Subteams
AURPI: Industrial & Systems Engineering Sensors are being used to detect potential equipment issues before failures occur—a strategy known as predictive maintenance. This approach helps prevent unnecessary shutdowns in forestry and poultry operations, protecting production and supporting the livelihoods of rural Alabamians. To make the collected data more actionable, a system is being developed that leverages the Overall Equipment Effectiveness (OEE) standard, making the information easier to process, understand, and apply.
Recent Projects: Our Industrial Team's most recent project was creating a digital application for capturing Overall Equipment Effectiveness (OEE) related data designed for poultry processing plants. The app was developed to replace paper forms and manual data entry. This facilitates the efficient monitoring of daily OEE scores and storage of operations data for performance tracking. Efforts have been made to deploy this app soon!
The Cyber Security Team is working on developing a case study to support the deployment of their OEE app. The team has also conducted a detailed analysis using the case study company's operational data to establish the relationships that may exist between the three factors of OEE (Availability, Performance, and Quality) to further understand how these factors contribute to achieving increased productivity and profitability as well as identify industry-wide trends and patterns to make informed decisions.
Install and validate the Arduino sensing systems, comparing their performance with Urban.io to ensure data reliability and identify improvement areas.
Scale the work into poultry facilities and eventually to other industries across Alabama.
Collaborate with local sawmill experts to refine the framework through interviews and panels.