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Identifying Relative Importance of Input Parameter(s) for Developing Predictive Model for Laser Cladding Process

[+] Author Affiliations
Kush Aggarwal, Ruth Jill Urbanic, Luv Aggarwal, Syed Saqib

University of Windsor, Windsor, ON, Canada

Paper No. IMECE2014-37719, pp. V02AT02A009; 12 pages
doi:10.1115/IMECE2014-37719
From:
  • ASME 2014 International Mechanical Engineering Congress and Exposition
  • Volume 2A: Advanced Manufacturing
  • Montreal, Quebec, Canada, November 14–20, 2014
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4643-8
  • Copyright © 2014 by ASME

abstract

Laser cladding (LC) is a multi-variable coating process which consists of process multiple inputs and associated bead geometry outputs. Fabrication of a desired clad bead geometry configuration is expensive, as it involves investment of specialized raw materials, specialty equipment, and time resources. Hence, it is vital to determine factors/inputs that affect the overall physical bead geometry parameters (response variables), and the nature of the responses. The objective of this research is to identify the extent of the contribution of each factor and impact of their interactions on the output which is essential in developing effective predictive models. Analysis of variance (ANOVA) and sensitivity analysis methodologies are studied in this research to determine the most significant process factors that relate to the shape parameters for a typical laser cladding production process scenario. A set of statistical based summaries for all response variables are presented. This includes contour and surface plots to illustrate the difference in effects for a response variable by a single process parameter as compared to two or more interacting process parameters. Finally, an optimization solver toolbox is applied to determine single and multiple objective optimization results that can be obtained for various desired bead geometries.

Copyright © 2014 by ASME

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