Additive vs. conventional manufacturing of metal components: selection of the manufacturing process using the AHP method

Dirk Schuhmann*, Mario Rupp, Markus Merkel, David K. Harrison

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
7 Downloads (Pure)

Abstract

Additive manufacturing (AM) processes have experienced significant technological developments over the past decade. Today, 3D-printed metal parts can almost achieve the mechanical properties of conventionally manufactured components; process times have been shortened, and the range of available materials has been widely expanded. The decision between conventional manufacturing and AM is therefore becoming more complex, considering technical and economic criteria along the entire product life cycle. To reflect the vision of the manufacturer, each decision needs to be based on individual preferences and strategies. The present research introduces a standardised and systemised multi-criteria decision-making process to choose between additive and conventional production. Multi-criteria decision models from within the literature are analysed and a holistic decision matrix is developed based on the analytic hierarchy process (AHP). The key novelty of the present research is the consideration of technical and economic categories along the whole product life cycle for decision making. The matrix allows an individual weighting of individual criteria along the product life cycle, starting with the conceptualisation of the product, and ending with marketing and after-sales. The approach is evaluated using two scenarios, including a control unit housing and a flat metal gasket, with different scopes of application. In conclusion, the developed multi-criteria decision matrix provides sufficient and repeatable results. The systematic decision process allows users to clearly identify the best production method for their individual use case.
Original languageEnglish
Article number1617
JournalProcesses
Volume10
Issue number8
Early online date16 Aug 2022
DOIs
Publication statusPublished - Aug 2022

Keywords

  • multi-criteria decision model
  • 3D printing
  • production
  • product life cycle
  • resource efficiency

ASJC Scopus subject areas

  • Chemical Engineering (miscellaneous)
  • Bioengineering
  • Process Chemistry and Technology

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