Binary logistic regression for defect-free electron beam welding

  • 1 University of Chemical Technology and Metallurgy, Bulgaria; Institute of Electronics, Bulgarian Academy of Sciences, Bulgaria
  • 2 University of Chemical Technology and Metallurgy, Bulgaria


Using the method of binary logistic regression, the dependence of dichotomous variables on one or more, quantitative or qualitative independent variables is studied. In order to solve problems with binary dependent variables, binary choice model estimation methodologies, such as logistic regression (logit) and probit regression (probit), can be implemented. The logistic model is based on the logistic distribution, while the probit model is based on the normal distribution. In this paper the binary logistic regression methodology is applied for obtaining defect-free welds by electron beam welding process, based on experimental data.



  1. E. Koleva, Applied Statistics (UCTM-Sofia, 2020)
  2. D.W. Hosmer, S. Lemeshow, Applied Logistic Regression. 2nd ed. (John Wiley & Sons, Inc., 2000)
  3. C. Huberty, S. Olejnik, Applied MANOVA and Discriminant Analysis. 2nd ed. (Wiley, 2006)
  4. D. Montgomery, G. Runger, Applied Statistics and Probability for Engineers. Seventh Edition (John Wiley & Sons, Inc., 2018)
  5. E. Koleva, G. Mladenov, Process Parameter Optimization and Quality Improvement at Electron Beam Welding, Welding: Processes, Quality, and applications, еd. Richard J. Klein (Nova Sci. Publishers, Seria Mechanical Engineering-Theory and Applications, 2010)
  6. E. G. Koleva, G. M. Mladenov, Experience on electron beam welding. Practical Aspects and Applications of Electron Beam Irradiation, eds. Monica R. Nemtanu and Mirela Brasoveanu, (Transworld Research Network, India, 2011).
  7. E. G. Koleva, L. S. Koleva, G. M. Mladenov. Electrotechnica & Electronica E+E, 52(3-4), 22-28 (2017)

Article full text

Download PDF