Application of 2 Factorial Experiment in Analyzing the Effect of Four Factors of Cracks on Components for Jet Turbine Aircraft Engines

E. J. Mahanan; A. B. Pwasong

Application of 2⁴ Factorial Experiment in Analyzing the Effect of Four Factors of Cracks on Components for Jet Turbine Aircraft Engines

E. J. Mahanan and A. B. Pwasong,
International Journal of Computational and Electronic Aspects in Engineering
Volume 4: Issue 2, April-June 2023, pp 11-24

Author's Information

E. J. Mahanan¹

Corresponding Author

¹Plateau State College of Health Technology /Department of Environmental Health, Pankshin, Nigeria

Josiahemm1967@gmail.com

A. B. Pwasong²

²University of Jos /Department of Mathematics, Jos, Nigeria

Article -- Peer Reviewed

First online on – 30 June 2023

Open Access article under Creative Commons License

Cite this article –E. J. Mahanan, A. B. Pwasong “Application of 2⁴ Factorial Experiment in Analyzing the Effect of Four Factors of Cracks on Components for Jet Turbine Aircraft Engines”, International Journal of Computational and Electronic Aspects in Engineering, RAME Publishers, vol. 4, Issue 2, pp. 11-24, 2023.

https://doi.org/10.26706/ijceae.4.2.20230601

Abstract:-

This study investigates the effect of four factors: pouring temperature (A), titanium content (B), heat treatment method (C) and amount of grain refiner (D) as well as the interaction of pouring temperature X titanium content (AB), pouring temperature heat treatment method (AC), titanium content X heat treatment (BC), heat treatment amount of grain refiner (CD), pouring temperature X titanium content X heat treatment method (ABC) and pouring temperature titanium content X heat treatment method X amount of grain refiner (ABCD) on the length of crack in the components of a jet turbine engine. This was made possible by the application of the Factorial Design to analyse data which is on nickel-titanium used to create components for a jet turbine engine. The results revealed that the four factors take a substantial consequence on cracking in the parts of a jet turbine engine The significant effect of the factors on cracking was further confirmed by a multiple linear regression model. Two multiple comparison methods were employed in the study to compare all pairs of means involving the main factors effects in the data, the reason for which is to determine which of the main factor effect affects variability in cracking and these multiple comparison techniques are the Duncan’s multiple range (DMR) test as well as the least significance difference (LSD) method. The result of the multiple comparison revealed that the least significance difference (LSD) method produced the same outcome with the Duncan’s multiple range (DMR) method. The analysis in this article were analyzed and executed with the Statistical Package for Social Sciences (SPSS) software and Microsoft Excel.

Index Terms:-

factorial, cracking, regression, factor effects, multiple comparison, error

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