Unearth the possibilities in your data
Statistical Discovery in Quality Engineering
Date: 10 October 2019
Time: 13:00 - 14:20 BST | 14:00 – 15:20 CEST
Registration : Free
Who should attend: Scientists, engineers and anyone who wants to explore data using visual approaches
With quality engineering you can systematically use data to determine more efficient and effective ways to get things done throughout the product life cycle – and minimize the associated cost, waste and time. But increasing levels of automation and the rise of the digital economy mean that data from the production and delivery of products is rapidly increasing in volume and complexity.
This on-line seminar will show how you can still effectively pursue the traditional objectives of process control, improvement and troubleshooting in this evolving world. It will address ways to achieve high quality for your processes, products, services and organizational performance with continuous learning and improvement.
You will learn how to:
- Decide if the measurements you make are actually fit for purpose, or just noise.
- Simply monitor or control processes, even when there are multiple sources of variation.
- Expedite troubleshooting using a blend of visualization and analysis to rapidly identify root causes, even for difficult problems.
- Correctly identify which responses have actually changed after a process intervention.
- Simply and easily communicate your findings to build consensus in engineering and management.
The seminar will be appropriate for anyone who is interested in delivering products and services that consistently meet or exceed customer expectations, reducing time to market and warranty costs, and building and protecting a brand. Whether you are a seasoned practitioner or just starting out, it will provide useful advanced analytical techniques (such as neural networks and tree-based methods).
Register now to attend.
ABOUT THE SPEAKERS
François Bergeret, PhD in statistics, founder of Ippon Innovation and co-author of Statistical process control - principles and industrial cases. He provides consulting in metrology, statistics and modelling, design of experiments, statistical process control and the management of industrial process improvement projects. He is also a lecturer at the University of Toulouse, the INSA (Institut National des Sciences Appliquées) and the ISAE (Institut Supérieur de l'Aéronautique et de l'Espace). His professional experience includes 15 years in industry at Motorola and Freescale as a statistician, quality control manager and zero fault champion. He is also a Six Sigma Black Belt.
Ian Cox, PhD, is Director Pre-Sales Support. He has also been Marketing Manager for JMP in Europe. A Six Sigma Black Belt and Fellow of the Royal Statistical Society, Cox is part of the SPIE organizing committee for Process Control, and referees related papers for the IEEE Transactions on Semiconductor Manufacturing.