team photo


Team 10

Team Members

Faculty Advisor

Nicholas Rivard-Lentz
Lucas Zabarburu
Luke Santoro
Augustine Teage

Prof Craig Calvert, Prof Rajiv Naik​

Sponsor

The Gilman Brothers Company

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Design and Feasibility Analysis of Automated Carton-Making ​Solutions to Increase End-of-Line Throughput by 30%+ for The Gilman Brothers Company

This project evaluates commercially available tray-forming machines to automate the end-of-line packaging process at The Gilman Brothers Company. Currently, trays are formed manually by folding die-cut corrugated blanks and securing them with pneumatic staples. This manual process runs across three shifts and limits throughput while creating variation in tray availability and consistency. The goal of this study is not to design a new machine. Instead, it analyzes existing off-the-shelf tray formers to determine whether they can meet the required production conditions. The selected system must sustain 160–200 cartons per hour, fit within the available packaging floor space, connect with the current material handling flow, and handle a wide range of carton sizes, including oversized trays. The machines were compared based on forming range, blank handling method, cycle rate, changeover requirements, machine footprint, and utility needs. Structural design, safety guarding, and integration with the existing packaging area were also considered. Measured carton dimensions and annual usage data were compared with each machine’s operating range to confirm size compatibility. Layout studies were performed to verify floor space requirements, conveyor alignment, operator access, and maintenance clearance. Each system was evaluated from a mechanical engineering perspective, focusing on forming method, motion design, structural stability, expected reliability, and the ability to handle variation in carton sizes. The final result of this project is a technically supported recommendation identifying which commercial tray-forming system best meets the required throughput, size range, and integration constraints without requiring custom machine development.