Application of central composite design to minimize product variability in iron sheet production process

Abstract

The CCD is a fundamental technique in RSM and is widely applied in scientific research to accurately estimate factors in a 2nd degree model. This paper demonstrates the use of CCD in optimizing process variables to keep the production of iron sheets on target and minimize variability. Specifically, the study focused on three key factors influencing variability in iron sheet manufacturing: the pressure of the press rollers (X₁), the flow rate of the hydraulic fluid (X₂), and the power applied to the digital setting (X₃). By utilizing CCD, the study systematically optimized these factors and considered their interaction effects. The analysis highlighted the magnitudes of coefficients across the linear, interaction, and quadratic models, illustrating the varying degrees of influence each factor exerts on the response variable. By quantifying these effects, the study provided deeper insights into the relationships between factors, helping to identify key drivers of efficiency and variability. The R² values for the linear, interaction, and quadratic models were 0.98, 0.95, and 0.973, in that order, indicating that the quadratic model provides a more accurate description of the production process. Surface plots comparing the pressure of the press rollers with the power applied to the digital setting, and the flow rate of the hydraulic fluid with the power applied to the digital setting, suggested that increasing the hydraulic fluid flow enhances production efficiency. The minimum variability was found at X₁ = 8.15, X₂ = 5.022, and X₃ = 0.4550.