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Special Section Articles

Design and Implementation of a Broker for Cloud Additive Manufacturing Services

[+] Author and Article Information
Venkata P. Modekurthy

Department of Computer Science,
Missouri University of Science and Technology,
Rolla, MO 65409
e-mail: vmkf5@mst.edu

Xiaoqing F. Liu

Department of Computer Science,
Missouri University of Science and Technology,
Rolla, MO 65409
e-mail: fliu@mst.edu

Kenneth K. Fletcher

Department of Computer Science,
Missouri University of Science and Technology,
Rolla, MO 65409
e-mail: kkft3c@mst.edu

Ming C. Leu

Department of Mechanical
and Aerospace Engineering,
Missouri University of Science and Technology,
Rolla, MO 65409
e-mail: mleu@mst.edu

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received November 14, 2014; final manuscript received May 8, 2015; published online July 8, 2015. Assoc. Editor: Xun Xu.

J. Manuf. Sci. Eng 137(4), 040904 (Aug 01, 2015) (10 pages) Paper No: MANU-14-1593; doi: 10.1115/1.4030670 History: Received November 14, 2014; Revised May 08, 2015; Online July 08, 2015

With increasing number of cloud additive manufacturing (AM) service providers, cloud AM services are becoming decentralized and it is difficult for consumers to discover cloud AM services according to their personal preferences and tradeoffs. Existing frameworks of cloud manufacturing either do not have brokers between cloud manufacturing service providers and consumers or do not support personalized preference and tradeoff based brokerage. In this paper, we present a cloud-based service broker system for cloud AM to provide consumers with a single point of access to a large number of cloud AM services from many cloud AM service providers over the Internet based on a service oriented architecture using web services. This broker system uses an innovative cloud AM service selection method which considers consumers' preferences and tradeoffs on service attributes like price, material, and accuracy in the ranking process. It is also based on a new integrated representation for both exact and varied matches in cloud AM service selection. We present an application case study to show how the cloud AM service broker system is used to select cloud AM services based on personal preferences and tradeoffs. It demonstrates feasibility of brokerage in cloud AM and effectiveness of the cloud AM service ranking method based on personalized preferences and tradeoffs.

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Figures

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Fig. 3

Framework of the cloud AM service selection engine

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Fig. 2

Framework of the proposed cloud AM broker system

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Fig. 1

The proposed cloud AM hierarchical architecture

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Fig. 4

The Missouri University of Science and Technology emblem in STL file1

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Fig. 7

Application result for consumer #2's request

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Fig. 5

Connector part to be manufactured in STL file2

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Fig. 6

Application result for consumer #1's request

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