Statistical and Managerial Techniques for Six Sigma Methodology [Elektronisk resurs] Theory and Application.

• Statistical and Managerial Techniques for Six Sigma Methodology; Contents; Preface; About the Authors; 1 Six Sigma methodology; 1.1 Management by process; 1.1.1 The concept of 'process'; 1.1.2 Managing by process; 1.1.3 The process performance triangle; 1.1.4 Customer satisfaction; 1.1.5 The success of enterprise; 1.1.6 Innovation and Six Sigma; 1.2 Meanings and origins of Six Sigma; 1.2.1 Variation in products and processes; 1.2.2 Meaning of 'Six Sigma'; 1.2.3 Six Sigma process; 1.2.4 Origins of Six Sigma; 1.2.5 Six Sigma: Some definitions; 1.3 Six Sigma projects. 
• 1.3.1 Why implement Six Sigma projects?1.3.2 Six Sigma paths; 1.4 The DMARIC path; 1.4.1 Human resources and training; References; 2 Basic managerial techniques; 2.1 For brainstorming; 2.1.1 Cause-effect diagram; 2.1.2 Affinity diagram (KJ analysis); 2.2 To manage the project; 2.2.1 Work breakdown structure; 2.2.2 Gantt chart; 2.3 To describe and understand the processes; 2.3.1 The SIPOC scheme; 2.3.2 The flow chart; 2.3.3 The ServQual model; 2.4 To direct the improvement; 2.4.1 The Kano model; References; 3 Basic statistical techniques; 3.1 To explore data. 
• 3.1.1 Fundamental concepts and phases of the exploratory data analysis3.1.2 Empirical frequency distribution of a numerical variable; 3.1.3 Analysis by stratification; 3.1.4 Other graphical representations; 3.2 To define and calculate the uncertainty; 3.2.1 Definitions of probability; 3.2.2 Events and probabilities in the Venn diagram; 3.2.3 Probability calculation rules; 3.2.4 Dispositions, permutations and combinations; 3.3 To model the random variability; 3.3.1 Definition of random variable; 3.3.2 Probability distribution function. 
• 3.3.3 Probability mass function for discrete random variables3.3.4 Probability density function for continuous variables; 3.3.5 Mean and variance of a random variable; 3.3.6 Principal models of random variables; 3.4 To draw conclusions from observed data; 3.4.1 The inferential process; 3.4.2 Sampling and samples; 3.4.3 Adopting a probability distribution model by graphical analysis of the sample (probability plot); 3.4.4 Point estimation of the parameters of a Gaussian population; 3.4.5 Interval estimation; 3.4.6 Hypothesis testing; References; 4 Advanced managerial techniques. 
• 4.1 To describe processes4.1.1 IDEF0; 4.2 To manage a project; 4.2.1 Project evaluation and review technique; 4.2.2 Critical path method; 4.3 To analyse faults; 4.3.1 Failure mode and effect analysis; 4.3.2 Fault tree analysis; 4.4 To make decisions; 4.4.1 Analytic hierarchy process; 4.4.2 Response latency model; 4.4.3 Quality function deployment; References; 5 Advanced statistical techniques; 5.1 To study the relationships between variables; 5.1.1 Linear regression analysis; 5.1.2 Logistic regression models; 5.1.3 Introduction to multivariate statistics. 
• 5.2 To monitor and keep processes under control. 

• Statistical and Managerial Techniques for Six Sigma Methodology examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be analyzed, allowing the reader to apply these tools in the field. This book offers an insight on variation and risk management, and focuses on the structure and organizational aspects of the Six Sigma projects. It covers six sigma methodology, basic managerial techniques, basic statistical techniques, methods for variation and risk management and advanc 

Ämnesord

Management. 

Quality control -- Management. 

Six sigma (Quality control standard). 

Total quality management. 

Genre

Electronic books.  (LCSH)

Klassifikation

HD62.15 .B367 2012 (LCC)

658.4013 (DDC)

Qbab (kssb/8 (machine generated))