Fixturing plays an important role in the quality of metal fit-up for sheet metal assembly with laser welding. To reduce the sensitivity of the designed fixture configuration to location fluctuation, this paper provides a quality design of the fixture configuration for sheet metal laser welding. A generic robust design methodology, labeled the two-stage response surface methodology, is developed in the robust design model. The first stage is to find the Robust Design Space (RDS), in which robust solutions with higher degrees of insensitivity reside. Within the RDS, a second-order response surface model can be fitted by a 3k fractional factorial design in the second stage. Based on the resultant response model, the robust fixturing scheme and the influential design locators can be obtained by an optimization and a statistical screening techniques. The degree of metal fit-up is taken as the performance characteristic of the robust design. An example illustrates how the robust design method effectively meets the quality requirements of the fixturing design.

1.
Havrilla, D., 1996, Laser Welding Design and Process Fundamentals and Troubleshooting Guideline, Rofin-Sinar, Incorporated.
2.
Rossler, M. D., and Uddin, M. N., 1996, “Lasers in the Automotive Industry,” Proceeding of SPIE- the International Society for Optical Engineering, J. J. Dubowski, ed., San Jose, California, Vol. 2703, pp. 194-201.
3.
Ma
,
W.
,
Lei
,
Z.
, and
Rong
,
Y.
,
1998
, “
FIX-DES: A Computer-Aided Modular Fixture Configuration Design System
,”
International Journal of Advanced Manufacturing Technology
,
14
, pp.
21
32
.
4.
Asada
,
H.
, and
By
,
A. B.
,
1985
, “
Kinematic Analysis of Workpiece Fixturing for Flexible Assembly with Automatically Reconfigurable Fixtures
,”
IEEE Journal of Robotics and Automation
RA-1
(
2
), pp.
86
94
.
5.
Rearick, M. R., Hu, S. J., and Wu, S. M., 1993, “Optimal Fixture Design for Deformable Sheet Metal Workpieces,” Transactions of NAMRI/SME, Vol. XXI, pp. 407–412.
6.
Cai
,
W.
,
Hu
,
S. J.
, and
Yuan
,
J. X.
,
1996
, “
Deformable Sheet Metal Fixturing: Principles, Algorithms, and Simulation
,”
ASME J. Manuf. Sci. Eng.
,
118
, pp.
318
331
.
7.
Li
,
B.
,
Shiu
,
B. W.
, and
Lau
,
K. J.
,
2001
, “
Principle and Simulation of Fixture Configuration Design for Sheet Metal Assembly with Laser Welding, Part I: Finite Element Modeling and A Prediction and Correction Method
,”
International Journal of Advanced Manufacturing Technology
,
18
, pp.
266
275
.
8.
Li
,
B.
, and
Shiu
,
B. W.
,
2000
, “
Principle and Simulation of Fixture Configuration Design for Sheet Metal Assembly With Laser Welding, Part II: Optimal Configuration Design with Genetic Algorithm
,”
International Journal of Advanced Manufacturing Technology
,
18
, pp.
276
284
.
9.
Tsui
,
K. L.
,
1992
, “
An Overview of Taguchi Method and Newly Developed Statistical Methods for Robust Design
,”
IIE Transaction
,
24
(
5
), pp.
44
57
.
10.
Yang
,
W. H.
, and
Tarng
,
Y. S.
,
1998
, “
Design Optimization of Cutting Parameters for Turning Operations Based On the Taguchi Method
,”
J. Mater. Process. Technol.
,
84
, pp.
122
129
.
11.
Parkinson
,
A.
,
1995
, “
Robust Mechanical Design Using Engineering Models
,”
ASME J. Mech. Des.
116
, pp.
48
53
.
12.
Parkinson
,
A.
,
Sorensen
,
C.
, and
Pourhassan
,
N.
,
1993
, “
A General Approach for Robust Optimal Design
,”
ASME J. Mech. Des.
,
115
, pp.
74
79
.
13.
Lewis
,
L.
, and
Parkinson
,
A.
,
1994
, “
Robust Optimal Design Using A Second-Order Tolerance Model
,”
ASME J. Mech. Des.
6
, pp.
25
37
.
14.
Plante
,
Robert D.
,
1999
, “
Multicriteria Models for the Allocation of Design Parameter Targets
,”
European Journal of Operational Research
,
115
, pp.
98
112
.
15.
Kunjur
,
A.
, and
Krishnamurty
,
S.
,
1997
, “
A Robust Multi-criteria Optimization Approach
,”
Mech. Mach. Theory
,
32
(
7
), pp.
797
810
.
16.
Cai
,
W.
,
Hu
,
S. J.
, and
Yuan
,
J. X.
,
1997
, “
A Variational Method of Robust Fixture Configuration Design for 3-D Workpieces
,”
ASME J. Manuf. Sci. Eng.
,
119
, pp.
593
602
.
17.
Montgomery, Douglas C., 1995, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley & Sons Inc., New York.
You do not currently have access to this content.