Surface Modification Analysis of Dental Implant Materials through Taguchi and RSM Approach for: A Review
Abstract
Dental implants have revolutionized the field of dentistry, providing a durable and long-lasting replacement for missing teeth. The success of dental implants is highly dependent on the materials used and their properties, including surface characteristics. In recent years, Taguchi and Response Surface Methodology (RSM) techniques have emerged as powerful tools for optimizing surface modification parameters to improve dental implant materials. This review paper provides a comprehensive overview of Taguchi and RSM methods for surface modification analysis of dental implant materials. The paper explains the principles behind Taguchi and RSM techniques and their application to dental implant materials. The advantages and limitations of each technique are highlighted, and recent advances in the field are discussed. The paper presents case studies and examples demonstrating the effectiveness of Taguchi and RSM techniques in optimizing surface properties of dental implant materials. By optimizing the surface properties, it is possible to improve the biocompatibility, osseointegration, and corrosion resistance of dental implant materials, resulting in better clinical outcomes.
Keywords: Taguchi, Response Surface Methodology (RSM), surface modification, dental implant materials, optimization parameters.
How to cite this article:
Singh S. Surface Modification Analysis of Dental Implant Materials through Taguchi and RSM
Approach for: A Review. J Adv Res Instru Control Engi 2023; 10(1): 6-9
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surface and design of experiments methodologies for dental implants based on the stress of the cortical
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Part B: Engineering 2009; 40(7): 668-675.
31. Elleuch S, Jrad H, Kessentini A. Design optimization of implant geometrical characteristics enhancing primary
stability using FEA of stress distribution around dental prosthesis. Computer Methods in Biomechanics and
Biomedical Engineering 2021; 24(9): 1035-1051.
32. Sadollah A, Bahreininejad A, Eskandar H. Optimum material gradient for functionally graded dental
implant using particle swarm optimization. In Advanced Materials Research Trans Tech Publications Ltd 2013;
647: 30-36.
33. Chen J, Rungsiyakull C, Li W. Multiscale design of surface morphological gradient for osseointegration. Journal of the mechanical behavior of biomedical materials 2013; 20: 387-397.
34. Akhai S. From Black Boxes to Transparent Machines: The Quest for Explainable AI. Available at: Social Science
Research Network, 2023. http://dx.doi.org/10.2139/ ssrn.4390887.
2015; 43(7): 798-805.
2. Grusovin MG, Coulthard P, Worthington HV et al. Interventions for replacing missing teeth: maintaining
and recovering soft tissue health around dental implants. Cochrane Database of Systematic Reviews
2010; 8.
3. Block MS. Dental implants: the last 100 years. Journal of Oral and Maxillofacial Surgery 2018; 76(1): 11-26.
4. Gaviria L, Salcido JP, Guda T. Current trends in dental implants. Journal of the Korean Association of Oral and
Maxillofacial Surgeons 2014; 40(2): 50.
5. Hosseini-Faradonbeh SA, Katoozian HR. Biomechanical evaluations of the long-term stability of dental implant
using finite element modeling method: a systematic review. The Journal of Advanced Prosthodontics
2022; 14(3): 182.
6. Satpathy M. Optimizing the Design of Reduced- Diameter Dental Implants to Increase Their Fatigue
Lifetime (Doctoral dissertation, The University of Mississippi Medical Center).
7. Moradi, H., Beh Aein, R., & Youssef, G. (2021). Multi objective design optimization of dental implant
geometrical parameters. International Journal for Numerical Methods in Biomedical Engineering, 37(9),
e3511.
8. Akhai S, Rana M. Taguchi-based grey relational analysis of abrasive water jet machining of Al-6061. Materials
Today: Proceedings 2022; 65: 3165-3169.
9. Rana M, Akhai S. Multi-objective optimization of Abrasive water jet Machining parameters for Inconel
625 alloy using TGRA. Materials Today: Proceedings 2022; 65: 3205-3210.
10. Akhai S, Srivastava P, Sharma V, Bhatia A. Investigating weld strength of AA8011-6062 alloys joined via frictionstir welding using the RSM approach. In Journal of Physics: Conference Series 1950; 1: 012016. IOP
Publishing.
11. Jadhav L, Kapole S, Dhatrak P. Design of experiments (DoE) based optimization of dental implants: a review.
In AIP Conference Proceedings 2021; 2358(1): 040003) AIP Publishing LLC.
12. Khened, V., Bhandarkar, S., & Dhatrak, P. (2022). Dental implant thread profile optimization using Taguchi
approach. Materials Today: Proceedings, 62, 3344- 3349.
13. Safaei M, Moghadam A. Optimization of the synthesis of novel alginate-manganese oxide bionanocomposite
by Taguchi design as antimicrobial dental impression material. Materials Today Communications, 31, 103698.
14. Singh G, Akhai S. Experimental study and optimisation of MRR in CNC plasma arc cutting. International Journal of Engineering Research and Applications 2015; 5(6): 96-99.
