Design heuristics for additive manufacturing
Year: 2017
Editor: Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos
Author: Blösch-Paidosh, Alexandra; Shea, Kristina
Series: ICED
Institution: ETH Zurich, Switzerland
Section: Design for X, Design to X
Page(s): 091-100
ISBN: 978-1-904670-93-3
ISSN: 2220-4342
Abstract
The potential benefits of additive manufacturing (AM) have been expounded upon by many in academic, industry, media, and policy circles. These potential benefits include functional integration, reduced complexity, increased robustness and increased performance. Many designers would like to take advantage of these benefits to improve their designs, but are at a loss as to how they can best incorporate AM. Existing DfAM methods are not tailored to generating the high-level concepts desired in the early stages of the design process and often require AM process-specific knowledge. Therefore, we propose to provide an AM process-independent method for transferring the high-level knowledge necessary for reasoning about functions and configurations to designers in the context of AM. The chosen method to accomplish this knowledge transfer is design heuristics for AM, which we derive from an analysis of 275 existing AM artifacts. Twenty-nine process-independent heuristics are derived, and the feasibility of the heuristics is verified with two DfAM case studies: a car door and a fighter pilot helmet to provide an initial proof of concept.
Keywords: Additive Manufacturing, Design for Additive Manufacturing (DfAM), Design methods, Early design phases, Design heuristics