MIXTURE MODEL WITH INVERSE TERMS FOR WELD-METAL CHEMISTRY PREDICTION AS A FUNCTION OF SAW FLUX INGREDIENTS

MIXTURE MODEL WITH INVERSE TERMS FOR WELD-METAL CHEMISTRY PREDICTION

Authors

  • Ademola Adeyeye Department of Industrial and Production Engineering, University of Ibadan, NIGERIA
  • Ofonime Udom Akpan University of Ibadan, Nigeria
  • Paul Adedeji University of Johannesburg, South Africa

DOI:

https://doi.org/10.4314/njt.v41i5.7

Keywords:

Edge Effects,, Scheffe's mixture models,, Predictive ability,, Response equations,, welding flux

Abstract

The development of regression equations in terms of welding flux ingredients for prediction and optimisation of weld-metal quality has received much attention. However, studies that take edge effects into account are sparse. In this study, models that incorporate edge effects were proposed for the predictions of carbon, nitrogen and phosphorus contents in weld-metal using secondary data. From the study, none of the models provides an adequate fit for carbon and nitrogen content in weld-metal (are ). The models showed some promise for phosphorus content (). Special cubic and full cubic with inverse terms fitted the phosphorus data better than others. Their respective  values were (81.32; 80.27%) and (81.57; 80.48%). The difference between their respective   and  are less than 0.2 as specified in the literature. Development of prediction models for carbon and nitrogen and understanding of the phenomenon of edge effects are recommended for further study.                                  

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Published

2022-11-08

Issue

Section

Chemical, Industrial, Materials, Mechanical, Metallurgical, Petroleum & Production Engineering

How to Cite

MIXTURE MODEL WITH INVERSE TERMS FOR WELD-METAL CHEMISTRY PREDICTION AS A FUNCTION OF SAW FLUX INGREDIENTS: MIXTURE MODEL WITH INVERSE TERMS FOR WELD-METAL CHEMISTRY PREDICTION. (2022). Nigerian Journal of Technology, 41(5), 870-878. https://doi.org/10.4314/njt.v41i5.7