Selection for Rapid Manufacturing under epistemic uncertainty

被引:0
作者
Wilson, Jamal O. [1 ]
Rosen, David [1 ]
机构
[1] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Syst Realizat Lab, Atlanta, GA 30332 USA
来源
DETC 2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2005, Vol 4 | 2005年
关键词
Rapid Manufacturing; selection; epistemic uncertainty; decision support problem technique;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Rapid Prototyping (RP) is the process of building three-dimensional objects, in layers, using additive manufacturing. Rapid Manufacturing (RM) is the use of RP technologies to manufacture end-use, or finished, products. At small lot sizes, such as with customized products, traditional manufacturing technologies become infeasible due to the high costs of tooling and setup. RM offers the opportunity to produce these customized products economically. Coupled with the customization opportunities afforded by RM is a certain degree of uncertainty. This uncertainty is mainly attributed to the lack of information known about what the customer's specific requirements and preferences are at the time of production. In this paper, we present an overall method for selection of a RM technology under the geometric uncertainty inherent to mass customization. Specifically, we define the types of uncertainty inherent to RM (epistemic), propose a method to account for this uncertainty in a selection process (interval analysis), and propose a method to select a technology under uncertainty (Hurwicz selection criterion). We illustrate our method with an example on the selection of an RM technology to produce custom caster wheels.
引用
收藏
页码:451 / 460
页数:10
相关论文
共 22 条
[1]   The decision to introduce new technology: The fuzzy preliminary selection decision support problem [J].
Allen, JK .
ENGINEERING OPTIMIZATION, 1996, 26 (01) :61-77
[2]   Epistemic uncertainty quantification techniques including evidence theory for large-scale structures [J].
Bae, HR ;
Grandhi, RV ;
Canfield, RA .
COMPUTERS & STRUCTURES, 2004, 82 (13-14) :1101-1112
[3]  
Bascaran E., 1989, ENG OPTIMIZ, V14, P207, DOI [10.1080/03052158908941212, DOI 10.1080/03052158908941212]
[4]   Design and planning under uncertainty: issues on problem formulation and solution [J].
Cheng, L ;
Subrahmanian, E ;
Westerberg, AW .
COMPUTERS & CHEMICAL ENGINEERING, 2003, 27 (06) :781-801
[5]  
FERNANDEZ MG, 2001, 2001 ASME DES ENG TE
[6]  
FERNANDEZ MG, 2002, MECH ENG
[7]   Different methods are needed to propagate ignorance and variability [J].
Ferson, S ;
Ginzburg, LR .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 1996, 54 (2-3) :133-144
[8]  
French Simon, 1986, DECISION THEORY INTR
[9]  
HERMANN A, 1999, 1999 ASME DES ENG TE
[10]  
Hurwicz L., 1951, Optimality criteria for decision-making under ignorance