Reliability Modeling & Prediction (QIT112)

03 August 2017 - 04 August 2017

OBJECTIVES
This course consists of 2 parts.

Part I (Day #1):
This Part I instills awareness and expectation that customer satisfaction can be improved by understanding continuous improvement strategy. The participant will learn how to quantify variation, both analytically and graphically. The course will also teach the participant how to make comparisons and understand if there is any statistical difference in the analysis.
The main objective in this Part I is to ensure that engineers are able to make better analysis and decision making through the use of statistical tools & data-driven methodology
Upon completion of Part I, the participants will be able to:
• Consider the risk of sampling and impact to population by using confidence interval
• Perform data comparison by utilizing comparative method tools using Minitab
• Perform correlation between two continuous data

Part II (Day #2):
This Part II introduces the participant to the tools used & the flow of the tools in Reliability. Participants will be taught on how & when to use the Reliability tools to improve quality of product design during Product Development.
Upon completion of Part II, for a given product design, participants will be able to:
• Understand the big idea behind Reliability
• Understand when Reliability is used during Product Development
• Understand how Reliability is being measured.
• Select the methods & tools used for different Reliability data types.
• Manual Plotting of Reliability Data and Interpreting Reliability Plot
• Use Minitab to analyze Reliability data with Parametric and Nonparametric Methods.
• Understand what is SystemReliability (optional)
The theory, concepts and examples in Part I & II of this course are explained with every day analogies and using real world examples. The participants will get hands-on experience with a fun game and step-by-step examples using Minitab.

IMPORTANT
This course includes multiple hands-on activities that require the use of computers. Unless your class is scheduled in a Computer Lab, please plan to bring along your Laptop computer to this class with Minitab software version 16 installed.
Pre-requisite(s)
• Basic Statistics
• Basic knowledge in the use of Minitab statistical software

COURSE OUTLINE
Day #1
Course Introduction and Objective

MODULE 1: CONFIDENCE INTERVAL
• Population vs. sampling
• Importance of Confidence Interval in Sampling

MODULE 2: COMPARATIVE METHOD
• Introduction – Why do we need comparison?
• Comparison Flow Chart
• Practical Problem Statement
• Statistical Problem Statement
   o Hypothesis Testing
   o Analysis, Statistical and Practical Conclusion
   oType of Comparison
   o Side of Comparison
   o Hypothesis Testing – analysis
   o Type of error - α & β error
   o p-value
• Test for Assumption
• Independent test
   o Graphical & Analytical
• Normality Test
   o Graphical & Analytical
• Box-Cox Transformation
• X-Axis Discrete & Y-Axis Continuous – Mean Comparison
   o One-To-Standard (1-Sample T)
   o One-To-One (2-Sample T)
   o Multiple (Anova)
• X-Axis Discrete & Y-Axis Continuous – Variance Comparison
   o One-To-Standard (Confidence Interval)
   o One-To-One (F-Test)
   o Multiple (Bartlett/Levene Test)

MODULE 3: INTRODUCTION TO RELIABILITY & LIFE DATA ANALYSIS
• Objectives
• Introduction
• Why is Reliability in product development?

MODULE 4: RELIABILITY DEFINITION & CONCEPTS
• Objectives
• Concept & Definitions in Reliability
• Tools for Design for Reliability (DFR)
• Reliability functions & measures
• Commonly used distributions in Reliability
   o Weibull distributions
   o Exponential distribution
   o Normal distribution
   o Lognormal distribution

MODULE 5: WEIBULL ANALYSIS
• Objectives
• An Overview of Weibull Analysis
  o History & Background
  o Scope of Weibull Analysis
  o Advantages and Limitations of Weibull Analysis
  o Complete Data vs. Dirty Data
• Manual Plotting Reliability Data & Interpreting Weibull Plot
  o Eta vs. Beta
  o Bathtub Curves
  o Median Rank Regression & Adjusted Rank Methodyears ew part
  o Median Rank Regression (MRR) vs. Maximum Likelihood Estimation (MLE)

Day #2
MODULE 6: PARAMETRIC & NON-PARAMETRIC RELIABILITY ANALYSIS
• Class Exercise on How to Collect Reliability Data
• Class Exercises of Reliability Analysis using Minitab
   o Complete vs. Censored data
   o Parametric (Weibull ) vs. Non-parametric methods (Kaplan Mier)
   o Comparing multiple groups, designs & products for Reliability
   o Comparing multiple failures modes for complete & censored data

MODULE 7: OTHER METHODS IN RELIABILITY ANALYSIS`
• Weibayes Analysis
  o Weibayes With Failures
  o Weibayes Without Failures
  o Weibayes Limitation & Concerns
• Probit Method Analysis
  o Probit vs. Point to Point Analysis
  o Data Format
• Warranty Analysis
  o Warranty Data Martix
  o Warranty Data Rules

MODULE 8: ACCELERATED LIFE TESTING
• Objectives
• Accelerated Life Testing-Overview
• Types of Accelerated Life Testing
• Class Demo: Insulation Failure

WHO SHOULD ATTEND
This course is intended for Design Engineers, R&D Engineers, Subject Matter Experts (SME), QA, Service and Engineering personals who are directly or indirectly involved in Product Development or Product Design and require some basic understand in Reliability Analysis.

METHODOLOGY
Workshop shall be delivered via lectures, discussions, demonstrations, and hands-on exercises. Course shall lean towards practical application aspects rather than theoretical. Participants are required to pre-install their laptops with Minitab v16.

DURATION
2 days @ 9am – 5pm

COURSE FEE
PSDC Member: RM 740
Non-Member:   RM 810
*All prices listed above are subjected to GST effective 1st April 2015

HRDF
SBL Scheme