Plastic Flow, LLC — National Science Foundation SBIR Phase I: MN

Description

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the reduction in the development time and cost of the dies employed for coextrusion of multilayer plastic products. The die optimization software which will be developed in this project will reduce the lead time for coextrusion die design by at least 50%, resulting in a saving of $15,500-22,500 for each die design. The die optimization software from this project will also improve the quality of the coextruded products. Coextruded plastic products are used in application ranging from automotive parts, housing and construction, to tubing used during medical operations. Optimized coextrusion dies will improve the quality of products for all these applications. The die optimization software will also be used by many universities for academic research as well as to teach extrusion die design in their plastics engineering curriculum. This optimization software will also enhance the scientific understanding of the root cause behind various complexities encountered in polymer coextrusion. The intellectual merit of this project is development of a mathematical algorithm which will be able to optimize the geometry of different types of coextrusion dies including those used for extrusion of sheets, pipes, and complex profiles. The main challenge in design of a coextrusion die is to develop a die geometry which will give a uniform velocity distribution at the die exit and will also provide the required layer structure in the coextruded product. If exit velocity is different in different portions as polymer exits the die, the material is redistributed after it comes out - which can distort the shape of the extruded product. Coextrusion dies are still mostly designed using a "trial-and-error" approach. For complex coextrusion dies, this fine-tuning by trial-and-error not only takes 2 to 3 months to reach the final die design, but also requires highly experienced engineers and rarely provides an optimum die design. The die optimization software which will be developed in this project will eliminate this trial-and-error approach, replacing it with a science-based mathematical algorithm. To evaluate each die design, this optimization software will use a recently developed flow simulation software that can accurately predict the development of layer structure in coextrusion dies along with the post-die distortion of multilayer coextruded products.