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Selection for Rapid Manufacturing Under Epistemic Uncertainty
Author(s) -
Jamal O. Wilson,
David W. Rosen
Publication year - 2005
Publication title -
upt. syiah kuala university library (syiah kuala university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1115/detc2005-85264
Subject(s) - selection (genetic algorithm) , uncertainty quantification , computer science , epistemology , artificial intelligence , machine learning , philosophy
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.Copyright © 2005 by ASME

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