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contributor authorLi Chen
contributor authorFengfeng (Jeff) Xi
contributor authorAshish Macwan
date accessioned2017-05-09T00:17:01Z
date available2017-05-09T00:17:01Z
date copyrightFebruary, 2005
date issued2005
identifier issn1087-1357
identifier otherJMSEFK-27849#104_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/132225
description abstractPresented in this paper is a feature-based method for selecting an optimal (minimum yet sufficient) set of modules necessary to form a reconfigurable machine tool for producing a part family. This method consists of two parts. In the first part, a feature-module database is created to form a selection space, where the machinable geometric features identified in STEP are defined as functional requirements (FR’s) and the structural component modules derived from the conventional machine tools as design parameters (DP’s). An inner FR-to-DP mapping mechanism within the database is based on the “Membership Grade Matrix,” which defines metrics to quantify the degree of association between a FR and a DP. Within the confines of the selection space built upon this FR-DP database, the second part of the method involves a two-step procedure for module selection. The first step is to select the modules from this space to construct all the required individual configurations of the reconfigurable machine tool. The second step is to maximize the number of common modules among the originally selected modules through re-selection. A case study on designing a reconfigurable machine tool dedicated to a given family of die molds is conducted and discussed.
publisherThe American Society of Mechanical Engineers (ASME)
titleOptimal Module Selection for Preliminary Design of Reconfigurable Machine Tools
typeJournal Paper
journal volume127
journal issue1
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.1826075
journal fristpage104
journal lastpage115
identifier eissn1528-8935
keywordsMachinery
keywordsMachining
keywordsMachine tools
keywordsDesign AND Databases
treeJournal of Manufacturing Science and Engineering:;2005:;volume( 127 ):;issue: 001
contenttypeFulltext


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