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Tolerance Synthesis Using Axiomatic Design

Authors: CAMPATELLI, GIANNI;

Tolerance Synthesis Using Axiomatic Design

Abstract

This paper introduces a new approach based on Axiomatic Design to simplify the process of Tolerance Synthesis. The main advantage of this approach is to include easily all the information needed for the Tolerance Synthesis in the classical AD framework. The information that must be stored in the design matrices are mainly related to the production cost vs. tolerance curves and the tolerance chain, needed for the synthesis phase. The Tolerance Synthesis is nowadays one of the most proficient ways to reduce the cost of machined parts but its diffusion is limited by two main issues. First, the information needed for the synthesis are complex and have a difficult management. Second, there is a cultural limit because often a concurrent approach is not fully used, especially by small and medium enterprises (SMEs), and often the tolerances are decided by the designers while the manufacturing process (and so the cost) is chosen by the process engineer. Both these issues could be solved by the use of Axiomatic Design resulting in a greater use of such approach, especially for SMEs. The approach developed introduces a cross level matrix to represent effectively the tolerance chain of the product and the idea to store the cost-tolerance function as terms of the DPs-PVs design matrix. The model developed has been applied to an industrial case study.

Country
Italy
Related Organizations
Keywords

Axiomatic Design; Tolerance Optimization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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