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A Polymer Process Optimization Center: Integration Of Nsf And Industrial Support
Author(s) -
Gwan-Ywan Lai,
Laura Sullivan
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--7346
Subject(s) - stereolithography , manufacturing engineering , molding (decorative) , process (computing) , mechanical engineering , computer science , engineering , operating system
The Polymer Processing Laboratory at Kettering University has enjoyed tremendous growth in capability over the past four years. Four National Science Foundation ILI Grants have provided for microprocessor controlled injection molding, stereolithography, capillary and on-line rheometry, and tensile testing. Funding from the Society for Manufacturing Engineering has resulted in the acquisition of mold temperature control equipment and mold flow simulation software. Internal funding has provided for process capability analysis, and industrial support has funded a coordinate measuring machine. Now, integration of this equipment has been endorsed through a $100K donation from local industry for a Polymer Process Optimization Center. With the creation of this Center, all phases of thermoplastic component manufacturing via injection molding will be integrated, from materials selection to tool design to process optimization. Undergraduate students will access this facility (1) as freshman, in one week study of polymer processing within a survey Introduction to Manufacturing Processes course (IMSE 101), (2) in an upper division Polymer Processing course (IMSE 407), and (3) via independent study projects in the area of injection molding for senior level students. Within the framework of the Polymer Processing course, IMSE 407, students will be given the opportunity to take the concept of a part, rendered via a solid modeling program, and transform it to a manufactured, injection molded part. This will involve converting the solid model to a solid tool via stereolithography, researching the materials of interest to be sure that they have suitable viscosity characteristics via rheometry, optimize the mold filling and packing portion of the injection molding cycle via online process parameter variation.

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