Module 1 (6 hours) : Statistical Methods: Important statistical distribution and their properties, correlation and regression, multiple regression analysis.
Statistical Inference: t-tests, F-tests, Chi-square tests, ANOVA,

Module 2 (6 hours) : Quality Engineering: On-line quality control using Control Charts, Off-line Quality Control using Design of Experiments and Response Surface Methodology Approaches.

Module 3 (6 hours) : Importance of parameter design. Experimental design principles for product and process design, Two-level and three-level experimental for full factorial and fractional factorial design. Taguchi's Loss Function. S/N ratio. Inner and outer Arrays, Experimental design for control and noise factors. ANOVA in Engineering design, Computer software in experimental design.

Module 4 (9 hours) : Components of TQM, PDCA cycle, TQM implementation. Quality costs, Ishikawa diagram, brain storming, QFD, JIT philosophy and techniques. Characteristics features and clauses of ISO 9000 standards, Certification procedures, quality audit procedure, and implementation procedures.

Module 5 (3 hours) : Reliability: System effectiveness, mission reliability, design adequacy, operational readiness, serviceability, performance indices and their evaluation, uses and limitations.

Module 6 (6 hours) : Reliability models of maintained systems, fundamental definitions, relationship between reliability and maintainability. Single equipment systems, parallel, stand by, K-out-of n-configuration, steady state availability. Maintainability predication. Inspection policies bases on profits, downtime and performance degradation. Inspection under emergency condition.

To gain knowledge on planned way of conducting experiments using statistical design of experiment approach

To impart knowledge on online and offline quality control

To familiarize with the concept of TQM and TPM and international standards for assurance of quality

To design the products/processes conforming to desired reliability, availability and maintainability
Objective 5:
To enhance six-sigma drive in manufacturing/service sectors

Introduction to statistical methods for quality improvement
Knowledge will be gained on online and off-line quality control practiced in industries.
Develop the ability to apply the statistical theories during product development for producing conforming to quality and reliability standards .
Knowledge will be enhanced to implement the best practices to develop quality culture in real situations.
Application of software for analysis of quality programs

D.C. Montgomery, Design and Analysis of Experiments, John Wiley & Sons , Eighth Edition

M.S.Phadke, Quality Engineering Using Robust Design, Prentice Hall , First Edition

S S. Singh, Total Quality Control Essentials, McGraw Hill , First Edition

L.S. Srinath, Reliability Engineering, EWP , First Edition

Journal: Quality Engineering Taylor and Francis

Conference: International Conference on Quality Engineering and Management (ICQEM)