Porosity exploration of SMA by Taguchi, regression analysis and genetic programming

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@Article{sharma:2019:JoIM,

• author = "Neeraj Sharma and Kamal Kumar and Tilak Raj and Vinod Kumar",
• title = "Porosity exploration of {SMA} by Taguchi, regression analysis and genetic programming",
• journal = "Journal of Intelligent Manufacturing",
• year = "2019",
• volume = "30",
• number = "1",
• keywords = "genetic algorithms, genetic programming, NiTi, SMA, Taguchi's method, Regression, analysis",
• URL = "http://link.springer.com/article/10.1007/s10845-016-1236-8",
• DOI = "doi:10.1007/s10845-016-1236-8",
• size = "8 pages",
• abstract = "Porosity plays a vital role in the field of biomedical engineering of implants i.e. orthopedic and orthodontics. Shape memory alloys exhibit a greater strength with a higher porosity. The strength of porous shape memory alloys were found similar to the strength of bones. In the present research, NiTi SMA is fabricated by powder metallurgy process. The processing parameters of sintering and compaction (i.e. compaction pressure, sintering temperature and sintering time) play an important role in the porosity investigation of SMA. Taguchi's method based L 9 orthogonal array was selected for the planning of experiments. Sintering temperature and sintering time were the significant process parameters as compared to compaction pressure. Regression coefficients and equation was derived by use of regression analysis. Further this equation was solved with the help of genetic programming and results of both (i.e. Taguchi method and genetic programming) were compared to find the maximum porosity. The maximum porosity that can be achieved is 56 percent and the confirmation experiments were performed at 95 percent confidence level.",
• notes = "p 145 'Genetic Programming predicts the optimal setting of process parameters for porosity'",

}

Genetic Programming entries for Neeraj Sharma Kamal Kumar Tilak Raj Vinod Kumar

Citations