In biotechnological processes, a great number of factors can influence the income productivity and conversion. Normally, it is not evident which of these factors are the most important and how they interact. In this work, multivariate analysis techniques are used as experimental design coupled to a detailed deterministic model to identify the parameters with the most significant impact on the model to represent well the acrylic acid production process. It is proposed as an alternative process, having sugarcane as feedstock, to the petrochemical-based ones that have significant environmental impacts for their production. To increase the competitiveness of renewable acrylic-acid-based process, it is necessary to find out working conditions near the optimal region, which is not an easy task, as the process is multivariable and non-linear. The mapping of the dynamics of the developed process is made using techniques of factorial design together with the methodology of Plackett-Burman. It is shown that it is possible to increase the process performance by choosing optimized conditions for the reactor operation.