Design for Six SIGMA Statistics: 59 Tools for Diagnosing and Solving Problems in Dfss Initiatives: 59 Tools for Diagnosing And Solving Problems in Dffs Initiatives - Hardcover

Über die Autorin bzw. den Autor

Andrew Sleeper is a DFSS expert and General Manager of Successful Statistics, LLC. He has worked with product development teams for 22 years as an engineer, statistician, project manager, Six Sigma Black Belt, and consultant. Mr. Sleeper holds degrees in electrical engineering and statistics, and is a licensed Professional Engineer. A senior member of the American Society for Quality, he is certified by ASQ as a Quality Manager, Reliability Engineer, and Quality Engineer, and has provided over 1,000 hours of instruction in countries around the world. His client list includes Anheuser-Busch, Intier Automotive Seating, New Belgium Brewing Company, and Ingersoll-Rand.

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THE STATISTICAL TOOL NECESSARY TO IDENTIFY AND SOLVE ANY DFSS PROBLEM

Design for Six Sigma Statistics meticulously details 59 mathematical procedures for executing DFSS programs, isolating and identifying problems, and solving them before the actual product launch. More than an introduction to statistical concepts and methods, this comprehensive resource offers real-world case studies and step-by-step MINTAB instruction for performing:

• DFSS Design of Experiments
• Measuring Process Capability
• Statistical Tolerancing in DFSS
• DFSS Techniques within the supply chain

THE STATISTICAL TOOLS YOU NEED TO MAXIMIZE DFSS:
The Design for Six Sigma Process * Defining Product Requirements * Making Decisions with Data * Conducting Efficient Experiments * Predicting New Product Quality * Controlling New Product Quality

Survival in today's competitive environment demands goods and services that truly approximate perfection -- which means pinpointing and solving problems before a product launches. Written by a Six Sigma practitioner with more than two decades of DFSS experience, Design for Six Sigma Statistics provides a detailed, goal-focused roadmap.

Design for Six Sigma Statistics shows quality professionals how to execute advanced mathematical procedures specifically aimed at implementing, fine-tuning, or maximizing DFSS projects to yield optimal results.

For virtually every instance and situation, readers are shown how to select and use appropriate mathematical methods to meet the challenges of today's engineering design for quality. The author covers mathematical tools for planning, interpreting, measuring, correcting, and anticipating product performance and manufacturing parameters. Examples, equations, and MINTAB screen shots facilitate progress through every step toward efficient, effective, and measurable results. In one comprehensive resource, readers will have the formulas they need to fully understand:

• Robust Engineering Concepts
• Failure Mode and Effects Analysis
• Gap Analysis: Audits and Metrics
• Design of Experiments

With Andrew Sleeper's Design for Six Sigma Statistics, quality professionals will have the highly specialized, problem-solving mathematical procedures necessary to create products and services that can compete and succeed in today's marketplace.