Economic Benefit Analysis of Cloud-Based Design, Engineering Analysis, and Manufacturing

被引:12
作者
Wu, Dazhong [1 ]
Terpenny, Janis [1 ]
Gentzsch, Wolfgang [2 ]
机构
[1] Iowa State Univ, Ctr E Design, Ames, IA 50010 USA
[2] UberCloud, Los Altos, CA 94024 USA
来源
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME | 2015年 / 137卷 / 04期
基金
美国国家科学基金会;
关键词
cloud-based design and manufacturing; cloud-based engineering analysis; cloud computing; cost-benefit analysis; activity-based costing; COST ESTIMATION;
D O I
10.1115/1.4030306
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
From a business perspective, cloud computing has revolutionized the information and communication technology (ICT) industry by offering scalable and on-demand ICT services as well as innovative pricing plans such as pay-per-use and subscription. Considering the economic benefits of cloud computing, cloud-based design and manufacturing (CBDM) has been proposed as a new paradigm in digital manufacturing and design innovation. Although CBDM has the potential to reduce costs associated with high performance computing (HPC) and maintaining ICT infrastructures in the context of cloud computing, it is challenging to justify the potential cost savings associated with design and manufacturing because of the complexity in the economic benefit analysis of migrating to CBDM. In response, this paper provides important insights into the economics of CBDM by identifying key cost factors and potential pricing models that can influence decision making on whether migrating to the cloud for computationally expensive analyses that are commonplace for design and manufacturing (e.g., computer-aided design (CAD)/computer-aided engineering (CAE)/computer-aided manufacturing (CAM)) is economically justifiable. This work, for the first time, identifies the key economic benefits required for a comparative study that supports organizations in determining when traditional in-house design and manufacturing versus CBDM is most appropriate. Several comparative case studies and a hypothetical application example are provided to demonstrate and quantitatively validate decision support methods. Finally, key issues and road blocks for CBDM are outlined.
引用
收藏
页数:9
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