Lean Six Sigma Using SigmaXL and Minitab e-bog
278,81 DKK
(ekskl. moms 223,05 DKK)
Effectively Execute Lean Six Sigma Projects using SigmaXL and MinitabWritten by a Six Sigma Master Black Belt and a Ph.D., this practical guide to Lean Six Sigma project execution follows the DMAIC (Define, Measure, Analyze, Improve, and Control) roadmap. The many real-world examples used in the book offer in-depth theoretical analyses and are implemented using the two most popular statistical so…
E-bog
278,81 DKK
Forlag
McGraw Hill
Udgivet
2009-01-05
Længde
408 sider
Genrer
Quality Assurance (QA) and Total Quality Management (TQM)
Sprog
English
Format
epub
Beskyttelse
LCP
ISBN
9780071626217
Effectively Execute Lean Six Sigma Projects using SigmaXL and MinitabWritten by a Six Sigma Master Black Belt and a Ph.D., this practical guide to Lean Six Sigma project execution follows the DMAIC (Define, Measure, Analyze, Improve, and Control) roadmap. The many real-world examples used in the book offer in-depth theoretical analyses and are implemented using the two most popular statistical software suites--SigmaXL and Minitab. This expert resource covers Lean topics ranging from basic data analysis to complex design of experiments and statistical process control. Harness the power of SigmaXL and Minitab and enable sustained positive operational results throughout your organization with help from this authoritative guide.Lean Six Sigma Using SigmaXL and Minitab explains how to:Define the project goals, project manager, value statement, stakeholders, and riskSchedule tasks using the Gantt chart, critical path analysis, and program evaluation and review techniqueCapture the voice of internal and external customersAssess the cost of qualityGather data and measure process performancePerform process capabilities analysisApply Lean Six Sigma metrics to determine baseline performanceImplement analysis techniques such as Pareto analysis, value stream mapping, failure mode and effect analysis (FMEA), and regression analysisIdentify constraints via factorial experiments, and implement process improvementsMonitor production performance using statistical process control
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