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Additive manufacturing–integrated hybrid manufacturing and subtractive processes: economic model and analysis

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This article presents economic models for a new hybrid method where additive manufacturing (AM) and subtractive methods (SMs) are integrated through composite process planning. Although AM and SM offer several unique advantages, there are technological limitations such as tolerance and surface finish requirements; tooling and fixturing, etc. that cannot be met by a single type of manufacturing. The intent of this article is not to show a new manufacturing method, but rather to provide economic context to additive and subtractive methods as the best practice provides, and look at the corresponding economics of each of those methods as a function of production batch size, machinability, cost of the material, part geometry and tolerance requirements. Basic models of fixed and variable costs associated with additive, subtractive and hybrid methods to produce parts are also presented. An experimental design is used to study the influence of production volume, material and operating cost, batch size, machinability of the material and impact of reducing AM processing time. A composite response model for the unit cost is computed for the various levels associated with such engineering requirements. The developed models provide insight into how these variables affect the costs associated with engineering a mechanical product that will be produced using AM and SM methods. From the results, it appears that batch size, AM processing time and AM processing cost were the major cost factors. It was shown that the cost of producing ‘near-net’ shape through SM and AM was the decision criteria; which will be critical for tough-to-machine alloys and at multi-batch size.
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Keywords: AIMS; CNC-RP; EBM; economic analysis and additive manufacturing; hybrid manufacturing

Document Type: Research Article

Affiliations: 1: Department of Mechanical and Industrial Engineering, Youngstown State University, Youngstown, OH, USA 2: Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC, USA

Publication date: May 3, 2016

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