A specific manufacturing cost model for fast cost estimation in additive manufacturing

Li Yi; Max Werrel; Svenja Ehmsen; Moritz Glatt; Jan C. Aurich

doi:10.1016/j.procir.2023.08.005

A specific manufacturing cost model for fast cost estimation in additive manufacturing

Li Yi^*
, Max Werrel
, Svenja Ehmsen
, Moritz Glatt
, Jan C. Aurich

^*此作品的通讯作者

The University of Kaiserslautern-Landau

科研成果: 期刊稿件 › 会议文章 › 同行评审

6 引用（Scopus）

摘要

Additive manufacturing (AM) has been widely used for high-value-added parts. Therefore, cost models are needed for fast and accurate cost estimation during the AM design phase; otherwise, incorrect cost estimation may cause unexpected cost expenses. This work proposes a parametric cost model for AM using experimental and statistical methods. In this work, specific manufacturing costs (SMC) and build rates (cm^3/h) are calculated based on experiments and approximated by regression models. For a fast cost estimation in AM, the build rate for a build task needs to be investigated, and then the SMC can be calculated using the regression model.

源语言	英语
页（从-至）	21-26
页数	6
期刊	Procedia CIRP
卷	120
DOI	https://doi.org/10.1016/j.procir.2023.08.005
出版状态	已出版 - 2023
已对外发布	是
活动	56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023 - Cape Town, 南非期限: 24 10月 2023 → 26 10月 2023

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10.1016/j.procir.2023.08.005

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引用此

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title = "A specific manufacturing cost model for fast cost estimation in additive manufacturing",

abstract = "Additive manufacturing (AM) has been widely used for high-value-added parts. Therefore, cost models are needed for fast and accurate cost estimation during the AM design phase; otherwise, incorrect cost estimation may cause unexpected cost expenses. This work proposes a parametric cost model for AM using experimental and statistical methods. In this work, specific manufacturing costs (SMC) and build rates (cm3/h) are calculated based on experiments and approximated by regression models. For a fast cost estimation in AM, the build rate for a build task needs to be investigated, and then the SMC can be calculated using the regression model.",

keywords = "additive manufacturing, cost estimation, material extrusion, specific manufacturing cost, statsticl modeling",

author = "Li Yi and Max Werrel and Svenja Ehmsen and Moritz Glatt and Aurich, \{Jan C.\}",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International Conference on Manufacturing Systems 2023.; 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023 ; Conference date: 24-10-2023 Through 26-10-2023",

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doi = "10.1016/j.procir.2023.08.005",

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volume = "120",

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AU - Yi, Li

AU - Werrel, Max

AU - Ehmsen, Svenja

AU - Glatt, Moritz

AU - Aurich, Jan C.

N1 - Publisher Copyright: © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International Conference on Manufacturing Systems 2023.

PY - 2023

Y1 - 2023

N2 - Additive manufacturing (AM) has been widely used for high-value-added parts. Therefore, cost models are needed for fast and accurate cost estimation during the AM design phase; otherwise, incorrect cost estimation may cause unexpected cost expenses. This work proposes a parametric cost model for AM using experimental and statistical methods. In this work, specific manufacturing costs (SMC) and build rates (cm3/h) are calculated based on experiments and approximated by regression models. For a fast cost estimation in AM, the build rate for a build task needs to be investigated, and then the SMC can be calculated using the regression model.

AB - Additive manufacturing (AM) has been widely used for high-value-added parts. Therefore, cost models are needed for fast and accurate cost estimation during the AM design phase; otherwise, incorrect cost estimation may cause unexpected cost expenses. This work proposes a parametric cost model for AM using experimental and statistical methods. In this work, specific manufacturing costs (SMC) and build rates (cm3/h) are calculated based on experiments and approximated by regression models. For a fast cost estimation in AM, the build rate for a build task needs to be investigated, and then the SMC can be calculated using the regression model.

KW - additive manufacturing

KW - cost estimation

KW - material extrusion

KW - specific manufacturing cost

KW - statsticl modeling

UR - https://www.scopus.com/pages/publications/85184587943

U2 - 10.1016/j.procir.2023.08.005

DO - 10.1016/j.procir.2023.08.005

M3 - 会议文章

AN - SCOPUS:85184587943

SN - 2212-8271

VL - 120

SP - 21

EP - 26

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023

Y2 - 24 October 2023 through 26 October 2023

ER -

A specific manufacturing cost model for fast cost estimation in additive manufacturing

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