1 / 25

Recent Advances and Future Directions for Quality Engineering

Recent Advances and Future Directions for Quality Engineering. Geoff Vining Virginia Tech USA. Outline. Recent Advances Extending Standard Methodologies to Hard, Practical Problems “Statistical Thinking” Applications in Areas Other than Manufacturing

Download Presentation

Recent Advances and Future Directions for Quality Engineering

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Recent Advances and Future Directions for Quality Engineering Geoff Vining Virginia Tech USA

  2. Outline • Recent Advances • Extending Standard Methodologies to Hard, Practical Problems • “Statistical Thinking” • Applications in Areas Other than Manufacturing • Advances in Software (However, Need Caution) • Truly Global Reach

  3. Outline • Future Directions • Integrating Quality Engineering Concepts over Complex Systems • Large Data Sets • Dealing with Image Data • Greater Emphasis on Reliability • Innovation • Strong Need to Train Practitioners Properly (Dangers of Current Software!) • Statistical Engineering

  4. Background • Past Department Head of Statistics at Virginia Tech • Past Editor of the Journal of Quality Technology (1998-2000) • Past Editor of Quality Engineering (2009-2010) • Past Chair of the ASQ Publications Management Board • Member of the ASQ Board of Directors

  5. Background - Journals • Quality Engineering • Co-Published by ASQ and Taylor & Francis • Practitioner Focus • Journal of Quality Technology • Published by ASQ • Focus on High Level Practitioner/Academic

  6. Background - Journals • Technometrics • Co-Published by ASQ and ASA • Similar Focus as JQT, Tends to be More Mathematical • Quality and Reliability Engineering International • Published by Wiley • More European • Publishes “Best” Papers from ENBIS

  7. Extending Standard Methodologies to Hard Problems • Experiments with Hard-to-Change and Easy-to-Change Factors • Very Common Practical Problem • Extensive Literature for Agricultural Applications • Jones and Nachtsheim • Profile Monitoring • Characteristic of Interest Is a Profile (Function) • Woodall • Computer Experiments

  8. “Statistical Thinking” • Originated in the mid 90s • Basic Idea: • All work occurs in a system of interconnected processes. • Variation exists in all processes. • The keys to success are: • understanding variation • reducing variation.

  9. “Statistical Thinking” • Roger Hoerl and Ron Snee (2012) Statistical Thinking: Improving Business Performance (Wiley and SAS Business Series) • Point: Biggest contribution that quality practitioners can make: get senior managers to understand variation and its sources • Data Analysis in North America is easy to send off-shore!

  10. Applications in Areas Other than Manufacturing • See Quality Engineering for Examples • Service Functions • Accounts Payable • Product Delivery • Costumer Relations • Risk Management • Security • Healthcare • Several People in Israel Have Done Very Nice Work!

  11. Advances in Software • Current Software Can Do Much More Sophisticated Statistical Analyses to Support Quality Engineering • Hard-to-Change versus Easy-to-Change Factors • Integrated Variance Optimal Designs • Space-Filling Designs (Computer Experiments) • Gaussian Stochastic Processes (Comp. Exp.)

  12. Advances in Software • Exercise Caution with Software “Claims”! • You Do Not Need to Think about Data Collection • Give Us the Factors and the Levels • We Give You the Plan • You Do Not Need to Think about The Analysis • We Plan the Data Collection • We Know the Best Analysis • Consequence: Potential for Major Disasters!

  13. Advances in Software • Software Is an Extremely Important Tool • Requires Intelligent Use • “Fisher in a Box”/”George Box in a Box” Does Not Exist! • Data Collection Requires Intelligent Collaboration • Ask the Right Questions • Think Carefully about the Science • Translate Everything Properly into the Analysis

  14. Global Reach • Foundations to Quality Engineering are North American and Japanese Manufacturing • North America: Statistical Theory and Methods • Japan: • Quality Management • “Soft Tools” • Teamwork • Deming, Box, Taguchi, “The Gurus”

  15. Global Reach • Important Influences • Movement of Manufacturing Away from North America • Asian Tigers • China • India • Latin America (Brazil and Mexico) • Recognition in Europe of Need for Quality Engineering: ENBIS

  16. Impact of Global Reach • Editorial Boards Are Truly Global • Authors Publishing in the Quality Engineering Journals Are Truly Global • Proliferation of Outstanding Quality Engineering Conferences • ASQ - Global

  17. Future Directions • Current Directions Will Continue to Grow • New Directions • “Research” • “Practice” • Be Aware of the Divide!

  18. Integrating Quality Engineering Concepts Across Complex Processes • Complex Processes as Opposed to “Data Mining” (Next Topic!) • Developmental Testing of Weapon Systems • Multiyear • Multistage • Different Objectives at Each Stage • Competing Interests! • Complex Manufacturing Processes • Multistage • Often, Multi-location

  19. Integrating Quality Engineering Concepts Across Complex Processes • Good Quality Engineering Practices May or May Not Being Used at Substages • In Some Cases, Just Applying Current Quality Engineering Methods to the System Work • In Many More Cases, Need New Methodology • Formal/Informal Bayesian Methods • Belief Networks

  20. Large Data Sets • Data Mining Is Becoming Extremely Important • Great Deal of Good Work in Israel! • Emergence of Massive Data Warehouses (Planet Scale!) • Standard Statistical Approaches • Not Valid • Not Informative • Often Most Interesting Phenomena: Outliers!

  21. Image Data • Ability to Monitor Processes via Image Data • Basic Analysis of Image Data Becoming “Mature” • In Some Cases, May Be Able to Adapt Standard Statistical Process Control Techniques • In Many Cases, Must Create New Monitoring Procedures Based on Image of Every Item

  22. Greater Emphasis on Reliability • Reliability: Quality Over Time • Customers Beginning to Demand Highly Reliable Products and Processes • Simple Accelerated Life Tests Not Sufficient • Strong Need: • Experimental Design and Analysis for Reliabilty Data • Process Control with Reliability Data

  23. Innovation • Not Long Ago, Building Better Quality Was Significant Innovation • High Quality Now Viewed as Expectation • New Issue: Next Way to “Delight” Customers • “Improved” Current Products • New Products Customers Never Imagined • Issue: How Can Quality Engineering Facilitate Innovation • See January 2012 Issue of Quality Engineering

  24. Proper Training of Practitioners • Six Sigma Brought Quality Engineering into the Hands of Subject Matter Experts • Typical Training Barely Scratched Surface • “3 Month Wonders” • Often, Do Not Know When to Call an Expert • Software Developments • Proper Follow-Up Training Essential

  25. Statistical Engineering • How to best use known statistical principles and tools to solve high impact problems for the benefit of humanity. • tactical integration of statistical thinking with the application of statistical methods and tools (at the operational level • drive proper application of statistical methods based on solid understanding of statistical thinking principles. • typically involves the appropriate selection and use of multiple statistical tools, integrated into a comprehensive approach to solving complex problems. • Focus on Large, Unstructured, Complex Problems • Most Recent Issue of Quality Engineering (April 2012)

More Related