Preform shape and operating condition optimization for the stretch blow molding process

In this work, a new design approach was developed to automatically and consecutively predict optimal preform geometry and optimal operating conditions for the stretch blow molding process. The numerical approach combines a constrained gradient-based optimization algorithm that iterates automatically over predictive finite element software. The strategy allows for targeting a specified container thickness distribution by manipulating consecutively the preform geometry (thickness and shape) and the operating parameters subject to process and design constraints. For the preform shape optimization, the preform geometry is mathematically parameterized for simplified treatment and the corresponding sensitivities are evaluated using a finite difference technique. A finite difference technique is also employed for the operating condition optimization. The constrained optimization algorithms are solved via the use of the sequential quadratic programming method that updates the design variables accordingly. Predicted optimization results obtained on an industrial case are presented and discussed to assess the validity when compared to experimental results and the robustness of the proposed approach.