-Verlag.

10)

Lawless, J. F. (2003): Statistical Models and Methods for Lifetime Data, 2nd ed., Wiley, N.Y.

11)

Sinha, S. K. (1986). Reliability and Life Testing, Wiley Eastern Ltd., India.

12)

Tobias, P. A. and Trindade, D. C. (1995). Applied Reliability, 2nd ed., Van Nostrand Reinhold, New York.