AI-Aided Expander Machine Parameter Optimization

The Automation Manufacturing Technology (AMT) team is looking for an automated method to adjust parameters for one of our medical manufacturing machines using a closed loop system assisted by a machine learning model. This student team will work to optimize the air flow to create the ideal air pressure based on different variables which would improve machine efficiency and minimize production costs. Some of the factors that affect desired air pressure include outer diameter, surface quality, and the length of product that has already been processed. This student team will work to receive data and develop an optimized air flow model with air pressure being the output. The outcome of this project can be implemented in manufacturing equipment for medical devices. Currently the air pressure is an offline parameter that operators manually adjust. Two of the independent variables this student team should work to consider in this system include outer diameter of the tubing, surface texture. This student team will work to provide the optimized air flow rate for each combination of these variables such that the air pressure is constantly increasing based on the length of the product that has been processed by the machine. In addition to this main scope, this student team can work to automate other parameters. The outcome this student team will work to create is an optimization program where the user can provide inputs in an easy excel type format and the outputs of the airflow rate will be in an excel or similar format (Need to confirm). The program should accurately predict the optimized air flow based on the input data. A stretch goal the student team could work toward is the integration of the solution into the manufacturing line.

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