# QUALITY ENGINEERING

**Academic Year 2020/2021**- 2° Year

**Teaching Staff:**

**Giovanni CELANO**

**Credit Value:**9

**Scientific field:**ING-IND/16 - Manufacturing technology and systems

**Taught classes:**42 hours

**Exercise:**45 hours

**Term / Semester:**2°

## Learning Objectives

At the end of the course the students should be able:

- to know the main quality principles and definitions;
- to join a quality assurance team implementing the ISO 9000 standards;
- to implement a process improvement project according to DMAIC metholodogy and Six Sigma principles;
- to perform a preliminary data analysis aimed at identifying quality issues in manufacturing/service processes;
- to implement statistical process monitoring tools;
- to perform process and measurement system capability analysis;
- to use the Minitab® software quality tools.

## Course Structure

Learning is based on theory classes and practice sessions. Practice sessions are scheduled once per week and consist of solving numerical problems/case studies.

## Detailed Course Content

1. QUALITY IMPROVEMENT IN MODERN BUSINESS ENVIRONMENT (Week #1)

The Meaning of Quality and its Dimensions. Quality Improvement (QI). Quality Engineering Terminology: Quality Characteristics (CTQs). A Brief History of Quality Control and Improvement (QCI)*. Statistical Methods for QCI. Management Aspects of Quality Improvement: Quality Planning, Quality Assurance, Quality Control and Improvement. PDCA cycle. The Link between Quality and Productivity: first-time yield (FTY), first-pass yield (FPY). Supply Chain Quality Management*, Quality Costs*.

2. QUALITY PHILOSOPHIES AND MANAGEMENT STRATEGIES (Week #1)

ISO 9000 quality standards and their evolution, certification and accreditation, Audits, ISO 9000 and 9001 ver. 2015. Fundamental Concepts, Structure, Context of the Organization, Quality policy and objectives, Risk-based thinking. Maintaining and retaining documented information. Nonconforming and defective products: rework, repair, scrap. The Six Sigma Philosophy: Meaning of Six Sigma, The Six Sigma Roles, The DMAIC Process Steps. DFSS, Lean principles and Six Sigma. Case Studies*.

3. STATISTICAL MODELS FOR QCI (Week #2)

Describing variation and data: Histogram, Box Plot and Dot Plot. Discrete distributions: Hypergeometric, Binomial, Poisson Distributions. Continuous distributions: Normal, Lognormal, Exponential Distributions. Probability Plots. The Anderson Darling test. The Normal Approximation to the Binomial.

4. STATISTICAL INFERENCE IN QCI (Weeks #3-#5)

Statistics and Sampling Distributions. Sampling from a Normal, Binomial and Poisson Distribution. Point Estimation of Process Parameters. Statistical Inference for a Single Sample. Inference on the Mean of a Normal Distribution, (z-test and t-test), Confidence Intervals. The p-value approach. Inference on the Variance of a Normal Distribution, (chi2-test). Inference on a Population Proportion and Confidence Interval. The OC curve for the z-test: Choice of the Sample Size. Statistical Inference for Two Samples. Inference for a Difference in Means, (z-test and t-test), Confidence Intervals. Inference on the Variances of a Normal Distribution, (F-test), Confidence Interval. Comparing two populations. Inference on Two Population Proportions and Confidence Interval. Inference on More Than Two Populations: Analysis of Variance (ANOVA). Multiple comparison tests: LSD and Tukey test. Inference on more than two population proportions. Contingency tables.

5. HOW STATISTICAL PROCESS CONTROL WORKS (Week #6-#8)

Introduction. Chance and Assignable Causes. Statistical Basis of the Control Chart. Choice of Control Limits. Sample Size and Sampling Frequency. The Run Length of a control chart. Rational Subgroups. Analysis of Patterns. Adding Sensitizing Rules to Control Charts. Phase I and II Implementation of Control Charts. The Rest of Magnificent Seven: Pareto Chart, Cause and Effect Diagram. Applications of SPC (reading).

6. VARIABLES AND ATTRIBUTES CONTROL CHARTS (Weeks #9-#10)

Introduction. Control Charts for Xbar and R. The operating characteristic curve. Computation of the performance for the Xbar control chart5. Control Charts for Xbar and s: Construction and Operation of Xbar and s Charts; the Xbar and s Control Charts with Variable Sample Size. The s^2 control chart. The Shewhart Control Chart for Individual Measurements. Shewhart Control Charts for Attributes. Control Charts for Fraction Nonconforming (p Charts). Selection of the sample size for a p control chart. Control Charts for number of nonconforming (np Charts). Control Charts for Nonconformities (only c Charts). Procedures with variable sample size.

7. CAPABILITY ANALYSIS OF PROCESS AND MEASUREMENT SYSTEMS (Weeks #11-#12)

Introduction. Process Capability Ratios: Cp, Cpk, Cpm. Process Capability Analysis with Control Charts. Confidence intervals (only Cp) and tests on process capability ratios*. Short term and long term variability. Measurement system analysis: reference value and resolution; location variation: bias, linearity, stability, testing for location variation; width variation: precision error, repeatability, reproducibility, testing for width variation, Gauge R and R study: Xbar and R method with Excel. Part variation, Total variation. Gauge R and R Analysis with Minitab.

*The topic is suggested for reading, but it is not included in the exam text.

## Textbook Information

**1. D.C. Montgomery, “Statistical Quality Control”, 6 ^{th} edn or successive, Wiley. MAIN TEXT. The most widely used textbook about SQC in Universities teaching courses on Quality Engineering and in Companies implementing SQC tools.**

2. C. Cochran, “ISO 9001: 2015 in plain English”, 2015, Paton Professional, ISBN: 978-1-932828-72-6. *A recent guide to the implementation of the new ISO 9000: 2015.*

3. K. Magnusson, D. Kroslid, B. Bergman, 2003, “Six Sigma: The Pragmatic Approach, Studentilitteratur, Sweden, ISBN: 9-789-144-028033. *A professional text presenting the Six Sigma approach.*

4. Q. Brook, “Lean Six Sigma & Minitab”, 4^{th} edn., 2014, OPEX Resources Ltd, ISBN-13: 978-0954681388. *A very good text for professional use of Minitab in a lean Six Sigma context.*