This text meets the urgent need for a clear, concise introduction to the principles of statistical process control (SPC). The coverage has been deliberately restricted to the essential elements of SPC and the treatment of the subject is direct, practical and well organized. Nothing more than a very basic knowledge of statistics is assumed, making the book accessible to all those involved in quality control from technician level upwards. The book is up-to-date and designed to introduce students and practitioners to the basic concepts of SPC and the main mathematical techniques involved. This book should be of interest to senior undergraduate/graduate production engineer and quality professionals.
1 General questions and concepts.- 1.1 Introduction.- 1.2 Why quality?.- 1.3 What is total quality?.- 2 Reliability in the choice of technology.- 2.1 Quantitative analysis.- 2.2 Qualitative analysis.- 3 Controlling the manufacturing process.- 3.1 Variability in manufactured products.- 3.2 Monitoring the manufacture.- 3.3 Interval between control actions.- 4 Quality control of goods received.- 4.1 Control by attributes.- 4.2 Sequential testing.- 4.3 Control by measured properties.- 4.4 Sampling procedures.- 5 Cause-and-effect analysis.- 5.1 The Ishikawa cause—effect diagram.- 5.2 Pareto or ABC analysis.- 5.3 Rank correlation: Spearman’s coefficient.- 5.4 Analysis of variance.- 5.5 Experimental designs of type 2n.- 6 Basic mathematics.- 6.1 Probability: theory, definitions.- 6.2 Probability laws.- 6.3 Confidence interval for the mean.- 6.4 Linear regression.- Exercises.- Solutions.- Appendices (Tables).- 1. Gaussian (normal) distribution.- 4. The F (Fisher-Snedecor) distribution.- 5. MTBF for a system following the Weibull law.- 6. Median ranks (Johnson’s table).- 7. Laplace transforms.- 8. Random numbers.- 9. Gamma law.
... could become standard reading for most practising engineers in a design production environment and all students of quality. Ray Mellet, Quality News