Optimal process design of two-stage multiple responses grinding processes using desirability functions and metaheuristic technique

Applied Soft Computing Journal

Volumn 8, Issue 1, 2008, Pages 402-421

  Mukherjee, Indrajit ^a   Ray, Pradip Kumar ^b  

^a BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Desirability function; Honing; Mahalanobis distance; Metaheuristic; Modified Tabu search; Multivariate regression; Two stage grinding

Indexed keywords

GRINDING (COMMINUTION); HEURISTIC ALGORITHMS; METADATA; PROBLEM SOLVING; STATISTICAL METHODS; TABU SEARCH;

DESIRABILITY FUNCTION; MAHALANOBIS DISTANCE; METAHEURISTIC; MODIFIED TABU SEARCH; MULTIVARIATE REGRESSION; TWO-STAGE GRINDING;

PROCESS CONTROL;

EID: 34548506514     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2007.02.005     Document Type: Article

References (57)

1. Luong L.H.S., and Spedding T.A. A neural-network system for predicting machining behaviour. J. Mater. Process. Technol. 52 (1995) 585-591
2. Shin Y.C., and Vishnupad P. Neuro-fuzzy control of complex manufacturing processes. Int. J. Prod. Res. 34 12 (1996) 3291-3309
3. Chen Y.T., and Kumara S.R.T. Fuzzy logic and neural network for design of process parameters: a grinding process application. Int. J. Prod. Res. 36 2 (1998) 395-415
4. Rumelhart D.E., Hinton G.E., and Williams R.J. Learning representations by back-propagating errors. Nature 323 9 (1986) 533-536
5. Sathyanarayanan G., Lin I.J., and Chen M. Neural network modelling and multiobjective optimization of creep feed grinding of superalloys. Int. J. Prod. Res. 30 10 (1992) 2421-2438
6. Jain R.K., Jain V.K., and Kalra P.K. Modelling of abrasive flow machining process: a neural network approach. Wear 231 (1999) 242-248
7. Feng C., Wang X., and Yu Z. Neural networks modelling of honing surface roughness parameter defined by ISO 13565. SIAM J. Manuf. Syst. 21 8 (2002) 1-35
8. Kim J.D., and Choi M.S. Stochastic approach to experimental analysis of cylindrical lapping process. Int. J. Mach. Tools Manuf. 35 1 (1995) 51-59
9. Ross P.J. Taguchi Techniques for Quality Engineering (1989), McGraw-Hill Book Company
10. Prusak Z., Webster J.A., and Marinescu I.D. Influence of dressing parameters on grinding performance of CBN/seeded gel hybrid wheels in cylinder grinding. Int. J. Prod. Res. 35 10 (1997) 2899-2915
11. Montgomery D.C. Design and Analysis of Experiment. 5th ed. (2001), Wiley & sons Inc., New York
12. Brinksmeier E., Tonshoff H.K., Czenkusch C., and Heinzel C. Modelling and optimization of grinding process. J. Intell. Manuf. 9 (1998) 303-314
13. Petri K.L., Billo R.E., and Bidanda B. A neural network process model for abrasive flow machining operations. J. Manuf. Sci. 17 1 (1998) 52-64
14. Lee C.W., and Shin Y.C. Evolutionary modelling and optimization of grinding processes. Int. J. Prod. Res. 38 12 (2000) 2787-2831
15. Saravanan R., and Sachithanandam M. Genetic algorithm (GA) for multivariable surface grinding process optimization using multi-objective function model. Int. J. Adv. Manuf. Technol. 17 (2001) 330-338
16. Singh S., Shan H.S., and Pradeep K. Parametric optimization of magnetic field assisted abrasive flow machining by the Taguchi method. Qual. Reliab. Eng. Int. 18 (2002) 273-283
17. Shaji S., and Radhakrisnan V. Analysis of process parameters in surface grinding with graphite as lubricant based on Taguchi method. J. Mater. Process. Technol. (2003) 1-9
18. Mitra K., and Gopinath R. Multiobjective optimization of an industrial grinding operation using elitist nondominated sorted genetic algorithm. Chem. Eng. Sci. 59 (2004) 385-396
19. Baskar N., Saravanan R., Asokan P., and Prabhaharan G. Ants colony algorithm approach for multi-objective optimization of surface grinding operations. Int. J. Adv. Manuf. Technol. 23 (2004) 311-317
20. Kwak J. Application of Taguchi and response surface methodologies for geometric error in surface grinding process. Int. J. Mach. Tools Manuf. 45 (2005) 327-334
21. Harrington Jr. E.C. The desirability function. Ind. Qual. Cont. (1965) 494-498
22. Kim K.J., and Lin D.K.J. Simultaneous optimization of mechanical properties of steel by maximizing exponential desirability functions. Appl. Stat. 49 3 (2000) 311-325
