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Erschienen in: The International Journal of Advanced Manufacturing Technology 9-10/2020

24.04.2020 | ORIGINAL ARTICLE

Additive manufacturing cost estimation models—a classification review

verfasst von: Aini Zuhra Abdul Kadir, Yusri Yusof, Md Saidin Wahab

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 9-10/2020

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Abstract

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.

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Metadaten
Titel
Additive manufacturing cost estimation models—a classification review
verfasst von
Aini Zuhra Abdul Kadir
Yusri Yusof
Md Saidin Wahab
Publikationsdatum
24.04.2020
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 9-10/2020
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-020-05262-5

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