Additive manufacturing cost estimation models—a classification review

With the recent evolution of additive manufacturing (AM), accurate cost prediction models are of increasing importance to assist decision-making during product development tasks. Estimating the cost is a challenging task in that it requires a vast amount of manufacturing knowledge that has to be syn...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of advanced manufacturing technology 2020-04, Vol.107 (9-10), p.4033-4053
Hauptverfasser: Kadir, Aini Zuhra Abdul, Yusof, Yusri, Wahab, Md Saidin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:With the recent evolution of additive manufacturing (AM), accurate cost prediction models are of increasing importance to assist decision-making during product development tasks. Estimating the cost is a challenging task in that it requires a vast amount of manufacturing knowledge that has to be synchronised with many aspects from design to production. As a result, various AM cost models have been developed. This review is performed with the aim of providing an overview of the costing models being developed and utilised associated with the additive manufacturing product development phases. For a better understanding in this field, it is required to become familiar with the various terminologies, perspectives, concepts, techniques, and approaches used in developing these models. It was observed that the contexts and views described during the development of the models were often targeted at specific applications as well as technologies and were classified in many ways. Accordingly, the paper compiles different aspects of the cost estimation classification technique and provides definitions of some of the key terminologies. The main motivation is to provide broad and in-depth reviews of the estimation models developed over the past three decades using a systematic classification approach. From the review, a visualisation of future insights into the AM cost-oriented estimation framework from the perspective of various AM users can be better understood.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-020-05262-5