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Additive Manufacturing Decision Support Systems : A Systematic Literature Review Discerning Current and Future Directions

Rai, Chinthan ; Bhanuprakash, Shashank ; Kianian, Babak LU and Ståhl, Jan Eric LU (2022) 10th Swedish Production Symposium, SPS 2022 In Advances in Transdisciplinary Engineering 21. p.553-565
Abstract

Additive manufacturing (AM) was introduced the 1980's for rapid prototyping (RP) purposes but now AM provides complementary techniques to conventional manufacturing processes and offers advantages when components can be exacting, impossible, and too costly to be produced by conventional methods due to complex structures and geometric configurations, which require tailored designs. They are also often mass-customized components, with custom-made properties and low volume production requirements making AM the 'technology of choice' since its added-value aspects cannot be achieved by any other manufacturing technologies. These advancements in manufacturing, demand standardized fact-based decision support systems (DSSs), to support AM... (More)

Additive manufacturing (AM) was introduced the 1980's for rapid prototyping (RP) purposes but now AM provides complementary techniques to conventional manufacturing processes and offers advantages when components can be exacting, impossible, and too costly to be produced by conventional methods due to complex structures and geometric configurations, which require tailored designs. They are also often mass-customized components, with custom-made properties and low volume production requirements making AM the 'technology of choice' since its added-value aspects cannot be achieved by any other manufacturing technologies. These advancements in manufacturing, demand standardized fact-based decision support systems (DSSs), to support AM practitioners in their task selecting the most suitable techniques for given applications. Hence, this paper aims to increase the understanding of what - of how - DSSs are used in selecting and utilizing AM in various applications. This paper's core message, considering practical implications, is to guide and support AM researchers with an overview of the DSSs for AM landscape. This paper presents and compares different models and tools classified within four categories used as DSS for AM and identifies their advantages and disadvantages by conducting a 3-step systematic literature review (SLR). A total of 388 literatures were initially retrieved, and according to an inclusion criteria analysis, the literatures were evaluated. This is the first SLR emphasizing and synthesizing obtainable literatures on AM DSS. Until now, this topic has acquired narrow exploration; however, the authors believe it is of rapidly growing importance to both scientists and practitioners.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
3D Printing (3DP), Additive Manufacturing (AM), Decision Support System (DSS), Decision-Making Tools, Systematic Literature Review (SLR)
host publication
SPS 2022 - Proceedings of the 10th Swedish Production Symposium
series title
Advances in Transdisciplinary Engineering
editor
Ng, Amos H.C. ; Syberfeldt, Anna ; Hogberg, Dan and Holm, Magnus
volume
21
pages
13 pages
publisher
IOS Press
conference name
10th Swedish Production Symposium, SPS 2022
conference location
Skovde, Sweden
conference dates
2022-04-26 - 2022-04-29
external identifiers
  • scopus:85132818718
ISSN
2352-751X
2352-7528
ISBN
9781614994398
DOI
10.3233/ATDE220174
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2022 The authors and IOS Press.
id
c385e3a2-24bf-4ea2-9d87-e0a0f512205a
date added to LUP
2022-07-24 11:06:40
date last changed
2024-06-13 18:05:39
@inproceedings{c385e3a2-24bf-4ea2-9d87-e0a0f512205a,
  abstract     = {{<p>Additive manufacturing (AM) was introduced the 1980's for rapid prototyping (RP) purposes but now AM provides complementary techniques to conventional manufacturing processes and offers advantages when components can be exacting, impossible, and too costly to be produced by conventional methods due to complex structures and geometric configurations, which require tailored designs. They are also often mass-customized components, with custom-made properties and low volume production requirements making AM the 'technology of choice' since its added-value aspects cannot be achieved by any other manufacturing technologies. These advancements in manufacturing, demand standardized fact-based decision support systems (DSSs), to support AM practitioners in their task selecting the most suitable techniques for given applications. Hence, this paper aims to increase the understanding of what - of how - DSSs are used in selecting and utilizing AM in various applications. This paper's core message, considering practical implications, is to guide and support AM researchers with an overview of the DSSs for AM landscape. This paper presents and compares different models and tools classified within four categories used as DSS for AM and identifies their advantages and disadvantages by conducting a 3-step systematic literature review (SLR). A total of 388 literatures were initially retrieved, and according to an inclusion criteria analysis, the literatures were evaluated. This is the first SLR emphasizing and synthesizing obtainable literatures on AM DSS. Until now, this topic has acquired narrow exploration; however, the authors believe it is of rapidly growing importance to both scientists and practitioners.</p>}},
  author       = {{Rai, Chinthan and Bhanuprakash, Shashank and Kianian, Babak and Ståhl, Jan Eric}},
  booktitle    = {{SPS 2022 - Proceedings of the 10th Swedish Production Symposium}},
  editor       = {{Ng, Amos H.C. and Syberfeldt, Anna and Hogberg, Dan and Holm, Magnus}},
  isbn         = {{9781614994398}},
  issn         = {{2352-751X}},
  keywords     = {{3D Printing (3DP); Additive Manufacturing (AM); Decision Support System (DSS); Decision-Making Tools; Systematic Literature Review (SLR)}},
  language     = {{eng}},
  month        = {{04}},
  pages        = {{553--565}},
  publisher    = {{IOS Press}},
  series       = {{Advances in Transdisciplinary Engineering}},
  title        = {{Additive Manufacturing Decision Support Systems : A Systematic Literature Review Discerning Current and Future Directions}},
  url          = {{http://dx.doi.org/10.3233/ATDE220174}},
  doi          = {{10.3233/ATDE220174}},
  volume       = {{21}},
  year         = {{2022}},
}