In industrial manufacturing processes, particularly in the rubber industry, product quality is often influenced by multiple correlated and nonlinear process variables, making separate analysis insufficient and potentially leading to the loss of valuable process information. Among the available quality assessment tools, the rheometer torque–time curve provides continuous information on the curing behavior of rubber compounds and can be effectively analyzed as a functional profile. In this study, an orthogonal polynomial profile approach was employed to model and analyze the entire rheometer curve, overcoming the limitations of conventional methods that rely only on a few characteristic curing points. By transforming the conventional polynomial regression model into an orthogonal form, the proposed approach reduces multicollinearity among regression coefficients and enables independent and more stable monitoring of process parameters. A case study was conducted using data collected from an automotive rubber strip manufacturing process. The monitoring results showed that, in the scorch region, two out of four samples remained within the control limits, whereas the remaining two samples were identified as out-of-control. Likewise, in the cure completion region, only one sample was within the control limits, while three samples exceeded the control boundaries. These findings demonstrate that the proposed profile-based approach is more sensitive to process variations than conventional characteristic-point methods and provides a more comprehensive representation of the curing behavior. Therefore, the proposed methodology can serve as an effective tool for curing process monitoring, rheometer performance evaluation, and quality control decision-making in rubber manufacturing industries.