This paper derives the process window from quantitative process models. Multi-dimensional clipping algorithms are developed that operate on half-spaces defined from the quality specifications. The resulting polytope is difficult to directly interpret. To support interactive tuning and optimization of manufacturing processes, three types of graphical matrices are presented to the decision maker: (1) the function matrix describes the relations between the process parameters and the manufactured part quality attributes; (2) the process space illustrates the feasible processing space constrained by the product quality specifications; (3) the performance space provides the feasible region of the part quality attributes and the Pareto Optimal set corresponding to the processing space. Optimization of optical media manufacturing is presented to demonstrate the use of the process window to locate a feasible solution and proceed to a desired trade-off of multiple quality attributes.

1.
Moray
,
N.
,
Lootsteen
,
P.
, and
Pajak
,
J.
,
1986
, “
Acquisition of Process Control Skills
,”
IEEE Trans. Syst. Man Cybern.
,
SMC-16
(
4
), pp.
497
504
.
2.
Kuo
,
T.
, and
Mital
,
A.
,
1993
, “
Quality Control Expert Systems. A Review of Pertinent Literature
,”
Journal of Intelligent Manufacturing
,
4
(
4
), pp.
245
245
.
3.
Mather
,
H.
,
McKee
,
K.
,
Kaewert
,
J. W.
,
Frost
,
J. M.
,
McKee
,
K.
,
Franklin
,
G. F.
, and
Sinha
,
A.
,
1991
, “
Developing Expert Systems for Manufacturing
,”
Appl. Mech. Rev.
,
44
(
2
),
B28
B28
.
4.
Al-Sultan
,
K. S.
, and
Al-Fawzan
,
M. A.
,
1998
, “
Determination of the Optimal Process Means and Production Cycles for Multistage Production Systems Subject to Process Deterioration
,”
Production Planning and Control
,
9
(
1
), pp.
66
73
.
5.
Cass
,
R.
, and
Depietro
,
J.
,
1998
, “
Computational Intelligence Methods for Process Discovery
,”
Eng. Applic. Artif. Intell.
,
11
(
5
), pp.
675
681
.
6.
Luftig, J. T., and Jordan, V. S., 1998, Design of Experiments in Quality Engineering, McGraw-Hill, New York.
7.
Kim
,
J. S.
, and
Larsen
,
M.
,
1996
, “
Improving Quality with Integrated Statistical Tools
,”
Medical Device and Diagnostic Industry
,
18
(
10
), pp.
78
83
.
8.
Huang
,
S. H.
, and
Zhang
,
H.-C.
,
1994
, “
Artificial Neural Networks in Manufacturing: Concepts, Applications, and Perspectives
,”
IEEE Trans. Compon., Packag. Manuf. Technol., Part A
,
17
(
2
), pp.
212
228
.
9.
Zorriassatine
,
F.
, and
Tannock
,
J. D. T.
,
1998
, “
Review of Neural Networks for Statistical Process Control
,”
Journal of Intelligent Manufacturing
,
9
(
3
), pp.
209
224
.
10.
Ivester, R., Danai, K., and Kazmer, D., 1998, “Automatic Tuning of Injection Molding by the Virtual Search Method,” Society of Plastics Engineers’ Annual Technical Conf., ANTEC, pp. 362–366.
11.
Rinderle, J. R., and Krishnan, V., 1990, “Constraint Reasoning in Concurrent Design,” ASME, Design Technical Conference on Design Theory and Methodology, Chicago, IL.
12.
Thornton, A. C., 1999, “Variation Risk Management using Modeling and Simulation,” submitted ASME J. Mech. Des.
13.
Kusiak
,
A.
,
Wang
,
J.
, and
He
,
D. W.
,
1996
, “
Negotiation in Constraint-Based Design
,”
ASME J. Mech. Des.
,
118
(
4
), pp.
470
477
.
14.
Sutherland
,
I. E.
, and
Hodgman
,
G. W.
,
1974
, “
Reentrant Polygon Clipping
,”
Commun. ACM
,
17
(
1
), pp.
32
42
.
15.
Keeney, R. L., and Raiffa, H., 1993, Decisions With Multiple Objectives: Preferences and Value Tradeoffs, Cambridge University Press, Cambridge [England]; New York, NY.
16.
Nazareth, J. L., 1987, Computer Solutions of Linear Programs, Oxford University Press.
17.
Hatch, D. P., 2000, “Development of Transfer Functions for Optical Media,” MS, University of Massachusetts Amherst, Amherst, MA.
18.
Oshiro, T., Goto, T., and Ishibashi, J., 1997, “Experimental Study of DVD Substrate Quality by Operating Conditions in Injection Molding,” Annual Technical Conference—ANTEC, Conference Proceedings, Toronto, Can, pp. 410–414.
19.
Park, S. J., Han, J. H., Ryim, W. G., Chang, S. K., Kim, J. H., Kang, T. G., Heo, B. S., and Kwon, T. H., 1998, “Numerical Analysis of Injection/Compression Molding Process for Center-Gated Disc,” Annual Technical Conference—ANTEC, Conference Proceedings, Atlanta, Ga, pp. 1756–1759.
20.
Shin, J. W., Rhee, D. C., and Park, S. J., 1998, “Experimental Study of Optical Disc Birefringence,” Annual Technical Conference—ANTEC, Conference Proceedings, Atlanta, Ga, pp. 1753–1755.
21.
Myers
,
R. H.
,
Khuri
,
A. I.
, and
Carter
,
Walter H.
, Jr.
,
1989
, “
Response Surface Methodology: 1966–1988
,”
Technometrics
31
(
2
), pp.
137
157
.
22.
Neter, J., Kutner, M. H., Nachtshem, C. J., and Wasserman, W., 1996, Applied Linear Statistical Models, Irwin, Chicago.
23.
Parkinson
,
A.
,
Sorensen
,
C.
, and
Pourhassan
,
N.
,
1993
, “
A General Approach for Robust Optimal Design
,”
Transactions of the ASME
,
115
, pp.
74
80
.
24.
Chen
,
W.
,
Allen
,
J. K.
,
Tsui
,
K.-L.
, and
Mistree
,
F.
,
1996
, “
A Procedure for Robust Design: Minimizing Variance Caused by Noise Factors and Control Factors
,”
Trans. ASME
,
118
, pp.
478
485
.
25.
Taguchi, G. I., 1993, Taguchi on Robust Technology Development: Bringing Quality Engineering Upstream, ASME Press, New York.
26.
Bras
,
B.
, and
Mistree
,
F.
,
1995
, “
A Compromise Decision Support Problem for Axiomatic and Robust Design
,”
ASME J. Mech. Des.
,
117
(
1
), pp.
10
19
.
27.
Suh, N. P., Bell, A. C., and Gossard, D. C., 1977, “On an Axiomatic Approach to Manufacturing and Manufacturing Systems,” American Society of Mechanical Engineers Winter Annual Meeting.
28.
Yang, D., Hatch, D., Kazmer, D., and Danai, K., 1999, “Yield Maximization in Injection Molding by the Virtual Search Method,” Annual Technical Conference—ANTEC, Conference Proceedings, New York, NY, pp. 362–366.
29.
Akao, Y., 1990, Quality Function Deployment; Integrating Customer Requirements Into Product Design, Booknews, Inc.
You do not currently have access to this content.