Designed Experiments for Process Improvement - A joint webinar from the Statistics Division and the Canadian Section 3710
Designed Experiments for Process Improvement - A joint webinar from the Statistics Division and the Canadian Section
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Designed Experiments for Process Improvement
A Case Study & Potential Applications

This case-study describes the successful application of a designed experiment to resolve a significant issue in a complex industrial process. The paper further describes the broader family of highly efficient “factorial designs” that yield the maximum information with minimum resources. Equally simple and effective are graphical methods for the analysis of experiment data. The methodology is applicable to product & process improvement in all sectors.

Speaker Bio

Lally Marwah has led Quality systems & Statistical applications in IBM and Nortel Networks, as well as at SSHA (eHealth) and TSSA in the public sector. As chief statistician at IBM he led the deployment of statistical methods for improvement and control – SPC, Designed Experiments, Sampling and Reliability – key elements of a Six-Sigma framework. He led the development and ISO 9001 registration of the Global quality system at Nortel Networks; formulated Quality strategy at SSHA as Director, Corporate Quality; and served on the Board of Directors at TSSA. In parallel, Marwah has taught applied statistics at the University of Toronto and other academic forums; and conducted on-site statistics workshops in various companies and industry forums such as the ASQ. Marwah represents Canada in the governing body of ISO 9001 and has chaired the development of ISO standards on statistical techniques and on customer satisfaction. He has served on the Boards of industrial and academic institutions, notably at the University of Waterloo.
Date & Time
Wednesday January 26th, 2022 12:00pm CST
End Date & Time
Wednesday January 26th, 2022 1:00pm CST
Venue
Webinar
Categories
Webinar
Host Type
Geographic, Technical
Event Sponsor Information
ASQ Canadian Section and the Statistics Division
Category Public Calendar

Event Comments

No Data Available

Event Map

Date & Time: 01/26/2022 12:00:00 PM CST