Research Papers

Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods

[+] Author and Article Information
Wenzhen Huang

Department of Mechanical Engineering, University of Massachusetts, Dartmouth, MA 02747whuang@umassd.edu

Zhenyu Kong

School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK 74078james.kong@okstate.edu

Abishek Chennamaraju

Deparment of Mechanical Engineering, University of Massachusetts, Dartmouth, MA 02747

J. Comput. Inf. Sci. Eng 10(4), 041001 (Nov 04, 2010) (11 pages) doi:10.1115/1.3503880 History: Received January 09, 2009; Revised April 06, 2010; Published November 04, 2010; Online November 04, 2010

Fixture layout robust design of multistation manufacturing systems aims for an optimal design that enables the dimensional variation of a product insensitive to the variations of process variables in the manufacturing process. The robust design involves a high dimension and complex global optimization problem. Recent advances in stream of variation modeling techniques enable effective formulation of the optimization problem at the system level. However, there is a challenge of computation complexity in terms of searching optimal design parameters in a high dimension, nonconvex, and discontinuous design space. This makes many available algorithms ineffective or even invalid. In this paper, an alternative sequential space filling strategy is proposed, which adopts sampling approaches to search optimal designs. To improve computation efficiency, the search space is sequentially reduced to generate a series of subspaces, and a method is designed to ensure a complete coverage of these subspaces in the original feasible space. In order to validate the proposed method, a floor pan assembly from an automotive body assembly process is modeled, and then the fixture robust design is conducted with the developed methods. To show the effectiveness of the proposed method, genetic algorithm and sequential quadratic programming are also applied in the case study for comparison.

Copyright © 2010 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Figure 1

Evenly spaced grid sampling

Grahic Jump Location
Figure 2

Fixture locating scheme

Grahic Jump Location
Figure 3

(a) Two-way pin/slot and (b) four-way pin/hole pairs

Grahic Jump Location
Figure 4

Fixture locators in an assembly

Grahic Jump Location
Figure 5

An irregular feasible region

Grahic Jump Location
Figure 6

Procedure of sequential space filling sampling for optimization

Grahic Jump Location
Figure 7

Sequential space filling strategies: (a) COC shrinking and (b) CC shrinking

Grahic Jump Location
Figure 8

Floor pan assembly process and assembly tree

Grahic Jump Location
Figure 9

Schematic of a floor pan assembly process

Grahic Jump Location
Figure 10

Left and right floor pans and locator nominal locations

Grahic Jump Location
Figure 11

Minimum sensitivity and computation time in single run SFS

Grahic Jump Location
Figure 12

Minimum sensitivity computation time in SSF

Grahic Jump Location
Figure 13

Optimization by genetic algorithm (population=300, generation=25)

Grahic Jump Location
Figure 14

Optimization by SQP method

Grahic Jump Location
Figure 15

(a) Rastrigin’s function and (b) GA convergence process




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In