Abstract

This research aims to evaluate the relationship between the chemical composition of low alloy steel, temperature, and the mechanical properties of low alloy steel using Exploratory Data Analysis (EDA) techniques. The low alloy steel dataset is visualized using a correlation heat map, which shows a relationship between the mechanical properties of low alloy steel and its chemical composition and heat treatment temperature. Based on the results of the correlation heat map, an evaluation is carried out using scatterplots. The visualization results with scatterplots show a trend line indicating a linear relationship between YS and the elements V, Ni, and Mn, as well as a positive relationship between TS and V. In addition, there are determination coefficients ( R²) that show how well the trend line can explain the variation of the data. The R² values obtained for V are 0.405, Ni is 0.226, Mn is 0.159, and Mo is 0.130, while El and RA have a positive correlation with temperature with R²values of 0.166 and 0.320, respectively. It can be concluded that the evaluation results using scatterplots and R² show that variations in chemical composition and heat treatment temperature affect the mechanical properties of low alloy steel. The correlations that occur between these variables can help in determining the pattern of the relationship and evaluating how well the trend line can explain the variation of the data. The use of correlation heat maps and scatter plots can help in decision-making and developing low-alloy steel materials that meet specific needs.

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