This book is a valuable reference text that systematically outlines the DMAIC approach to advanced tools for implementing Six Sigma projects in industry. The authors begin by providing an introduction to, or ‘definition’ of Six Sigma. The following section on ‘Measure’, begins with a description of this phase, ending with a comparative study of computing processes and capability indices for non-normal data. In the next phase entitled ‘Analyse’, the authors debate various tests for normality, proportions, and goodness-of-fit, and examine graphical approaches and data transformation for geometrically distributed quality characteristics. The following phase analyses ways of gaining improved quality in experiments, such as factorial, fractional and robust designs, and Taguchi methods. The last phase, ‘Control’, charts tools to maintain quality and reliability in systems. Statistical process control in autocorrelated systems is discussed, along with simultaneous monitoring of sample and group autocorrelations.