A chart allocation strategy for multistage processes

IIE Transactions (Institute of Industrial Engineers)

Volumn 41, Issue 9, 2009, Pages 790-803

  Jin, Ming ^a   Tsung, Fugee ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Average time to signal; Chart allocation; Multistage process

Indexed keywords

ALLOCATION STRATEGY; AUTOMOTIVE ASSEMBLIES; AVERAGE TIME TO SIGNAL; CONTROL CHARTS; INHERENT STRUCTURES; MULTISTAGE MANUFACTURING; MULTISTAGE MANUFACTURING PROCESS; MULTISTAGE PROCESS; OUT-OF-CONTROL; POTENTIAL FAULTS; STRUCTURAL INFORMATION; STRUCTURAL PARAMETER;

DECISION MAKING; FAULT DETECTION; SIGNAL DETECTION;

STATISTICAL PROCESS CONTROL;

EID: 70749130581     PISSN: 0740817X     EISSN: 15458830     Source Type: Journal    
DOI: 10.1080/07408170902789068     Document Type: Article

References (45)

1. Apley, D. and Shi, J. (1998) Diagnosis of multiple fixture faults in panel assembly. Transactions of the ASME, Journal of Manufacturing Science and Engineering, 120, 793-801.
2. Ceglarek, D. and Shi, J. (1996) Fixture failure diagnosis for auto body assembly using pattern recognition. Transactions of the ASME, Journal of Engineering for Industry, 118, 55-65.
3. Ceglarek, D., Shi, J. and Wu, S.M. (1994) A knowledge-based diagnostic approach for the launch of the auto-body assembly process. Transactions of the ASME, Journal of Engineering for Industry, 116 491-499.
4. Crosier, R.B. (1988) Multivariate generalizations of cumulative sum quality-control schemes. Technometrics, 30, 291-303.
5. Dasgupta,T. andWu,C.F. (2006)Robust parameter designwith feedback control. Technometrics, 48, 349-361.
6. Denardo, E.V. (1982) Dynamic Programming-Models and Applications, Prentice-Hall. Englewood Cliffs, NJ.
7. Ding, Y., Ceglarek, D. and Shi, J. (2002) Fault diagnosis of multistage manufacturing processes by using state space approach. Transactions of the ASME, Journal of Manufacturing Science and Engineering, 124 313-322.
8. Ding, Y., Shi, J. and Ceglarek,D. (2002) Diagnosability analysis ofmultistationmanufacturing processes. Transactions of theASME, Journal of Dynamic Systems, Measurement and Control, 124, 1-33.
9. Djurdjanovic, D. and Ni, J. (2001) Linear state space modeling of dimensional machining errors. Transactions of NAMRI/SME, 29, 541-548.
10. Hawkins, D.M. (1991) Multivariate quality control based on regressionadjusted variables. Technometrics, 33, 61-75.
11. Hawkins, D.M.(1993)Regression adjustment for variables inmultivariate quality control. Journal of Quality Technology, 25, 170-182.
12. He, D. and Grigoryan, A. (2005) Multivariate multiple sampling charts. IIE Transactions, 37, 509-521.
13. Hotelling, H. (1947) Techniques of Statistical Analysis, McGraw Hill, New York.
14. Huang, Q., Zhou, S. and Shi, J. (2002) Diagnosis ofmulti-operationalmachining processes through variation propagation analysis. Robotics and CIM Journal, 18, 233-239.
15. Lawless, J.F., MacKay, R.J. and Robinson, J.A. (1999) Analysis of variation transmission in manufacturing processes - part I. Journal of Quality Technology, 31, 131-142.
16. Li, Y. and Tsung, F. (2009)False discovery rate-adjusted charting schemes for multistage process fault diagnosis and isolation. Technometrics, in press.
17. Lowry, C.A., Woodall, W.H., Champ, C.W. and Rigdon, S.E. (1992) A multivariate exponentially weighted moving average chart. Technometrics, 34, 46-53.
18. MacGregor, J.F., Jaeckle, C., Kiparissides, C. and Koutoudi, M. (1994) Process monitoring and diagnosis by multiblock PLS methods. AIChE Journal, 40, 826-838.
19. Molnau, W.E., Runger, G.C., Montgomery, D.C., Skinner, K.R. and Prabhu, S.S. (2001) A program for ARL calculation for multivariate EWMA charts. Journal of Quality Technology, 33, 515-21.
20. Molnau, W.E., Montgomery, D.C. and Runger, G.C. (2001) Statistically constrained designs of themultivariate exponentially weightedmoving average control chart. Quality and Reliability Engineering International, 17, 39-49.
21. Montgomery, D.C. (2001) Design and Analysis of Experiments. fifth edition, Wiley, New York, NY.
