Determination of the Proper Quality Costs Parameters via Variable Step Size Steepest Descent Algorithm
This paper presents the determination of the proper
quality costs parameters which provide the optimum return. The
system dynamics simulation was applied. The simulation model was
constructed by the real data from a case of the electronic devices
manufacturer in Thailand. The Steepest Descent algorithm was
employed to optimise. The experimental results show that the
company should spend on prevention and appraisal activities for 850
and 10 Baht/day respectively. It provides minimum cumulative total
quality cost, which is 258,000 Baht in twelve months. The effect of
the step size in the stage of improving the variables to the optimum
was also investigated. It can be stated that the smaller step size
provided a better result with more experimental runs. However, the
different yield in this case is not significant in practice. Therefore, the
greater step size is recommended because the region of optima could
be reached more easily and rapidly.
[1] J. M. Juran, Quality Control Handbook. 2nd ed. New York: McGraw-
Hill, 1962.
[2] A. M. Schneiderman, "Optimum Quality Costs and Zero Defects: Are
they contradictory concepts?," Quality Progress, November, 1986,
pp.28-31.
[3] W. E. Deming, Out of the Crisis, Cambridge, Massachusetts Institute of
Technology, 1986.
[4] S. T. Foster, "An examination of the relationship between conformance
and quality-related costs," International Journal of Quality & Reliability
Management, vol.13(4), 1996, pp. 50-63.
[5] J. M. Juran and F. M. Gryna, Juran-s Quality Handbook, 5th ed.
Singapore, McGraw-Hill International edition, 2000.
[6] J. Campanella, Principles of Quality Costs, Principles, Implementation,
and Use, 3rd ed. Wisconsin, American Society for Quality, 1999.
[7] D. Visuwan and J. D. T. Tannock, "Simulation of the economics of
quality improvement in manufacturing. A case study from the Thai
automotive industry", International Journal of Quality and Reliability
Management, vol.21, no.6, 2004, pp.638-654.
[8] D. Visuwan and J. D. T. Tannock, "An examination of the criteria for
optimizing in quality economics models", Proceedings of the 4th
International Conference on Responsive Manufacturing, Nottingham,
2007.
[9] D. Visuwan, "Stepwise Kaizen Parameters Improvement via the Path of
Steepest Ascent",Proceedings of The International MultiConference of
Engineers and Computer Scientists 2010, Hong Kong, 2010, pp. 1531-
1536.
[10] D. C. Montgomery, Design and Analysis of Experiments, 5th ed. New
York, John Wiley & Sons, 2001.
[11] P. Luangpaiboon, "Improving an Electrostatic Powder Coating Process
via Signal to Noise Response Surface," Am. J. Applied Sci., vol. 7(11),
2010, pp. 1521-1527
[12] P. Luangpaiboon, "Constrained response surface optimization for a
laser beam welding process," Journal of Mathematics and Statistics, vol.
7(1), 2011, pp. 5-11.
[1] J. M. Juran, Quality Control Handbook. 2nd ed. New York: McGraw-
Hill, 1962.
[2] A. M. Schneiderman, "Optimum Quality Costs and Zero Defects: Are
they contradictory concepts?," Quality Progress, November, 1986,
pp.28-31.
[3] W. E. Deming, Out of the Crisis, Cambridge, Massachusetts Institute of
Technology, 1986.
[4] S. T. Foster, "An examination of the relationship between conformance
and quality-related costs," International Journal of Quality & Reliability
Management, vol.13(4), 1996, pp. 50-63.
[5] J. M. Juran and F. M. Gryna, Juran-s Quality Handbook, 5th ed.
Singapore, McGraw-Hill International edition, 2000.
[6] J. Campanella, Principles of Quality Costs, Principles, Implementation,
and Use, 3rd ed. Wisconsin, American Society for Quality, 1999.
[7] D. Visuwan and J. D. T. Tannock, "Simulation of the economics of
quality improvement in manufacturing. A case study from the Thai
automotive industry", International Journal of Quality and Reliability
Management, vol.21, no.6, 2004, pp.638-654.
[8] D. Visuwan and J. D. T. Tannock, "An examination of the criteria for
optimizing in quality economics models", Proceedings of the 4th
International Conference on Responsive Manufacturing, Nottingham,
2007.
[9] D. Visuwan, "Stepwise Kaizen Parameters Improvement via the Path of
Steepest Ascent",Proceedings of The International MultiConference of
Engineers and Computer Scientists 2010, Hong Kong, 2010, pp. 1531-
1536.
[10] D. C. Montgomery, Design and Analysis of Experiments, 5th ed. New
York, John Wiley & Sons, 2001.
[11] P. Luangpaiboon, "Improving an Electrostatic Powder Coating Process
via Signal to Noise Response Surface," Am. J. Applied Sci., vol. 7(11),
2010, pp. 1521-1527
[12] P. Luangpaiboon, "Constrained response surface optimization for a
laser beam welding process," Journal of Mathematics and Statistics, vol.
7(1), 2011, pp. 5-11.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:51040", author = "Danupun Visuwan and Pongchanun Luangpaiboon", title = "Determination of the Proper Quality Costs Parameters via Variable Step Size Steepest Descent Algorithm", abstract = "This paper presents the determination of the proper
quality costs parameters which provide the optimum return. The
system dynamics simulation was applied. The simulation model was
constructed by the real data from a case of the electronic devices
manufacturer in Thailand. The Steepest Descent algorithm was
employed to optimise. The experimental results show that the
company should spend on prevention and appraisal activities for 850
and 10 Baht/day respectively. It provides minimum cumulative total
quality cost, which is 258,000 Baht in twelve months. The effect of
the step size in the stage of improving the variables to the optimum
was also investigated. It can be stated that the smaller step size
provided a better result with more experimental runs. However, the
different yield in this case is not significant in practice. Therefore, the
greater step size is recommended because the region of optima could
be reached more easily and rapidly.", keywords = "Quality costs, Steepest Descent Algorithm, StepSize, System Dynamics Simulation", volume = "5", number = "8", pages = "1146-6", }