In today’s competitive environment, companies can no longer produce goods and services that are merely good with low defect levels, they have to be near-perfect. Design for Six Sigma Statistics is a rigorous mathematical roadmap to help companies reach this goal. As the sixth book in the Six Sigma operations series, this comprehensive book goes beyond an introduction to the statistical tools and methods found in most books but contains expert case studies, equations and step by step MINTAB instruction for performing: DFSS Design of Experiments, Measuring Process Capability, Statistical Tolerancing in DFSS and DFSS Techniques within the Supply Chain for Improved Results. The aim is to help you better diagnosis and root out potential problems before your product or service is even launched.
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.
