Hybrid of Hunting Search and Modified Simplex Methods for Grease Position Parameter Design Optimisation
This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
[1] P. Kanchanasuttisang and P. Luangpaiboon, "Sequential Multiple
Response Optimization for Manufacturing Flexible Printed Circuit", Am.
J. Applied Sci., vol. 9, No.5, pp. 772-778. DOI:
10.3844/ajassp.2012.772.778, 2012.
[2] P.M. Cann, J.P. Doner, M.N. Webster and V. Wikstrom, "Grease
Degradation in Rolling Element Bearings," Tribology Transactions, vol.
44, no. 3, pp. 399-404, 2001.
[3] M.T.V. Zoelen, C.H. Venner and P.M. Lugt, "Free Surface Thin Layer
Flow in Bearings Induced by Centrifugal Effects," Tribology
Transactions, vol. 53, no. 3, pp. 297-307, 2010.
[4] H. Lin, J.G. Sun and Y.M. Zhang, " Theorem proving based on the
extension rule," Journal of Automated Reasoning, vol. 31, pp. 11-21,
2003.
[5] J.G. Zhou, D. Herscovici and C.C. Chen, "Parametric process
optimisation to improve the accuracy of rapid prototyped stereo
lithography parts," International Journal of Machine Tools and
Manufacture, vol. 40, pp. 363-379, 2000.
[6] C.M. Hsu, "An integrated approach to enhance the optical performance
of couplers based on neural networks, desirability functions and tabu
search,"International Journal of Production Economics, vol. 92, pp.
241-254, 2004.
[7] I. Mukherjee and P.K. Ray, "Optimal process design of two-stage
multiple responses grinding processes using desirability functions and
metaheuristic technique," Applied Soft Computing, vol. 8, pp. 402-421,
2008.
[8] Q.H. Zhao, D. Urosevic, N. Mladenovic and P. Hansen, "A restarted and
modified simplex search for unconstrained optimisation," Computers
and Operations Research, vol. 36, 3263-3271, 2009.
[9] A. Kamoun, M. Jaziri and M. Chaabouni, "The use of the simplex
method and its derivatives to the on-line optimisation of the parameters
of an injection moulding process," Chemometrics and Intelligent
Laboratory Systems, vol. 96, pp. 117-122, 2009.
[10] H.C. Kuo, J.R. Chang and K.S. Shyu, "A hybrid algorithm of evolution
and simplex methods applied to global optimisation," Journal of Marine
Science and Technology, vol. 12, pp. 280-289, 2004.
[11] P. Luangpaiboon, "Variable Neighborhood Simplex Search Methods for
Global Optimisation Models", Journal of Computer Science, vol. 8, no.
4, pp. 613-620, 2012.
[12] R. Oftadeh, M.J. Mahjoob and M. Shariatpanahi, "A novel metaheuristic
optimisation algorithm inspired by group hunting of animals:
Hunting search," Computers and Mathematics with Applications, vol.
60, pp. 2087-2098, 2010.
[1] P. Kanchanasuttisang and P. Luangpaiboon, "Sequential Multiple
Response Optimization for Manufacturing Flexible Printed Circuit", Am.
J. Applied Sci., vol. 9, No.5, pp. 772-778. DOI:
10.3844/ajassp.2012.772.778, 2012.
[2] P.M. Cann, J.P. Doner, M.N. Webster and V. Wikstrom, "Grease
Degradation in Rolling Element Bearings," Tribology Transactions, vol.
44, no. 3, pp. 399-404, 2001.
[3] M.T.V. Zoelen, C.H. Venner and P.M. Lugt, "Free Surface Thin Layer
Flow in Bearings Induced by Centrifugal Effects," Tribology
Transactions, vol. 53, no. 3, pp. 297-307, 2010.
[4] H. Lin, J.G. Sun and Y.M. Zhang, " Theorem proving based on the
extension rule," Journal of Automated Reasoning, vol. 31, pp. 11-21,
2003.
[5] J.G. Zhou, D. Herscovici and C.C. Chen, "Parametric process
optimisation to improve the accuracy of rapid prototyped stereo
lithography parts," International Journal of Machine Tools and
Manufacture, vol. 40, pp. 363-379, 2000.
[6] C.M. Hsu, "An integrated approach to enhance the optical performance
of couplers based on neural networks, desirability functions and tabu
search,"International Journal of Production Economics, vol. 92, pp.
241-254, 2004.
[7] I. Mukherjee and P.K. Ray, "Optimal process design of two-stage
multiple responses grinding processes using desirability functions and
metaheuristic technique," Applied Soft Computing, vol. 8, pp. 402-421,
2008.
[8] Q.H. Zhao, D. Urosevic, N. Mladenovic and P. Hansen, "A restarted and
modified simplex search for unconstrained optimisation," Computers
and Operations Research, vol. 36, 3263-3271, 2009.
[9] A. Kamoun, M. Jaziri and M. Chaabouni, "The use of the simplex
method and its derivatives to the on-line optimisation of the parameters
of an injection moulding process," Chemometrics and Intelligent
Laboratory Systems, vol. 96, pp. 117-122, 2009.
[10] H.C. Kuo, J.R. Chang and K.S. Shyu, "A hybrid algorithm of evolution
and simplex methods applied to global optimisation," Journal of Marine
Science and Technology, vol. 12, pp. 280-289, 2004.
[11] P. Luangpaiboon, "Variable Neighborhood Simplex Search Methods for
Global Optimisation Models", Journal of Computer Science, vol. 8, no.
4, pp. 613-620, 2012.
[12] R. Oftadeh, M.J. Mahjoob and M. Shariatpanahi, "A novel metaheuristic
optimisation algorithm inspired by group hunting of animals:
Hunting search," Computers and Mathematics with Applications, vol.
60, pp. 2087-2098, 2010.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:56832", author = "P. Luangpaiboon and S. Boonhao", title = "Hybrid of Hunting Search and Modified Simplex Methods for Grease Position Parameter Design Optimisation", abstract = "This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.", keywords = "Grease Position Process, Multi-response Surfaces,
Modified Simplex Method, Hunting Search Method, Desirability
Function Approach.", volume = "7", number = "1", pages = "57-7", }