G-Optimal Design in Non-linear Models to Increase Silicon Oxide Purity Levels and Electrical Conductivity

Authors

  • Muklas Riva'i  Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
  • Bagus Sartono  Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
  • Erfiani  Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
  • Irzaman  Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia

DOI:

https://doi.org//10.32628/IJSRSET21841110

Keywords:

G-Optimal, Non-Linear Model, Optimal Design, Silicon Oxide

Abstract

Optimal design is a design which required in determining the points of variable factors that would be attempted  to optimize the relevant information so that fulfilled the desired criteria. The optimal fulfillment criteria based on the information matrix of the selected model. The experimental design in silicon oxide with a purity rise silicon oxide obtained following the exponential decay distribution and approaches an asymptotic value which is a non-linear models. This research is aimed to obtain the best designs in determining the levels of silicon. The method used is the G-optimal criterion on non-linear models using the exchange algorithm. G-optimal is an optimal criteria in order to minimize the maximum variety of the estimation responses. The results of this study shows that the best G-optimal design  for non-linear models to the respons of purification levels of SiO2 (Y1) and electrical conductivity (Y2) is alternative 3 (Y1 = 0.75 and Y2 = 0.25) with temperature levels of 700oC, 705oC, 710oC, 735oC, 740oC,750oC, 835oC, 840oC, 860oC, 865oC, 870oC and 875oC with the G-efficiency value of  Y1 is 78.10% and the G-efficiency value of Y2 is 67.48%.

References

  1. Atkinson AC, Donev AN, Tobias RD. 2007. Optimum Experimental Designs, with SAS. New York: Oxford university press
  2. Aldrich S. 2006. Advancing Science. Singapore; Sigma-Aldrich Pte Ltd.
  3. Montgomery DC. 2001. Design and Analysis of Experiments. New York (US): John Wiley and Sons, Inc.
  4. Widiharih T, Haryatmi S, Gunardi. 2014. Rancangan D-optimal untuk model eksponensial general. Media Statistika. 7(2): 71:76.
  5. Yang M, Stufken J. 2012. Identifying locally optimal designs for nonlinear models: a simple extension with profound consequences. The Annals of Statistics. 40(3): 1665-1681.
  6. Rodrguez C, Ortiz I, Martnez I. 2015. Locally and maximin optimal designs for multifactor nonlinear models. Statistics. 49(5): 1157-1168.
  7. Belmiro P.M. Duarte a, b,*,1, Weng Kee Wong c , Nuno M.C. Oliveira a,1. 2016. Model-based optimal design of experiments-Semidefinite and nonlinear programming formulations. Chemometrics and Intelligent Laboratory Systems. 151 : 153-163.
  8. Coniwanti P, Srikandhy R, Apriliyanni. 2008. Pengaruh proses pengeringan, normalitas hcl, dan temperatur pembakaran pada pembuatan silika dari sekam padi. Jurnal Teknik Kimia. 15 (1): 5-10
  9. Aguiar DPF et al. 1995. Tutorial D-optimal designs. Journal of Chemometrics and Intelligent Laboratory System. 30: 199-210.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-12-30

Issue

Volume 4, Issue 11, November-December-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Muklas Riva'i, Bagus Sartono, Erfiani, Irzaman, " G-Optimal Design in Non-linear Models to Increase Silicon Oxide Purity Levels and Electrical Conductivity, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp.150-155, November-December-2018. Available at doi : https://doi.org/10.32628/IJSRSET21841110