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Robustness study of the tricalcium phosphate synthesis by using Taguchi’s approach

  • Mohamed Nohair EMAIL logo , Chaymae Jermouni , Sara Azmi , El Mati Khoumri , Ouafaa Britel and Hassan Chaair
Published/Copyright: November 16, 2020
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Abstract

In this work we propose a contribution for the optimization of the tricalcium phosphate synthesis by a double decomposition with a Ca/P ratio equal to 1.5, using Taguchi’s approach in the methodology of experiment design. We used a model involving four factors, namely the pH of the reaction, the concentration of Ca2+ ions, the temperature and the reaction time. We reduced the number of factors by subtracting the temperature, because it varies randomly in its range of variation. So we have developed a much simpler and more robust model by a double optimization. It consists in finding a configuration of the retained factors to synthesize a product with a Ca/P equal to 1.5 with the minimum of dispersion. We propose a synthesis process insensitive to random variations in temperature in its field of experimental variation defined previously. The synthesis process of the tricalcium phosphate is robust and insensitive on the temperature in the range of variation that was analyzed. The resolution of the mathematical model proposes different ways for this synthesis by a factorial variation of the three remaining factors. The proposed mathematical model is linear and efficient with very satisfactory statistical indicators.


Corresponding author: Mohamed Nohair, Laboratoire de Chimie Physique & de Chimie Bioorganique, Energie, Electrochimie Interfaciale et Chimiométrie, F.S.T de Mohammedia-Maroc, Casablanca, Morocco, E-mail:

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

1. Bouler, JM, Pilet, P, Gauthier, O, Verron, E. Biphasic calcium phosphate ceramics for bone reconstruction: a review of biological response. Acta Biomater 2017;53:1. https://doi.org/10.1016/j.actbio.2017.01.076.Search in Google Scholar

2. Brazete, D, Torres, PMC, Abrantes, JCC, Ferreira, JMF. Influence of the Ca/P ratio and cooling rate on the allotropic α↔β-tricalcium phosphate phase transformations. Ceram Int 2018;44:8249. https://doi.org/10.1016/j.ceramint.2018.02.005.Search in Google Scholar

3. Chaair, H, Labjar, H, Britel, O. Synthesis of β-tricalcium phosphate : synthèse du phosphate tricalcique-β. Morphologie 2017;101:120. https://doi.org/10.1016/j.morpho.2017.06.002.Search in Google Scholar

4. Barralet, JE, Best, SM. Effet of sintering parameters on the density and microstructure of carbonate hydroxyapatite. J Mater Sci Mater Med 2000;11:719. https://doi.org/10.1023/a:1008975812793.10.1023/A:1008975812793Search in Google Scholar

5. Chaair, H. Optimisation de la synthèse en continu des phosphates de calcium. thèse. Toulouse, France: INP; 1993.Search in Google Scholar

6. Britel, O, Hamad, M, Sallek, B, Chaair, H, Digua, K, Ouadadess, H. Modélisation de la Synthèse de l’Hydroxyapatite Elaborée à Partir du Carbonate de Calcium et de l’Acide Phosphorique. Phosphorus, Sulfur, Silicon Relat Elem 2006;181:325. https://doi.org/10.1080/104265090970386.Search in Google Scholar

7. Goupy, J. Pratiquer les plans d’expériences. Paris: Dunod; 2005.Search in Google Scholar

8. Goupy, J. What kind of experimental design for finding and checking robustness of analytical methods? Anal Chim Acta 2005;544:184. https://doi.org/10.1016/j.aca.2005.01.051.Search in Google Scholar

9. Myers, RH, Montgomery, DC, Anderson-Cook, CM. Response surface methodology: process and product optimization using designed experiments, 4th ed. Wiley; 2016.Search in Google Scholar

10. Pillet, M. Les plans d’expériences par la méthode Taguchi. Paris: Editions d’Organisation; 1997.Search in Google Scholar

11. Ganorkar, SB, Shirkhedkar, AA. Design of experiments in liquid chromatography (HPLC) analysis of pharmaceuticals: analytics, applications, implications and future prospects. Rev Anal Chem 2017;36:1. https://doi.org/10.1515/revac-2016-0025.Search in Google Scholar

12. Sergio, F, Adriana, C, Thaise, B, Ariana, L, Laiana, S, Walter, S. Robustness evaluation in analytical methods optimized using experimental designs. Microchem J 2017;131:163.10.1016/j.microc.2016.12.004Search in Google Scholar

13. Feinberg, M. Labo-Stat : Guide de validation des méthodes d’analyse. Paris: Lavoisier Tec&Doc; 2009.Search in Google Scholar

14. Montgomery, DC, Runger, GC. Applied statistics and probability for engineers, 7th ed. Wiley; 2018.Search in Google Scholar

15. Dagnelie, P. Statistique théorique et appliquée – Tome 2. Inférence statistique à une et à deux dimensions. Bruxelles: De Boeck; 2011.Search in Google Scholar

16. Taguchi, G. System of experimental design: engineering methods to optimize quality and minimize costs (tome I et II). Kraub: Unipub; 1987.Search in Google Scholar

17. JMP DemoVersion 14. USA: SAS Institute; 2014.Search in Google Scholar

Received: 2020-07-15
Accepted: 2020-10-21
Published Online: 2020-11-16

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