Different sets of measurements carry different amounts of information about the root causes of quality problems in machining. The selection of measurements in multi-station machining systems is currently a slow and error-prone process based on expert human knowledge. In this paper, we propose systematic procedures for synthesizing measurement schemes that carry the most information about the root causes of dimensional machining errors. The amount of root cause information conveyed by a given set of measurements was assessed using the recently introduced formal methods for quantitative characterization of measurement schemes in multi-station machining systems. The newly proposed measurement scheme synthesis procedures were applied to devising measurement schemes in an automotive cylinder head machining process. It was observed that the measurement scheme synthesis procedure based on a genetic algorithm robustly outperformed the synthesis procedures based on the heuristics of successive measurement removal.
Issue Section:
Technical Papers
1.
Hu
, S.
, and Wu
, S. M.
, 1992
, “Identifying Root Causes of Variation in Auto-Body Assembly Using Principal Component Analysis
,” Transactions of NAMRI
, 20
, pp. 311
–316
.2.
Ceglarek
, D.
, Shi
, J.
, and Wu
, S. M.
, 1994
, “A Knowledge-Based Diagnostic Approach for the Launch of the Auto-Body Assembly Processes
,” ASME J. Eng. Ind.
, 116
, pp. 491
–499
.3.
Appley
, D.
, and Shi
, J.
, 1998
, “Diagnosis of Multiple Fixture Faults in Panel Assembly
,” ASME J. Manuf. Sci. Eng.
, 120
, pp. 793
–801
.4.
Huang, Q., Zhou, N., and Shi, J., 2000, “Stream of Variation Modeling and Diagnosis of Multi-Station Machining Processes,” Proc. of the ASME Int. Mech. Eng. Congress and Exposition, Orlando, FL, MED-11, pp. 81–88.
5.
Ford Motor Company, 1995, “Potential Failure Mode and Effects Analysis,” Prepared by: Environmental and Safety Engineering, Automotive Safety and Engineering Office.
6.
Cowan
, C. K.
, and Kovesi
, P. D.
, 1988
, “Automatic Sensor Placement for Vision Task Requirements
,” IEEE Trans. Pattern Anal. Mach. Intell.
, 10
, pp. 407
–416
.7.
Choi, W., 1996, “Computational Analysis of Three-Dimensional Measurement Data,” Ph.D. Thesis, Carnegie Mellon University, Pittsburgh, PA.
8.
Gupta, S., 1994, “Manufacturing Part Modeling for Automotive Spaceframe Extrusions,” Ph.D. Thesis, University of Maryland, Baltimore County, Baltimore, MD.
9.
Wang
, Y.
, and Nagarkar
, S. R.
, 1999
, “Locator and Sensor Placement for Automated Coordinate Checking Fixtures
,” ASME J. Manuf. Sci. Technol.
, 121
(4
), pp. 709
–719
.10.
Cai
, W.
, Hu
, S. J.
, and Woo
, T. C.
, 2001
, “Visibility Analysis and Synthesis for Assembly Fixture Certification Using Theodolite Systems
,” ASME J. Manuf. Sci. Eng.
, 123
, pp. 83
–89
.11.
Khan
, A.
, Ceglarek
, D.
, and Ni
, J.
, 1998
, “Sensor Location Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems
,” ASME J. Manuf. Sci. Eng.
, 120
, pp. 781
–792
.12.
Khan
, A.
, and Ceglarek
, D.
, 2000
, “Sensor Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems With Distributed Sensing
,” ASME J. Manuf. Sci. Eng.
, 122
, pp. 215
–226
.13.
Hu
, S. J.
, 1997
, “Stream of Variation Theory for Automotive-Body Assembly
,” CIRP Ann.
, 46
(1
), pp. 1
–6
.14.
Jin
, J.
, and Shi
, J.
, 1999
, “State-Space Modeling of Sheet Metal Assembly for Dimensional Control
,” ASME J. Manuf. Sci. Eng.
, 121
(4
), pp. 756
–762
.15.
Ding, Y., Ceglarek, D., and Shi, J., 2000, “Modeling and Diagnosis of Multistage Manufacturing Processes, Part I—State Space Modeling,” Proc. of the Japan-USA Symposium, Ann Arbor, MI.
16.
Ding, Y., Ceglarek, D., and Shi, J., 2000, “Modeling and Diagnosis of Multistage Manufacturing Processes, Part II—Fault Diagnosis,” Proc. of the Japan-USA Symposium, Ann Arbor, MI.
17.
Djurdjanovic
, D.
, and Ni
, J.
, 2001
, “Linear State Space Modeling of Dimensional Machining Errors
,” Trans. of NAMRI/SME
, 29
, pp. 541
–548
.18.
Djurdjanovic
, D.
, and Ni
, J.
, 2003
, “Dimensional Errors of Fixtures, Locating and Measurement Datum Features in the Stream of Variation Modeling in Machining
,” ASME J. Manuf. Sci. Eng.
