Six Sigma

The purpose of this book is to show how, using the principles of Six Sigma, you can exploit data to make better decisions more quickly and easily than you would otherwise. To deliver products that consistently meet customers’ expectations, it is necessary to develop a process of transforming customers’ wants into designs that are useful to the customer. Product design is a process that identifies products’ purposes and functions and then allocates them to a structural or concrete form. To shorten product development time and save cost, product teams would be able to evaluate and determine the form of that product at the same time as creating methods for achieving those purposes. The ability to evaluate conformance of potential designs to design specifications prior to hardware builds can shorten the development cycle and save cost. The iterative process of design–build–test–fix is simply too slow and costly. In order to achieve on-target design right the first time, Design for Six Sigma has been developed to complement the product development process. It typically consists of a set of voice of customer interpretation tools and engineering and statistical methods to be used during product development. The main objective of Design for Six Sigma is to “design it right the first time” by identifying product features and functions that the customer can recognize as being beneficial and to ensure that the design can consistently deliver exceptional performance.

Shawnna Barham has received Ph.D. in Economics from Business University, Gothenburg. She is a Programme Coordinator and Business Expert at Public University, Punkalaidun. She consistently shares her knowledge with the researcher fraternity by organizing lectures and conferences around the globe. Barham has contributed dozens of articles, research papers, and journals about DMAIC and other improvement modelsproblem solving tools, principles of measurement, measurement systems analysis, statistical process control techniques, managing six sigma projects and design for six sigma (DFSS). She provides real meaning to the use of statistics in real world by using real business situations and real data.

Preface IX
1. Introduction to DMAIC and Other Improvement Models 1
Introduction 1
Certification 2
Difference from lean management 3
Dmaic, Dmadv and learning models 5
2. Problem Solving Tools 15
Introduction 15
Process mapping 16
Check sheets 26
Pareto analysis 30
Cause and effect diagrams 31
7M tools 34
3. Basic Principles of Measurement 64
Introduction 64
Scales of measurement 64
Reliability and validity of data 66
Overview of statistical methods 69
Hypergeometric 81
Principles of statistical process control 88
Objectives and benefits 92
4. Measurement Systems Analysis 96
Introduction 96
Factors affecting a measurement process 97
R&R studies for continuous data 98
Attribute measurement error analysis 119
Operational definitions 122
Example of attribute inspection error analysis 123
Repeatability and Pairwise Reproducibility 125
Minitab attribute gage R&R example 127
5. Knowledge Discovery 133
Introduction 133
Knowledge Discovery Tools 134
Establishing the process baseline 162
Sipoc 165
6. Statistical Process Control Techniques 170
Introduction 170
Statistical process control 170
7. Process Capability Analysis 195
Introduction 195
Process Capability Analysis: Definition (CPCA) 196
Estimating process yield 210
8. Statistical Analysis of Cause and Effect 218
Introduction 218
Testing Common Assumptions 219
Regression and Correlation Analysis 224
Analysis of Categorial Data 229
Non Parametric Methods 232
9. Managing Six Sigma Projects 235
Introduction 235
Useful project management tools & techniques 235
Project charter 239
Work breakdown structure 242
Feedback loops 245
Performance measures 247
Cost consideration in Project Scheduling 254
Project Management Implementation 256
10. Risk Assessment 266
Introduction 266
Individual risk assessment 267
Reliability and Safety Analysis 267
Failure mode and effect analysis 271
Statistical tolerancing 275
11. Design of Experiments (DOE) 278
Introduction 278
Terminology 278
Power and Sample Size 279
Design characterstics 282
Types of design 284
One factor 285
Example of applying common DOE methods using software 286
Two way Anova with replication 290
Two way Anova Without replication 290
12. Maintaining Control After the Project 292
Introduction 292
Business process Control Planning 292
Tools and techniques useful for control planning 294
Using spc for ongoing control 295
Process control planning for short and small runs 296
Strategies for short and small runs 296
Preparing the short run process control plan (pcp) 297
Pre-control 299
13. Design for Six Sigma (DFSS) 301
Introduction 301
Preliminary steps 301
Define 302
Identify CTQ 302
Measure 304
Analyze 306
Design 309
Pilot run 311
14. Lean Manufacturing and Six Sigma 314
Introduction 314
Introduction to lean and muda 315
What is value to the customers? 317
What is value stream? 318
How do we make value flow? 319
How do we make value flow at the pull of the customer? 321
How can we continue towards perfection? 323
Becoming Lean : A tactical Perspective 326
Six Sigma and Lean 327
Bibliography 330
Index 332

Six Sigma: Basic Tools And Techniques