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Approach Towards a Decision Support System for Additive Manufacturing

[+] Author Affiliations
Douglas Eddy, Justin Calderara, Mark Price, Sundar Krishnamurty, Ian Grosse

University of Massachusetts Amherst, Amherst, MA

Paper No. DETC2016-60507, pp. V01AT02A047; 11 pages
doi:10.1115/DETC2016-60507
From:
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1A: 36th Computers and Information in Engineering Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5007-7
  • Copyright © 2016 by ASME

abstract

Advancements in the capabilities of additive manufacturing (AM) have increased its usage as an appropriate manufacturing process, particularly when the number of parts in an assembly can be significantly reduced, production volumes are low, or geometric complexity is difficult, if not impossible, to obtain through conventional subtractive processes. However, there are many reasons why it is best to not design a given part based on AM technology. The choice of conventional versus AM manufacturing must occur as early as possible in the design process as this choice can substantially affect how the product is designed. Making the wrong decision will lead to wasted design time, increased time to market the product, a functionally inferior design, and/or a costlier product. To address this critical manufacturing decision, we introduce a usable template and a decision making method for manufacturing process selection which is integrated early into the design process (DS-SAM). This work can serve as the logical foundation for a potential holistic and more mathematically rigorous formulation toward a decision making method that could infer design evaluations based on designer inputs. This approach improves early design efficiency and effectiveness by methodically focusing on the key design process elements to optimally compare alternatives earlier in a design process. The benefits and potential cost savings of using the DS-SAM approach are demonstrated by a pair of case studies, and the results are discussed.

Copyright © 2016 by ASME

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