15. Arora N, Akhai S. Reclaiming EN-14b steel grade implements by hardfacing. International journal of
scientific research 2015; 4(10): 14-16.
16. Thareja P, Akhai S. Processing parameters of powder aluminium-fly ash P/M composites. Journal of advanced
research in manufacturing, material science & metallurgical engineering 2017; 4(3&4): 24-35.
17. Thareja P, Akhai S. Processing Aluminum Fly Ash Composites via Parametric Analysis of Stir Casting. Journal of Advanced Research in Manufacturing, Material Science & Metallurgical Engineering 2016; 3(3&4): 21-28.
18. Rafieerad AR, Bushroa AR, Nasiri-Tabrizi B. Toward improved mechanical, tribological, corrosion and invitro
bioactivity properties of mixed oxide nanotubes on Ti–6Al–7Nb implant using multi-objective PSO. Journal
of the mechanical behavior of biomedical materials 2017; 69: 1-18.
19. Jain S, Parashar V. Critical review on the impact of EDM process on biomedical materials. Materials and Manufacturing Processes 2021; 36(15): 1701-1724.
20. Lin CL, Chang SH, Chang WJ. Factorial analysis of variables influencing mechanical characteristics of
a single tooth implant placed in the maxilla using finite element analysis and the statistics‐based Taguchi
method. European journal of oral sciences 2007; 115(5): 408-416.
21. Karnik N, Dhatrak P. Optimization Techniques and Algorithms for Dental Implants–A Comprehensive
Review. Metaheuristic Algorithms in Industry 2021; 4.0: 261-282.
22. Liu CW, Chen CT, Lin KC. Prevention of implant fracture complications in dental implantation. Journal
of Biomaterials and Tissue Engineering 2018; 8(7): 1017-1021.
23. Liu CW, Chuang KJ, Chen CT. Evaluation of the Influence of Bone Resorption on Dental Implant Systems Using
Taguchi Method and Finite Element Analysis. Journal of Biomaterials and Tissue Engineering 2021; 11(2): 276-281.
24. Liu CW, Chuang KJ, Chen CT. Evaluation of the Influence of Bone Resorption on Dental Implant Systems Using
Taguchi Method and Finite Element Analysis. Journal of Biomaterials and Tissue Engineering 2021; 11(2): 276-281.
25. Chakraborty A, Datta P, Kumar CS. Probing combinational influence of design variables on bone biomechanical response around dental implant‐supported fixed prosthesis. Journal of Biomedical Materials Research Part B: Applied Biomaterials 2022; 110(10): 2338-2352.
26. Liu CW, Chen CT, Lin KC. Prevention of implant fracture complications in dental implantation. Journal
of Biomaterials and Tissue Engineering 2018; 8(7): 1017-1021.
27. Kuo RF, Fang KM, Ty W. Quantification of dental prostheses on cone‐beam CT images by the Taguchi
method. Journal of Applied Clinical Medical Physics 2016; 17(1): 207-220.
28. Günhan B, Deliktaş D, Kaya G. Optimization of selfcolored dental zirconia block parameters for an
effective machining performance using response surface methodology based artificial bee colony. Dental
Materials 2022; 38(8): 1248-1260.
29. Freitas JP, Agostinho Hernandez B, Gonçalves PJ. Novel and simplified optimisation pathway using response
surface and design of experiments methodologies for dental implants based on the stress of the cortical
bone. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
2021; 235(11): 1297-1309.
30. Lin D, Li Q, Li W.Design optimization of functionally graded dental implant for bone remodeling. Composites
Part B: Engineering 2009; 40(7): 668-675.
31. Elleuch S, Jrad H, Kessentini A. Design optimization of implant geometrical characteristics enhancing primary
stability using FEA of stress distribution around dental prosthesis. Computer Methods in Biomechanics and
Biomedical Engineering 2021; 24(9): 1035-1051.
32. Sadollah A, Bahreininejad A, Eskandar H. Optimum material gradient for functionally graded dental
implant using particle swarm optimization. In Advanced Materials Research Trans Tech Publications Ltd 2013;
647: 30-36.
33. Chen J, Rungsiyakull C, Li W. Multiscale design of surface morphological gradient for osseointegration. Journal of the mechanical behavior of biomedical materials 2013; 20: 387-397.
34. Akhai S. From Black Boxes to Transparent Machines: The Quest for Explainable AI. Available at: Social Science
Research Network, 2023. http://dx.doi.org/10.2139/ ssrn.4390887.
Published
2023-06-21
How to Cite
SINGH, Sarabjit.
Surface Modification Analysis of Dental Implant Materials through Taguchi and RSM Approach for: A Review.
Journal of Advanced Research in Instrumentation and Control Engineering, [S.l.], v. 10, n. 1&2, p. 6-9, june 2023.
ISSN 2456-1398.
Available at: <http://thejournalshouse.com/index.php/instrumentation-control-engg-adr/article/view/721>. Date accessed: 22 dec. 2024.
Section
Review Article
