Syllabus
Syllabus
Suggested lab exercises:
The experiments may be performed using Excel / R / Python / Minitab or equivalent statistical software.
- Control Charts for Variables: Construct ??? and R charts for a sample dataset. Compute control limits and plot charts, Identify out-of-control points and interpret causes
- Control Charts for Attributes: Construct p and c charts for defect data. Compute control limits and detect trends.Compare variable vs attribute control charts.
- Process Capability Analysis: Evaluate process capability using Cp and Cpk. Analyze dataset for specification limits. Plot histogram and interpret process capability.
- Acceptance Sampling: Apply single or double sampling plans. Compute OC, AOQ, ASN, and ATI curves. Compare efficiency of different sampling plans
- Taguchi Methods (Robust Design): Apply orthogonal array design for process optimization. Select 2–3 factors, compute S/N ratios.Identify optimal settings for minimal variation.
Unit 1
Introduction to quality and quality control Evolution of quality management (Inspection, Quality Control, Quality Assurance, Total Quality Management) Japanese system of Total Quality Management Quality Circles Seven basic Quality Control tools Plan-do-check-act (PDCA) cycle for project implementation
Unit 2
Basic concept of quality control, process control and product control -Process and measurement system capability analysis – Area properties of Normal distribution. Statistical process control, theory of control charts, Shewhart control charts for variables-x ?, R, s charts, attribute control charts – p, np, c, u charts, modified control charts, ARL of control charts.
Unit 3
Moving average control charts, EWMA charts, CUSUM charts two sided and one-sided procedures V mask technique, process capability analysis, process capability indices, Metrics of Six Sigma, The DMAIC cycle – Overview of Design for Six Sigma – Lean Sigma Statistical tools for Six Sigma.
Unit 4
Acceptance sampling for attributes, single sampling, double sampling, normal ang tightened inspection plans, measuring performance of the sampling plans- OC, AOQ, ASN, ATI curves.
Unit 5
Taguchi methods: Meaning of Quality, Taguchis loss function, Introduction to orthogonal arrays test strategies, steps in designing, conducting and analyzing an experiment, parameter and tolerance design: control and noise factors, signal to noise ratios, experimental design in Taguchi Methods with applications.
Text Books / References
Text Books:
- Montgomery Douglas C., Introduction to Statistical Quality Control, Sixth Edition. John Wiley & Sons, (2008).
- Ishikawa K, Guide to Quality Control, 2nd Edition: Asian Productivity Organization, Tokyo (1983).
- Ravichandran.J, Probability and Statistics for Engineers, 1st Edition 2012 (Reprint), Wiley India.
- Harry, M and Schroeder, Six Sigma: The Breakthrough Management Strategy. Currency Publishers, USA. (2000)
- Taguchi G, Introduction to Quality Engineering: Designing Quality into Products and Processes, Asian Productivity Organization, Second Edition. (1991).
Introduction
This course provides a foundational understanding of Statistical Process Control (SPC) techniques used to monitor, control, and improve quality in processes and products. Emphasis is placed on Total Quality Management principles, statistical process control, control charts, process capability analysis, acceptance sampling, Six Sigma fundamentals, and Taguchi methods. The course enables students to apply statistical tools for quality improvement in manufacturing and service environments.
Objectives and Outcomes
Course Outcomes: After successful completion of the course, students will be able to
- CO1. Analyze and explain the principles of Total Quality Management and quality improvement philosophies.
- CO2. Apply statistical process control techniques using control charts to monitor process performance.
- CO3. Evaluate process capability and interpret advanced control charts for quality improvement.
- CO4. Design and assess acceptance sampling plans using standard performance measures.
- CO5. Design and optimize processes using Taguchi methods and Six Sigma concepts for robust product and process design.
CO-PO Mapping:
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