23. Derringer G.C., and Suich R. Simultaneous optimization of several response variables. J. Qual. Technol. 12 4 (1980) 214-219
24. Derringer G.C. A balancing act: optimizing a product's properties. Qual. Prog. (1994) 51-57
25. Rencher A.C. Method of Multivariate Analysis (1995), John Wiley & Sons, Inc., USA
26. Khuri A.I., and Conlon M. Simultaneous optimization of multiple responses represented by polynomial regression functions. Technometrics 23 (1981) 363-375
27. Glover F., and Greenberg H.J. New approach for heuristic search: a bilateral linkage with artificial intelligence. Eur. J. Oper. Res. 39 (1989) 119-130
28. Goldberg D.E. Genetic Algorithms. Search Optim. Mach. Learn. (2002), Pearson Education, Inc, Delhi, India
29. Haupt R.L., and Haupt S.E. Practical Genetic Algorithms (1998), John Wiley & Sons, Inc., NY
30. Kirkpatrick K., Gelett Jr. C.D., and Vecchi M.P. Optimization by simulated annealing. Sciences 220 (1983) 671-680
31. Aarts E., and Korst J. Simulated annealing and boltzmann machines (1989), John Wiley & Sons, NY
32. Henderson D., Jacobson S.H., and Johnson A.W. In: Glover F., and Kochenberger G.A. (Eds). Handbook of Metaheuristics (2003), Kluwer Academic Publisher, NY 288-319
33. Bohachevsky I.O., Johnson M.E., and Stein M.L. Generalized simulated annealing for function optimization. Technometrics 28 3 (1986) 209-217
34. Fleischer M. Simulated annealing: past, present, and future. Proceedings of the Winter Simulation Conference (1995) 155-161
35. Eglese R.W. Simulated annealing: a tool for operational research. Eur. J. Oper. Res. 46 (1990) 271-281
36. Glover F. Tabu search-part I. ORSA J. Comput. 1 (1989) 190-206
37. Glover F. Tabu search-part II. ORSA J. Comput. 2 1 (1990) 4-32
38. Glover F. Tabu search: a tutorial. Interface 20 (1990) 74-94
39. Glover F. Tabu search for nonlinear and parameter optimization (with links to genetic algorithm). Discrete Appl. Math. 49 (1994) 213-255
40. Glover F. Tabu search-wellsprings and challenges. Eur. J. Oper. Res. 106 (1998) 221-225
41. Glover F., and Laguna M. Tabu Search. 6th print (2002), Kluwer Academic Publisher, London
42. Cvijovic D., and Klinowski J. Taboo search: an approach to the multiple minima problem. Science 267 (1995) 664-666
43. Werra de.D., and Hertz A. Tabu search techniques. OR Spectrum (1989) 131-141
44. Glover F., and Marti R. Fundamentals of scatter search and path relinking. Control Cybern. 29 3 (2000) 653-684
45. Mahalanobis P. On the Generalized Distance in Statistics vol. 2 (1936), Proceedings of the Indian National Institute Science, Calcutta, India pp. 49-55
46. De Maesschalck R., Jouan-Rimbaud, and Massart D.L. Tutorial-the mahalanobis distance. Chemo Metrics Intell. Lab. Syst. 50 (2000) 1-18
47. Lokketangen A., and Glover F. Solving zero-one mixed integer programming problems using Tabu search. Eur. J. Oper. Res. 106 (1998) 624-658
48. S. Adra, K. Bogdanov, I. Griffin, Optimization Techniques for Gas Turbine Engine Control Systems (MSC Dissertation Final Report. University of Sheffield, Department of Computer Science, 2003).
49. Gendreau M. An introduction to Tabu search. In: Glover F., and Kochenberger G.A. (Eds). Handbook of Metaheuristics (2003), Kluwer Academic Publisher, NY 37-54
50. L. Tao, Research Incubator: Combinatorial Optimization. (A Technical Report. Pace University, 2004).
51. Coit D.W., Jackson B.T., and Smith A.E. Static neural network process models: considerations and case studies. Int. J. Prod. Res. 36 11 (1998) 2953-2967
52. Montgomery D.C. Introduction to Statistical Quality Control. 2nd ed. (1990), John Wiley & Sons, New York
53. Box G.E.P., and Cox D.R. An analysis of transformations. J. Royal Stat. Soc. Series B 26 (1964) 211-252
54. Krzanowski W.J. Principles of Multivariate Analysis: A User's Perspective (1988), Clarendon Press, Oxford Science Publication
55. Timm N.H. Applied Multivariate Analysis. Springer Text in Statistics (2002), Springer-Verlag Newyork Inc.
56. Barnett V., and Lewis T. Outlier in Statistical Data (1978), Wiley Publication, NY
57. Rencher A.C. Multivariate Statistical Inference and Applications (1998), John Wiley & Sons, Inc., New York