Ivan Scansani Gregori
Ivan Roger Scansani Gregori holds a Ph.D. in Engineering and is an Engineering Manager at ZF. He has more than thirty years of experience working with friction materials, tribology, and signal analysis, applying multivariate statistics and machine learning to real-world problems in clutch and transmission systems. He has also joined his son’s platform to help create high-quality content based on his expertise.
Multivariate exploratory analysis of eight process variables identified two that correlate with burst resistance — one positively, one negatively — and process changes based on that finding raised both burst resistance and reliability.
Design of experiments and Weibull analysis are used to correlate friction facing wear on a bench test with vehicle mileage, making it possible to estimate field durability from bench results.
The original presentation of a bench test procedure built to contain the full range of vehicle operating conditions, so that friction facing durability can be studied without depending on uncontrolled field data.
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Books
1Every clutch tells a story in torque—if you know how to read it. This collection of nine studies follows a single thread from bench to road: how laboratory signals, multivariate statistics, and finite element models can predict judder, burst, and wear without waiting for the vehicle. It is a casebook for engineers who want to move friction material development out of the field and into the lab.
Sep 13, 2026
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