Webinar: Sources of Variation Analysis with GLM

In our ISSSP April 2023 webinar, General Linear Modeling (GLM) was used to analyze Gage R&R data. While that webinar focused on a specific application of Sources of Variation, this webinar will look at using GLM to more generally analyze Sources of Variation data to compute variance components. By breaking down the total variability into parts attributable to different random factors, it becomes possible to understand what sources of variability are contributing the most to the overall variability. This then helps to prioritize improvement effort for variation reduction and statistical process control. GLM can accommodate fixed or random factors, interactions between these factors and unbalanced data. Note complex formula details will not be discussed - SigmaXL software will be used to demonstrate these methods.

Webinar Outline:

Review of GLM for Variance Components
Basic Sources of Variation: Within, Between, Over-Time data
Graphical tools: Multi-Vari and I-MR-R/S
GLM Analysis of Within, Between, Over-Time data
Case Study from Montgomery, Design and Analysis of Experiments, Example 14.2, Assembly Time Data from Nested Factorial Design
Re-Analysis of Assembly Time Data as Unbalanced

John Noguera
John Noguera

About John Noguera

John Noguera is Co-founder and Chief Technology Officer of SigmaXL, Inc., a leading provider of user-friendly Excel add-ins for Lean Six Sigma tools, statistical & graphical analysis and Monte Carlo simulation. He leads the development of SigmaXL and DiscoverSim with a passion for ease of use, practical & powerful features, and statistical accuracy. John is a certified Six Sigma master black belt and was an instructor at Motorola University. He has authored conference papers on Statistical Process Control and Six-Sigma Quality and is a contributing author in the Encyclopedia of Statistics in Quality and Reliability (Wiley).