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Reliability Data Analysis

Introduction

Reliability is crucial to the success of product sales in today competitive market. Reliability test is now a common routine to most of the manufacturing. However, the analysis of reliability test data is not straight forward since it involves advanced statistics. There are many existence software available for the reliability data analysis, but most of them have inherent assumptions that are suitable for system reliability rather than component reliability. Also, without understanding the impact of these assumptions could make the analysis results invalid.

This course provides a basic understanding of the reliability data analysis, and the various type of reliability data as well as their respectively analysis methodology. The planning of accelerate life testing will also be presented, and the extrapolation of the accelerated test data to normal operating conditions will be discussed in detail. Misconception in accelerated life testing and their extrapolation will be discussed.

Course Objectives

What You Will Learn
• Reliability concepts and types of reliability data
• Non-parametric analysis of reliability data and its limitation
• Parametric analysis of reliability data and its usefulness for reliability improvement
• Probability plotting in reliability data analysis and its precautious
• Planning of life tests for products
• Various accelerated test models and their use in extrapolation of test data for reliability prediction.

Course Outline

Day 1/2

Module 1: Reliability concepts and reliability data
- assess and improve product reliability
- important qualitative aspects of statistical models
- studies focusing on data from repairable systems and nonrepairable units.
- exploring, analyzing, and drawing conclusions

Module 2: Models and Censoring for Failure time data
- basic concepts
- basic relationships among cumulative distributions, densities, survival, hazard, and quantile functions
- importance of censoring, censoring mechanisms
- important assumptions about censoring mechanisms

Module 3: Non-parameteric estimation
- simple method that applies to problems with complete data or single censoring.
- statistical inference and the use of confidence intervals.
- confidence intervals for complete data or single censoring.
- simultaneous confidence bands to detect outlier data points
- use of company reliability data

Day 2/3

Module 4: Parametric Distributions
- basic concepts and motivation
- failure probabilities and distribution quantiles.
- location-scale family of distributions.
- log-location-scale distributions.

Module 5: Probability Plotting
- practical application
- distribution determination
- algorithm for identifying multiple failure mechanisms
- case studies
- Reliasoft

Day 4

Module 6: Planning life tests - Tools for evaluating and controlling estimation precision for a life test when censored data are expected.
- compute approximate sampling variability directly
- finding the sample size needed to control sampling variability
- methods for planning a test to demonstrate conformance
- case studies

Module 7: Accelerated test models - Models used for accelerated tests and introduces concepts of physics of failure.
- use-rate, temperature, and voltage acceleration
- models with a combination of accelerating variables
- common forms
- potential pitfalls

Trainer(s)

Associate Professor Tan, Cher Ming

Dr. Tan Cher Ming obtained his Electrical Engineering Degree from the National University of Singapore on 1984, and M.A. Sc and Ph.D in Electrical Engineering from the University of Toronto, Canada on 1987 and 1992 respectively. He has worked in the industry on reliability and failure analysis for 10 years before joining Nanyang Technological University. The companies he has worked with are Fairchild Semiconductor, Hewlett Packard, LiteOn Power Semiconductor (Taiwan), Chartered Semiconductor Mfg.

His research work is on Reliability engineering and failure analysis, nano-technology, power semiconductor, wafer bonding. He has published 150 papers in International Journal and Conferences. He has been invited to give several talks on reliability to the industry, and given a keynote speech in International Congress on Micro-reliability and Nano-reliability.

He is the immediate past Chair of IEEE Singapore Section, Chair of IEEE Nanotechnology Chapter in Singapore, Adjunct Senior Scientist in SIMTech, Fellow of Singapore Quality Institute, and Senior member in both the IEEE and ASQ. He was also awarded the first Distinguish Professor in Asia by Mathwork Inc. USA, and listed in Who’s Who in the World as well as Marquis Who’s Who in Science and Engineering, USA. He is also a reviewer of many international Journals, Chair of several International Conferences. He is the Chair of the Certified Reliability Engineers Program in the Singapore Quality Institute since 1999.

He is continuing giving consultation to industry in the area of reliability. Examples of some companies are Applied Materials, Delphi Automotive, Infineon Asia Pacific, Vestas R&D etc. He has also assisted RSAF to set up their electronic failure analysis Lab.

Who Should Attend

• R&D engineers
• Reliability engineers
• Process engineers

Prerequisite
Knowledge of basic statistics.

Course Details

Date:

30 June to 3 July 2009

Time:

9:00am to 5:00pm

Venue:

NTU@one-north campus, Executive Centre

Closing Date:

16 June 2009

Fee:

Standard: SGD$1180 Alumni: SGD$944 Group (3 & Above): SGD$1062

Registration fees inclusive of:

Course materials
Light refreshments
Lunch
Complimentary parking (1 entry/day) - applicable at NTU@one-north campus only.
Prevailing GST

Online Registration

>> CLICK HERE to Register Online

Methods of Payment

1. Credit Card (Visa and Mastercard only)

2. Cheque made payable to Nanyang Technological University

3. Invoice to Company (for Company Sponsored Participants)

4. E-invoice (for Government Organizations)

Cancellation & Refund Policy

Written notification to cce@ntu.edu.sg or fax: (+65) 6774 2911 at least 10 days before course commencement	No cancellation charges (Full refund)
Written notification within 4 – 9 days before course commencement	50% of course fees (50% refund)
Written notification within 3 days before course commencement	100% of course fees (No refund)