ISE Senior Design Symposium Award Winners

Project Abstract
Logistics Management Institute (LMI) is a consulting firm that innovates technological solutions for its clients spanning across the defense, space, and healthcare industries. The company is interested in expanding their workforce analytics toolset by digitizing the project assignment process. Current processes are vulnerable to inaccurate estimates of employee skills, project requirements, and project priority. Manually crafting assignments from complex inputs can result in schedules with unequal employee utilization, long project time horizons, and suboptimal project sequencing. LMI has digital tools that quantify employee skills and project requirements and now requires an application to produce an optimized project schedule. The team developed several mathematical models that are optimized using different solvers, heuristics, and software that converts the mathematical model output into human-readable schedules and performance metrics. This project has provided LMI with a product they can utilize internally or sell to customers to efficiently allocate resources. The optimized assignment approach produces solutions that show several improvements compared to an algorithmic approximation of the current state, with increases in average employee utilization of up to 41% and decreases in project time horizons of up to 60%.

Project Abstract
In partnership with Inmotion’s Continuous Improvement department at their North American headquarters in Blacksburg, VA, the team aimed to enhance their training program for critical production lines, including rotor, stator, and final assembly, which faced quality issues and high turnover due to insufficient training. Over these two semesters, the focus was on creating an efficient training solution that would reduce training duration, lower turnover rates, and boost employee satisfaction. Utilizing the waterfall methodology, significant training gaps were identified through a comprehensive floor-wide survey, with the final assembly line as the primary focus. The approach selected, integrated Augmented Reality (AR) technology to facilitate on-the-job learning for new hires with minimal supervision. To support this training proposal, Standard Operating Procedure (SOP) was developed, supplemented with training materials to ensure the program's sustainability and adaptability. The implementation of the AR training environment was evaluated across various personnel demographics, revealing a 33% reduction in training time, a 15% rise in training satisfaction, and a 10% decrease in the cost of poor quality (COPQ). Projected over three years, the AR training program is expected to retain an additional 15 jobs, save $30,600 in material costs, and avoided unnecessary labor costs by $56,000, thereby corroborating the project's effectiveness and potential for broader application.

Project Abstract
Woodward is a design and manufacturing company headquartered in Fort Collins, Colorado. They provide control systems and sub-components to the aerospace, industrial, military, power, and transportation industries. Woodward is facing inconsistent output from three interdependent assembly cells. These cells struggle with operating at the correct capacity due to unpredictable staffing levels and a lack of standardized procedures. This affects equipment and labor productivity as well as kanban levels, causing idle time and long lead times for products.
Phase 1 involved collecting and analyzing data to establish a baseline for product lead times, product mix, and operation cycle times. In evaluating Woodward’s processes, we identified their need for a playbook to improve daily operations for Value Stream Managers. Phase 2 included developing a validated simulation model and testing staffing scenarios. We determined each cell’s maximum capacity and identified bottlenecks. The final phase was the development of the playbook. We ran many staffing scenarios to create plays that maximize throughput for each cell. Once the playbook was implemented, and staffing levels properly set, the lead time standard deviation decreased by 45% on average between the three cells. Additionally, the cells adopted a standardized work in process (SWIP) to support the planned production rate. Overall, the implementation of the playbook is expected to save Woodward $1,010,200 through a one-time inventory reduction, retained sales, reduced turnover, labor cost savings, and overhead cost savings. Finally, this playbook was designed for simple replication to other business areas in the plant, where the opportunity exists for further benefits beyond the initial project scope with a projected savings of $3,328,000.

Project Abstract
Infrabel is the sole provider of Belgian rail infrastructure and is entrusted with constructing, maintaining, and improving the country's railway network. Following a recent increase in system delays, there is a need for a resilience metric to assess the system's adherence to published train schedules. This metric is crucial for identifying areas requiring improvement to enhance punctuality, thereby increasing customer confidence in the reliability of the train system. The team developed a resilience metric comprised of four performance indicators, calculated using RStudio. The approach examined initial instances of a delay and assessed its potential impact on up to five subsequent trains. Additionally, an emphases was placed on prioritizing the metric's accessibility and adaptability for all employees and alignment with current system operations. To achieve this, the team created a visual dashboard to enhance user accessibility and interaction with the generated data. The overarching goals include achieving a 2% increase in system resilience, a 1% improvement in punctuality, and fostering a deeper understanding of resilience within Infrabel and among the public. While our solution represents a significant step forward, it is intended to serve as the foundation for further refinement by following teams.