PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Verification of the Random Nature of the Experimental Data in the End-Milling Process of Aluminum Alloys

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
From a theoretical point of view, the research carried out in this manuscript was carried out starting from the study of the links between surface roughness and cutting speed, cutting depth and feed per tooth in the end milling process. From an experimental point of view, it started from the organization and development of the physical cutting process, the cutting regimes to be analyzed were established, after which the surface roughness was determined and measured. In this way, the connections between the factors and parameters pursued in the research resulted. The main purpose of this research is to check the random nature of the measured data related to the quality of the end milled surface of the Al7136 aluminum alloy. The main types of statistical processing performed on the sample values from the experimental measurements, the algorithms and the corresponding work modes are according to the method of research that is based on the use of the Young test. The conclusions highlighted the importance of adopting this research method and opened new directions of study.
Twórcy
  • Technical University of Cluj-Napoca, Northern University Centre of Baia Mare, Faculty of Engineering - Department of Engineering and Technology Management, 62A, Victor Babes Street, 430083, Baia Mare, Maramures, Romania
  • ”Lucian Blaga” University of Sibiu, Faculty of Engineering, Industrial Engineering and Management Department, 10 Victoriei Street, 550024, Sibiu, Romania
Bibliografia
  • [1] M. Balaji, K.V. Rao, N.M. Rao, B. Murthy, Measurement 114, 332-339 (2018).
  • [2] S. Wojciechowski, R. Maruda, S. Barrans, P. Nieslony, G. Krolczyk, Measurement 111, 18-28 (2017).
  • [3] M. Bănică, N. Medan, Academic Journal of Manufacturing Engineering 13 (1) (2015).
  • [4] I. Mukherjee, P.K. Ray, Comput. Ind. Eng. 50 (1), 15-34 (2006).
  • [5] M. Wan, J. Feng, Y.C. Ma, W.H. Zhang, Int. J. Mach. Tools. Manuf. 122, 120-131 (2017).
  • [6] A. Polishetty, M. Shunmugavel, M. Goldberg, G. Littlefair, R.K. Singh, Proc. Manuf. 7, 284-289 (2017).
  • [7] D. Montgomery, Design and Analysis of Experiments. Eighth Edition ed. Hoboken: John Wiley & Sons, Inc, (2013).
  • [8] V. Năsui, A. Coteţiu, R. Coteţiu, M. Lobonţiu, N. Ungureanu, Basics of experimental research of electromechanical actuators. Northern University Publishing House, Baia MARE, ISBN 973-1729-08-9, (2007).
  • [9] C. Opariuc-Dan, Statistics applied in the socio-human sciences. Analysis of associations and statistical differences, Cluj-Napoca, ASCR & Cognitrom, (2011).
  • [10] A.K.Y. Jain, Y. Shrivastava. Mater. Today Proceed. 21, 1680-1684 (2019).
  • [11] I. Hanif, M. Aamir, N. Ahmed, S. Maqsood, R. Muhammad, A. Akhtar, I. Hussain, Int. J. Adv. Manuf. Technol. 100, 1893-1905 (2019).
  • [12] M. Aamir, M. Tolouei-Rad, K. Giasin, A. Vafadar, Machinability of Al2024, Al6061, and Al5083 alloys using multi-hole simultaneous drilling approach, J. Mater. Res. Technol. 9, 10991-11002 (2020).
  • [13] M. Wan, J. Feng, Y.C. Ma, W.H. Zhang, Int. J. Mach. Tools. Manuf. 122, 120-131 (2017).
  • [14] M. Wan, X.B. Dang, W.H. Zhang, Y. Yang, Mech. Syst. Signal. Process. 103, 196-215 (2018).
  • [15] L.M. Chihara, T.C. Hesterberg, Mathematical statistics with resampling and R. John Wiley & Sons, (2022).
  • [16] C. Selvan, S.R. Balasundaram, Data Analysis in Context-Based Statistical Modeling in Predictive Analytics. In Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics (2021) (pp. 96-114). IGI Global.
  • [17] E.B. Manoukian, Mathematical nonparametric statistics, Taylor & Francis. (2022).
  • [18] J. Wright, Y. Ma, High-dimensional data analysis with low-dimensional models: Principles, computation, and applications. Cambridge University Press, (2022).
  • [19] J.K. Kim, Shao, J. Statistical methods for handling incomplete data. Chapman and Hall/CRC, (2021).
  • [20] C. Giraud, Introduction to high-dimensional statistics. Chapman and Hall/CRC, (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8bffe77b-39d9-4f70-b5fb-f9c8ec78d6c8
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.