Data-Driven Design Decision Support for Re-X of High-Value Components in Industrial and Agricultural Equipment
This project will create a tool to evaluate and recommend the optimal designs of components in industrial and agricultural equipment. By designing components with optimum material utilization and end-of-life in mind, there is a 60% reduction in carbon emissions.
The novelty of this tool lies in its ability to incorporate real-world load/component health data that has been acquired by condition monitoring systems in the field into early-stage design assessment using random variable models. This approach enables data-informed design for Re-X.
Project Team:
Iowa State University, John Deere
18-02-DE-06