2021 Senior Projects Conference

Examining the Use of the DMAIC Process on the Operational Plan Improvement for UPS Personal Vehicle Drivers

Team Members: Landry Seimears, Emily Theriot, Courtney Wessels

Sponsor: UPS

Advisor: Dr. Jun-Ing Ker

UPS has recently incorporated temporary seasonal personnel to deliver packages out of their personal vehicles, or Personal Vehicle Drivers (PVDs). Being able to deliver at a low cost while providing additional capacity makes them an important resource to the company, but without a guideline in place, they are being used inefficiently at some delivery centers. By utilizing the define, measure, analyze, improve, and control (DMAIC) process, the goal of this project was to analyze how PVDs are currently being planned and dispatched in order to create a cost-effective plan and tools to be used for future implementation. With the DMAIC method, interviews with employees directly involved in working with PVDs were first conducted, and key metrics of PVD efficiency were identified using Pareto diagrams. A statistical analysis was then performed to give a predictive equation of PVD performance. These efforts in combination with two other teams’ approaches to the problem led to the creation of an operational plan and interactive tool to pinpoint the most productive areas for PVD routes. These solutions, if used, will result in positive financial savings for UPS. The process and findings of this project can be a starting point for others who have an introduced resource in their company that is being used without efficient direction and want to create a methodical guideline.

TCI Lamination Downtime Analysis

Team Name: T.C.I. (Textiles Coated International)

Team Members: Christian Dalby, Conner Hill, Benjamin Steib

Sponsor: Abhas Joshi

Advisor: Dr. Jun-Ing Ker

Our team was tasked with investigating machine downtime in the production process bottleneck area named the lamination department at the company T.C.I. (Textiles Coated International) located in New Hampshire. We were given the lamination department data collected over the previous year by our project sponsor (Abhas Joshi), and we utilized multiple statistical analysis techniques in order to determine what factors were contributing to the machines’ downtime. We then assembled our team’s findings and organized them in an easily digestible report that will be presented to our class and company T.C.I.

Benteler Steel Simulation

Team Name: Benteler Steel Simulators

Team Members: Claire Dorsett, Nick Liscomb, Noah Phenice

Sponsor: Xiang Sean Zhou

Advisor: Dr. Jun-Ing Ker

This senior design project is focused on designing and developing an Arena Simulation model of Benteler Steel’s LD81 pipe manufacturing process. The primary goal of this simulation is to identify and insulate bottlenecking issues in the manufacturing process. This model will also be designed to incorporate failure times along with the ability to run different scenarios to measure and compare the severity of different results. In the end, this model will continue to be used by operators and management at Benteler to estimate total processing times.

Alliance Compressors Capstone Project

Team Name: Alliance Compressors

Team Members: Alexander Brodtman, Alandria Ford, Blake McMillian, Frederick Musa

Sponsor: Logan Hughes

Advisor: Dr. Jun-Ing Ker

The purpose of this project was to provide engineers at Alliance with a method for identifying the areas in which bottlenecks occur on their production lines. To accomplish this goal, we separated both lines into zones and placed an andon light in each. We began by choosing data collection points on each line that we planned on using as the locations for our lights. We analyzed historical data as well as the data we collected to determine the options for light functionality. We discussed each solution option as a team and narrowed our selection until we arrived at the best solution. We presented our project sponsor and other engineering managers at Alliance with our findings and recommendation for light functionality. Finally, we developed a plan for collecting data after our solution was implemented to determine if the changes we made had the impact we expected.