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Dimensional variation modeling and a...
~
Wang, Haixia.
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Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage./
Author:
Wang, Haixia.
Description:
172 p.
Notes:
Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 3378.
Contained By:
Dissertation Abstracts International67-06B.
Subject:
Engineering, Automotive. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3222813
ISBN:
9780542753107
Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage.
Wang, Haixia.
Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage.
- 172 p.
Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 3378.
Thesis (Ph.D.)--The University of Wisconsin - Madison, 2006.
This thesis presents a methodology for dimensional variation design at a preliminary design stage with consideration of multi-station assembly with compliant parts. The methodology allows a robust assembly system design, which is less sensitive to part and tool variations, by developing the following four key research components.
ISBN: 9780542753107Subjects--Topical Terms:
1018477
Engineering, Automotive.
Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage.
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Dimensional variation modeling and analysis for multi-station compliant assemblies at a preliminary design stage.
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172 p.
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Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 3378.
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Adviser: Dariusz Ceglarek.
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Thesis (Ph.D.)--The University of Wisconsin - Madison, 2006.
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This thesis presents a methodology for dimensional variation design at a preliminary design stage with consideration of multi-station assembly with compliant parts. The methodology allows a robust assembly system design, which is less sensitive to part and tool variations, by developing the following four key research components.
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1. Graph-based assembly modeling framework for dimensional variation control, which includes hierarchical and unified representation of product and process using the concept of topological CAD data structure. The developed graph-based assembly model has the capability to: (i) model k-ary assemblies (generalization of binary assemblies); (ii) model variation propagation for multi-station compliant assemblies; and (iii) integrate variation design with existing CAD data structure.
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2. k-piece graph and k-piece mixed graph model, which expands line graph operation used in graph theory, and generalizes liaisons graph and datum flow chain representation of assembly by including representation of all feasible subassemblies. The developed k-piece graph and k-piece mixed graph model is applied to sequence generation of k-ary assemblies which expands existing methods for binary sequence generation.
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3. Beam-based variation propagation model for multi-station assembly with compliant parts at a preliminary design stage, which includes beam model and variation propagation model. The beam model includes representation of part geometry and material property, part-to-part mating features, and part locating features. The variation propagation model represents error propagation along with four operations within a single station and integrates it within a multi-station system using state transition model.
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4. Quality-driven Sequence Planning (Q/SP), which integrates 1--3 and allows the evaluation of assembly sequences based on product dimensional quality criteria. The Q/SP is formulated as a discrete optimization problem, and the sequences are evaluated based on the multivariate process capability index.
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A major advantage of the developed methodology is that it allows for variation analysis of k-ary assemblies with compliant parts at preliminary design stage. This allows prompt identification analysis of dimensional failures and reduction of necessary engineering changes in early design stage.
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School code: 0262.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3222813
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