Fall 2025 Senior Capstone Projects in Industrial, Manufacturing, and Systems Engineering

Fall 2025 - Industrial Engineering Capstone Design

Design of an Automated Snack Cookie Assembly System at Apogee Foods

Apogee Foods is a contract food manufacturing and packing facility in Dallas, Texas which specializes in working with their clients to produce high-quality foods using natural ingredients, while maintaining a 100% gluten free, Kosher, and SQF (Safe Quality Food) certified facility. A new client requires the manual assembly of snack cookies, similar to a Little Debbie™ Oatmeal Cream Pie which has resulted in a major production bottleneck that requires, at times, up to ten people simultaneously assembling cookies. We designed a feasible automation solution and simulated its performance. The critical path of the process is the line that involves the icing of the cookies, and then the 24 cookies being assembled. This takes an average of 119 seconds (1 minute, 59 seconds) assuming triangular distributions. One batch of 22.4 pounds of dough makes 282 sandwiches, which fill almost 12 trays of 24. Using this automated system, 12 trays would take 24 minutes to complete. This allows a max throughput of 2.5 batches, or 705 cookies per hour. Using data provided by Apogee Foods, the existing manual procedure takes approximately 90 minutes to complete, allowing a maximum throughput of 0.67 batches, or 188 cookies per hour. Even with a wide margin of error, our design results in 277% improvement in throughput. As Apogee transitions toward automation, a Failure Mode and Effects Analysis (FMEA) was conducted to anticipate risks associated with the proposed computer vision (CV) and robotic assembly system. The future-state FMEA identifies critical failure modes in cookie detection, icing variability, robotic pick-and-place accuracy, and tray alignment inside the CV tunnel.

Geek+ Pick Ergonomics at Ariat International, Inc.

Ariat is the world’s largest brand of riding footwear and apparel, boasting retail locations in 42 countries and 4 regional distribution centers across North America. In Haslet, Texas lies the main redistribution center, where thousands of apparel items and footwear are picked every hour for redistribution. To ensure a smooth flow of products in and around the facility, the center primarily utilizes automation in the form of Autonomous Mobile Robots (AMR’s) to retrieve products from bins and shelves and onto stations where pickers can easily retrieve them. For picking, Ariat makes use of an AMR called Geek+ that delivers shelves of products to a picker’s workstation. Despite minimal foot traffic, ergonomic concerns like twisting and heavy lifting are still noted and are subject to change via an improved picking station layout. The basis of this project has involved the examination of this system’s ergonomics with a focus on improvement through layout, equipment, and systematic changes. Developing a clear definition of the ergonomic risks present, their frequency of occurrence, and their severity, ergonomic assessment tools were used to acquire metrics used to design targeted improvements that ultimately enhance the ergonomics of both the station and its workers. The designed improvements are based on the idea of replacing current, strenuous movements in favor of simpler ones that are actually quicker to perform, leaving picking rates and overall flow speed ultimately ambiguous. Overall, the ergonomic improvements made to Ariat’s picking stations remain prevalent and promising, and with proper implementation, can ride Ariat to long-term benefits for its facilities and employees.

American Leather: Improving Product Development 

American Leather, also known as AL, is a furniture manufacturer founded by engineers in 1990 with a strong commitment to operational excellence. They are known for their fast delivery times in the industry and their proprietary innovations which have built AL’s reputation and agility. However, the company’s product development process is increasingly challenged by the rising complexity of its products and the growing demand for speed. These pressures have created inefficiencies in prototyping, quality management, and documentation practices. Overall, our project helped clarify the key challenges affecting the product development and prototyping process at American Leather. By measuring cycle time, number of iterations, and quality issues, we identified opportunities to improve documentation, version control, and communication, especially within the Pattern Maker–Cover area. We analyzed the data and designed practical solutions: recording product briefings, implementing a shared prototype tracking sheet, providing 5S training, and preparing for the adoption of a PLM system. These improvements directly addressed the major sources of errors and process waste, which reduced prototyping quality issues from 20% to 10%. By creating a clear SOP, defining responsibilities through a RACI chart, and establishing regular 5S audits and continuous documentation tracking ensured that these changes are sustained. In summary, this project strengthened communication, improved documentation practices, showed early signs of reducing rework, and created a more organized and reliable prototyping process. With continued 5S discipline and the future implementation of a PLM system, American Leather will be able to maintain and further enhance its product development performance in support of the operational excellence it strives for.