Design for Additive Manufacturing: Motivations, Competencies and Performance Impact

Atanu Chaudhuri; Jayanth Jayaram; Iñigo Flores Ituarte; Peder Veng Søberg; Siavash H.  Khajavi

Design for Additive Manufacturing: Motivations, Competencies and Performance Impact

Atanu Chaudhuri, Jayanth Jayaram, Iñigo Flores Ituarte, Peder Veng Søberg, Siavash H. Khajavi

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

32 secondary cases on Design for Additive Manufacturing (DfAM) and expert interviews were used to identify motivations, required competencies and performance impact of AM. Findings suggest that weight reduction motivation coupled with topology optimization competency helped in reducing weight and the number of parts. Material choice competency helped in reducing weight or in improving part functionality or quality. Weight reduction also required design simulation. Choice of appropriate AM process parameters was needed to reduce production time. 8 case studies indicated a collaborative process between DfAM partners.

Original language	English
Title of host publication	26 th EurOMA Conference - Operations adding value to Society
Publication date	2019
Publication status	Published - 2019
Event	26th EurOMA Conference - Operations adding value to Society - Hanken School of Economics - Aalto University Business School , Helsinki, Finland Duration: 17 Jun 2019 → 19 Oct 2019 http://euroma2019.org/

Conference

Conference	26th EurOMA Conference - Operations adding value to Society
Location	Hanken School of Economics - Aalto University Business School
Country/Territory	Finland
City	Helsinki
Period	17/06/2019 → 19/10/2019
Internet address	http://euroma2019.org/

Keywords

Design for AM
motivation
competencies
Performance impact

AUB Link

Search for the material in Aalborg University Library's search engine

Cite this

@inproceedings{a0d16240b787412aa7e72524d0a5c1a8,

title = "Design for Additive Manufacturing: Motivations, Competencies and Performance Impact",

abstract = "32 secondary cases on Design for Additive Manufacturing (DfAM) and expert interviews were used to identify motivations, required competencies and performance impact of AM. Findings suggest that weight reduction motivation coupled with topology optimization competency helped in reducing weight and the number of parts. Material choice competency helped in reducing weight or in improving part functionality or quality. Weight reduction also required design simulation. Choice of appropriate AM process parameters was needed to reduce production time. 8 case studies indicated a collaborative process between DfAM partners. ",

keywords = "Design for AM, motivation, competencies, Performance impact",

author = "Atanu Chaudhuri and Jayanth Jayaram and Ituarte, {I{\~n}igo Flores} and S{\o}berg, {Peder Veng} and Khajavi, {Siavash H.}",

year = "2019",

language = "English",

booktitle = "26 th EurOMA Conference - Operations adding value to Society",

note = "26th EurOMA Conference - Operations adding value to Society ; Conference date: 17-06-2019 Through 19-10-2019",

url = "http://euroma2019.org/ ",

}

TY - GEN

T1 - Design for Additive Manufacturing

T2 - 26th EurOMA Conference - Operations adding value to Society

AU - Chaudhuri, Atanu

AU - Jayaram, Jayanth

AU - Ituarte, Iñigo Flores

AU - Søberg, Peder Veng

AU - Khajavi, Siavash H.

PY - 2019

Y1 - 2019

N2 - 32 secondary cases on Design for Additive Manufacturing (DfAM) and expert interviews were used to identify motivations, required competencies and performance impact of AM. Findings suggest that weight reduction motivation coupled with topology optimization competency helped in reducing weight and the number of parts. Material choice competency helped in reducing weight or in improving part functionality or quality. Weight reduction also required design simulation. Choice of appropriate AM process parameters was needed to reduce production time. 8 case studies indicated a collaborative process between DfAM partners.

AB - 32 secondary cases on Design for Additive Manufacturing (DfAM) and expert interviews were used to identify motivations, required competencies and performance impact of AM. Findings suggest that weight reduction motivation coupled with topology optimization competency helped in reducing weight and the number of parts. Material choice competency helped in reducing weight or in improving part functionality or quality. Weight reduction also required design simulation. Choice of appropriate AM process parameters was needed to reduce production time. 8 case studies indicated a collaborative process between DfAM partners.

KW - Design for AM

KW - motivation

KW - competencies

KW - Performance impact

UR - http://euroma2019.org/media/1408/detailed_programme0615.pdf

M3 - Article in proceeding

BT - 26 th EurOMA Conference - Operations adding value to Society

Y2 - 17 June 2019 through 19 October 2019

ER -

Design for Additive Manufacturing: Motivations, Competencies and Performance Impact

Abstract

Conference

Keywords

AUB Link

Other files and links

Fingerprint

Cite this