22. Prabhu, S.S. and Runger, G.C. (1997) Designing a multivariate EWMA control chart. Journal of Quality Technology, 29, 8-15.
23. Shamsuzzaman, M., Lam, Y.C. and Wu, Z. (2005) Control chart system with independent quality characteristics. International Journal of Advanced Manufacturing Technology, 26, 1298-1305.
24. Shu, L.J., Apley, D.W. and Tsung, F. (2003) Autocorrelated process monitoring using triggered CUSCORE charts. Quality and Reliability Engineering International, 18, 411-421.
25. Shu, L.J. and Tsung, F. (2003) On multistage statistical process control. Journal of the Chinese Institute of Industrial Engineers, 20, 1-8.
26. Shu, L.J., Tsung, F. and Kapur, K.C. (2004) Design of multiple causeselecting charts for multistage processes with model uncertainty. Quality Engineering, 16, 437-450.
27. Smilde, A.K., Westerhuis, J.A. and Boqué, R. (2000) Multiway multiblock component and covariates regression models. Journal of Chemometircs, 14, 301-331.
28. Smith, D.K. (1991) Dynamic Programming-A Practical Introduction, Ellis Horwood, Chichester, UK.
29. Stoumbos, Z.G., Reynolds, M.R., Ryan, T.P. and Woodall, W.H. (2000) The state of statistical process control as we proceed into the 21st century. Journal of the American Statistical Association, 95 992-998.
30. Stoumbos, Z.G. and Sullivan, J.H. (2002) Robustness to non-normality of the multivariate EWMA control chart. Journal of Quality Technology 34, 260-276.
31. Testik, M.C., Runger, G.C. and Borror, C.M. (2003) Robustness properties of multivariate EWMA control charts. Quality and Reliability Engineering International, 19, 31-38.
32. Tsung, F., Li, Y. and Jin, M. (2008) Statistical process control for multistage manufacturing and service operations: A review and some extensions. International Journal of Services Operations and Informatics, 3, 191-204.
33. Warwick, J. and Phelps, B. (1986) An application of dynamic programming to pattern recognition. The Journal of the Operational Research Society, 37, 35-40.
34. Woodall, W.H. and Montgomery, D.C. (1999) Research issues and ideas in statistical process control. Journal of Quality Technology, 31, 376-386.
35. Wu, C.F.J. and Hamada, M. (2000) Experiments Planning, Analysis, and Parameter Design Optimization. Wiley, New York, NY.
36. Xiang, L. and Tsung, F. (2008) Statistical monitoring of multistage processes based on engineering models. IIE Transactions, 40, 957-970.
37. Zhang, G.X. (1984) A new type of control charts and a theory of diagnosis with control charts, in World Quality Congress Transactions American Society for Quality Control, Milwaukee, WI, pp. 175-185.
38. Zhang,G.X. (1985) Cause-selecting control charts - a newtype of quality control charts. The QR Journal, 12, 221-225.
39. Zhang, G.X. (1989) A new diagnosis theory with two kinds of quality, in World Quality Congress Transactions, American Society for Quality Control, Milwaukee, WI, pp. 594-599.
40. Zhang, G.X. (1992) Cause-selecting control chart and diagnosis, theory and practice. Report. Aarhus School of Business, Aarhus, Denmark.
41. Zhang, S. and Wu, Z. (2006) Monitoring the process mean and variance using a weighted loss function CUSUM scheme with variable sampling intervals. IIE Transactions, 38, 377-387.
42. Zhou, S., Chen, Y. and Shi, J. (2004) Statistical estimation and testing for variation root-cause identification ofmultistage manufacturing processes. IEEE Transactions on Automation Science and Engineering 1(1), 73-83.
43. Zhou, S., Ding, Y., Chen, Y. and Shi, J. (2003) Diagnosability study of multistage manufacturing processes based on linear mixed-effects models. Technometrics, 45, 312-325.
44. Zhou, S., Huang Q. and Shi J. (2003) State space modeling of dimensional variation propagation in multistage machining process using differential motion vector. IEEE Transactions on Robotics and Automation, 19 296-309.
45. Zou, C., Tsung, F. and Liu, Y. (2008) A change point approach for phase I analysis in multistage processes. Technometrics, 50, 344-356.