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Useful for ISS

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  1. Welcome
  2. Course Outcomes
  3. Units in this Course
  4. Recommended Textbooks

Welcome

This is the complete study package for Statistical Quality Control (SQC) — five interconnected topics that equip you with the statistical tools used in modern industry to monitor and maintain quality: fundamentals of SQC and causes of variation, control charts for variables, control charts for attributes, acceptance sampling plans, and single sampling plan computations. Each concept has two worked examples.

Pre-requisite: Statistical Methods — especially measures of central tendency, dispersion, and probability distributions. Inferential Statistics for hypothesis testing concepts and normal/binomial/Poisson distributions.

Course Outcomes

  1. Define 'quality' in a scientific way and understand the philosophy of SQC.
  2. Differentiate between process control and product control.
  3. Construct and interpret control charts for variables (Mean, Range, S.D.) and attributes (p, np, c, u).
  4. Understand acceptance sampling plans, OC curves, AQL, LTPD, AOQ, AOQL, ASN, and ATI.
  5. Compute and design single sampling plans using lot-quality and average-quality approaches.

Units in this Course

UNIT 1

Introduction to SQC

Importance of SQC, 4 M's, causes of variation (assignable and chance), process control vs product control, Shewhart control chart basics.

 UNIT 2

Control Charts for Variables

Construction of Mean (\(\bar{X}\)) and Range (R) charts; Mean and Standard Deviation (S) charts — with and without specified standards.

 UNIT 3

Control Charts for Attributes

Construction of p-chart, np-chart, c-chart and u-chart — with and without specified standards.

 UNIT 4

Acceptance Sampling for Attributes

Sampling inspection, producer's and consumer's risk, OC curve, AQL, LTPD, AOQ, AOQL, ASN, ATI.

 UNIT 5

Single Sampling Plan

Probability of acceptance using Binomial and Poisson, computation of AOQ and ATI, graphical AOQL, lot-quality and average-quality approaches.

 PRACTICAL

Practical Course (9 Experiments)

Construction of \(\bar{X}\)-R, \(\bar{X}\)-S, p, np, c, u charts; single sampling plan computations.

 REFERENCE

Official Syllabus

Course outline, textbooks, references and exam blueprint.
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Next course in learning order: Operations Research Applied statistics