Comprehensive Chapter-wise Syllabus for Statistical Process Control : A Step-by-Step Guide

Here’s a comprehensive chapter-wise syllabus for your book Statistical Process Control: A Step-by-Step Guide tailored to UG/PG Engineering, Diploma, AICTE/UGC curriculum standards, and competitive exams (e.g., GATE, AMIE, quality-engineer certification).

This structure reflects topics commonly taught in real SPC courses and quality control modules across academia and industry training programs. 


📘 Part I — Fundamentals of SPC (UG & PG Core)

Chapter 1: Introduction to Statistical Process Control

  • Definition and purpose of SPC

  • Historical evolution (Shewhart, Deming)

  • SPC within Quality Management Systems

  • Applications in manufacturing and services

Competency focus: Understand why SPC matters in quality engineering and process stability.


Chapter 2: Basic Statistical Concepts for SPC

  • Types of data (attribute vs. variable)

  • Descriptive statistics: mean, median, mode, variance, standard deviation

  • Probability distributions (Normal, Binomial, Poisson)

  • Central Limit Theorem & its role in SPC

Competency focus: Build the statistical foundation needed for control charts and capability analysis. (Udemy)


📊 Part II — Control Charts (UG/PG & Diploma)

Chapter 3: Variation in Processes

  • Common-cause vs. special-cause variation

  • Process behavior over time

  • Rational subgrouping

Competency focus: Distinguish types of variation and prepare for control chart selection. (svc.ac.in)


Chapter 4: Control Charts for Variables

  • X̄ & R charts

  • X̄ & S charts

  • I-MR (Individuals/Mobile Range) charts

  • Calculating control limits

  • Interpretation & signals of out-of-control

Competency focus: Construct, interpret, and diagnose variable data charts. (pdacek.ac.in)


Chapter 5: Control Charts for Attributes

  • p-chart (proportion defective)

  • np-chart (number defective)

  • c-chart (count of defects)

  • u-chart (defects per unit)

  • When to choose which attribute chart

Competency focus: Monitor categorical defects and nonconformities. (svc.ac.in)


Chapter 6: Control Chart Rules & Special Techniques

  • Western Electric & Nelson rules for detecting patterns

  • Handling special cases/slow trends

  • Practical interpretation pitfalls

Competency focus: Identify pattern signals beyond simple limits.


📈 Part III — Process Capability & Performance

Chapter 7: Process Stability vs Capability

  • Difference between being “in control” and being “capable”

  • Specification limits vs control limits

  • Cp, Cpk, Pp, Ppk indices

Competency focus: Evaluate how well a process meets tolerances and customer expectations. (Udemy)


Chapter 8: Capability Analysis with Non-Normal Data

  • Handling skewed and non-normal distributions

  • Alternative approaches (percentiles, transformation methods)

Competency focus: Extend capability concepts beyond normal assumptions.


🧰 Part IV — Practical Tools & Implementation

Chapter 9: Data Collection & Sampling

  • Sampling plans

  • Subgroup selection rules

  • Ensuring data quality

Competency focus: Collect meaningful data for control analyses. (igmguru)


Chapter 10: Measurement System Analysis (MSA)

  • Gage R&R studies

  • Repeatability and reproducibility

  • Attribute agreement analysis

Competency focus: Validate measurement systems before SPC application. (Miq)


Chapter 11: SPC Implementation in Practice

  • Setting up SPC in industry

  • Control plans

  • Reaction plans and corrective action

Competency focus: Apply SPC in real production/service environments. (Lean6SigmaPro)


🧠 Part V — Advanced & Competitive Exam Topics

Chapter 12: Advanced Charts & Techniques

  • EWMA and CUSUM charts

  • Short-run SPC

  • Multivariate SPC basics

Competency focus: Prepare learners for advanced industry standards and higher-level exams.


Chapter 13: Case Studies & Problem Sets

  • Manufacturing case studies (defects, stability)

  • Service sector applications

  • Competitive exam style questions (GATE/PG diploma/QE)

Competency focus: Reinforce learning with real examples and exam practice.


Alignment with AICTE/UGC & Diploma Standards

This syllabus aligns with typical course modules in quality and industrial engineering:

  • Control charts and variation analysis appear in UG curricula for mechanical/industrial engineering. (pdacek.ac.in)

  • Process capability and SPC fundamentals are core in PG quality management and Six Sigma specialization courses. (Udemy)

  • Data collection, sampling, and measurement system topics support practical skills required in diploma and industry certification programs. (igmguru)


🏆 Competitive Exam Preparation Tips

Include practice questions on:

  • Construction of X̄-R and p charts

  • Calculation of control limits and capability indices

  • Selection of control charts based on data type

  • Interpretation of out-of-control signals

  • Common cause vs special cause scenarios

This structure enhances readiness for exams like GATE, AMIE, QE certification, and Six Sigma belts.


If you want, I can now generate sample questions with answers, chapter objectives, or exam revision notes tailored to this syllabus. Just tell me which one you’d like next.

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