, 125
, pp. 716
–730
.19.
Zhou
, S.
, Huang
, Q.
, and Shi
, J.
, 2003
, “State Space Modeling of Multi-Stage Machining Systems by Using Differential Motion Vector
,” IEEE Trans. Rob. Autom.
, 19
(2
), pp. 296
–309
.20.
Ding
, Y.
, Ceglarek
, D.
, and Shi
, J.
, 2002
, “Fault Diagnosis of Multi-Stage Manufacturing Processes by Using State Space Approach
,” ASME J. Manuf. Sci. Eng.
, 124
, pp. 313
–322
.21.
Dewilde, P., and Deprettere, E. F., 1998, “Singular Value Decomposition, An Introduction,” SVD and Signal Processing, Algorithms: Applications and Architectures, E. F. Deprettere, ed., Amsterdam, The Netherlands: Elsevier Science B.V., pp. 3–41.
22.
Huang
, Q.
, Zhou
, S.
, and Shi
, J.
, 2002
, “Diagnosis of Multi-Operational Machining Processes by Using State-Space Approach
,” Rob. Comput.-Integr. Manufact.
, 18
, pp. 233
–239
.23.
Djurdjanovic, D., and Ni, J., 2001, “Stream of Variation Based Analysis and Synthesis of Measurement Schemes in Multi-Station Machining Systems,” Proc. of the ASME Int. Mech. Eng. Congress and Exposition, New York City, NY.
24.
Ding
, Y.
, Shi
, J.
, and Ceglarek
, D.
, 2002
, “Diagnosability Analysis of Multi-Station Manufacturing Processes
,” ASME J. Dyn. Syst., Meas., Control
, 124
, pp. 1
–13
.25.
Zhou, S., Ding, Y., Chen, Y., and Shi, J., 2001, “Variance Components Analysis Methods for Diagnosability of Multi-Stage Manufacturing Systems,” submitted to Technometrics, in revision.
26.
Djurdjanovic
, D.
, and Ni
, J.
, 2003
, “Bayesian Approach to Measurement Scheme Analysis in Multi-Station Machining Systems
,” J. Eng. Manuf.
217
(B8
), pp. 1117
–1130
.27.
Djurdjanovic, D., and Ni, J., 2002, “Measurement Scheme Analysis in Multi-Station Machining Systems,” submitted to ASME J. Manuf. Sci. Eng., (also, Proc. International Conference on Frontiers of Design and Manufacturing, Dailian, P.R. China, Vol. 1, pp. 372–383).
28.
Holand, J. H., 1975, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI.
29.
Coley, D. A., 1999, An Introduction to Genetic Algorithms for Scientists and Engineers, World Scientific Co. Pte. Ltd.
30.
Rugh, W. J., 1996, Linear System Theory, Prentice Hall, pp. 462–476.
31.
Deutsch, R., 1965, Estimation Theory, Prentice Hall, Inc. Englewood Cliffs, NJ.
32.
Calafiore
, G.
, and El Ghaoui
, L.
, 2001
, “Robust Maximum Likelihood Estimation in the Linear Model
,” Automatica
, 37
(4
), pp. 573
–580
.33.
Fedorov, V. V., 1972, Theory of Optimal Experiments, Academic Press, New York, NY.
34.
Michalewicz
, Z.
, and Schoenauer
, M.
, 1996
, “Evolutionary Algorithms for Constrained Parameter Optimization Problems
,” Evol. Comput.
, 4
(1
), pp. 1
–32
.35.
Gruget, T., and Djurdjanovic, D., 2003, “Optimal Reduction of Measurements in an Existing Manufacturing Process,” Proc. of the CIRP Conference on Reconfigurable Manufacturing Systems, Ann Arbor, MI.
36.
Montgomery, D. C., 2001, Introduction to Statistical Quality Control, 4th edition, John Wiley and Sons, Inc.
37.
De Jong, K. A., 1975, “Analysis of the Behavior of a Class of Genetic Adaptive Systems,” Doctoral Dissertation, University of Michigan, Dissertation Abstracts International, Vol. 36(10), 5140B.
38.
Ba¨ck, T., 1996, Evolutionary Algorithms in Theory and Practice, Oxford University Press, New York City, NY.
39.
Wang, H.-P., 1991, Computer-Aided Process Planning, Elsevier, New York, NY.
40.
Reed
, M. K.
, and Alen
, P. K.
, 2000
, “Constraint Basd Sensor Planning for Scene Modeling
,” IEEE Trans. Pattern Anal. Mach. Intell.
, 22
(12
), pp. 1460
–1467
.41.
Udwadia
, F. E.
, 1994
, “Methodology for Optimum Sensor Locations for Parameter Identification in Dynamic Systems
,” J. Eng. Mech.
, 120
, pp. 368
–390
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