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A Design Framework for Bi-Level Estimation of Machining Energy for Parts and Assemblies

[+] Author Affiliations
Gaurav Ameta, He Huang

Washington State University, Pullman, WA

Mahesh Mani

National Institute of Standards and Technology, Gaithersburg, MD

Paper No. DETC2009-86805, pp. 1103-1111; 9 pages
  • ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 29th Computers and Information in Engineering Conference, Parts A and B
  • San Diego, California, USA, August 30–September 2, 2009
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4899-9 | eISBN: 978-0-7918-3856-3
  • Copyright © 2009 by ASME


This paper presents a framework and approach for the computation of machining energy for parts and assemblies, at two levels — early design stage and manufacturing stage. Energy estimation at an early design stage can be useful for redesign strategies and improving manufacturing efficiency. At the manufacturing stage, energy estimations allow for asset management based on energy efficient process planning and scheduling, thereby reducing the negative impacts of the product to the environment. To facilitate the computation of the machining energy, at an early design stage, we first automate the process of identifying the material removal volume for machining operations for a given part. We subsequently use the identified removal volume together with the material specific data to compute an energy range for manufacturing the part. For an assembly, the above computations for individual parts are aggregated to arrive at the final energy range. The proposed method allows the identification of energy intensive parts/features based on the percent contribution, thereby assisting re-design strategies. We additionally explore the application of statistical analysis and allocation principles to identify priority re-design parts. In this paper, we limit our product re-design discussions based on form (geometry and shape) and material. Future extensions will potentially also include manufacturing process optimization. Although the framework presented in this paper is currently applied only to milled parts and assemblies, it can also be extended to other machining methods.

Copyright © 2009 by ASME
Topics: Machining , Design



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