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GOALI: Reliability-Based Design and Operation of Metal Rolling Mills using Bayesian Theory and a New Rolling Model

$364,474FY2011ENGNSF

Saint Louis University, Saint Louis MO

Investigators

Abstract

The research objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) award is to apply a new simplified, mixed finite element roll-stack deflection model as evidence with Bayesian Theory to calculate probabilities of attaining important criteria in metal rolling, including strip thickness profile and strip flatness distributions. The probability predictions will be used to study propagation effects of rolling process uncertainties, and to create new reliability-based mill simulation and control models that lead to higher quality, more efficient rolling schedules. The metal rolling industry's traditional way of addressing process uncertainties is to use statistical process control to simply monitor resulting variations in quality and efficiency criteria. This "backward-looking" approach is limited in that it neither adjusts nor optimizes the process set-up parameters based on predictive probability estimates of the rolling requirements. In contrast, the approach of this research award is to introduce an entirely new "forward-looking" method to optimize rolling parameters based on probability predictions for strip thickness profile and flatness. If successful, this research will economically benefit the many companies producing steel, aluminum, and copper sheet. These companies will be able to roll metal products at higher speeds, and with superior flatness and thickness profiles. The manufacturers of metal rolling mills and associated control systems will also benefit from the capability to design more competitive rolling equipment and systems. The broader societal and educational impacts of this research involve summer workshop programs for inner city teens offered by the Lewis & Clark Educational Institute of Saint Louis. These workshops, entitled "Math and Manufacturing", will spark the interest of fifth to eighth graders as to the exciting roles that math, science, and engineering play in industry. Furthermore, research-driven classroom projects, mentored by engineers from the industry partner, will provide undergraduates engineering students with an enriched learning experience.

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