Optimize Warehouse Layout and Distribution Center Processes
Student Team: Chandler Franklin, Alonso Garcia, Juan Garcia, Kristen Kramer
Faculty Advisor: Dr. Clara Novoa
The Goodwill Resource Center depends on the amount of storage available, the flow of the salvage that goes through the warehouse, and the routing of the trucks that bring the salvage in order to run smoothly. Our goal is to help find an efficient way to better organize the storage systems, improve the overall flow of the salvage from the moment it arrives at the facility to the moment it leaves, and to optimize the routes of the trucks from each retail store and donation center to the warehouse. Using a computer simulation model constructed from the store’s current layout, we hope to find the most efficient method of directing salvage. We will also use the known travel times in order to simulate the truck routes and find the optimal routes based on store demand.
Scheduling Patients and Providers at Outpatient Clinics
Sponsor: Central Texas Medical Center
Student Team: Darbie Walker, Emma Shanks, Calvin Weimen, David Montoya
Faculty Advisor: Dr. Eduardo Perez
Live Oak Health Partners is a multi-specialty medical practice located in central Texas. We are organizing the doctor schedules as well as assigning patients based on a new or existing patient status. We are creating an interface, so each day the nurses can plug the number of appointments for patients to be seen into a program and it will create the most time efficient schedule for that day. Our model will also account for possible no shows and walk-ins. This change in scheduling will help to improve the happiness of the patients and decrease the amount of phone calls missed, and save the amount waiting time for all patients.
Simulation of HEB Distribution Center
Student Team: Gabriel Carreno, Andrew Fails, Stephen Rosales, Richard Wambua
Faculty Advisor: Dr. Jesus Jimenez
This capstone design project seeks to improve the cases throughput per hour by one percent at the San Marcos H.E.B. Service Center. The focus of the project is to optimize the arrangement of general merchandise and slow-moving products in order to improve the H.E.B.’s order fulfillment process. Store orders will be data mined to create a warehouse layout based on association rules algorithms. The analysis will be performed in R and R Excel. Due to the stochastic and dynamic behavior of the warehouse operations, simulation will be conducted in Witness in order to evaluate the resulting warehouse layout configuration. Results of the integrated data mining and simulation study, as well as the recommendations for implementation of our algorithms will be presented.
Insulated Concrete Form Pre-Engineering Construction
Sponsor: Ingram School of Engineering
Student Team: Michael Mullen, David Holt, Matthew Snead
Faculty Advisor: Dr. Michelle Londa
Energy conservation is the practice of reducing the use of energy. There are many ways to reduce the energy consumption of a pre-existing home; however, most of these are minor improvements at best. The goal of this project is to propose an optimized facility that will produce a suitable new building design using Insulated Concrete Forms (ICF). A suitable new ICF design will have a reduced energy use of at least 30% when compared to a standard home. The design will also result in a more sustainable process throughout the home building industry with a reduction in construction time and waste. Furthermore the entire design of the process contains no HCFC, formaldehyde, asbestos, fiberglass, harmful CFCs (chlorofluorocarbons), nor is there any degree of “off-gassing”. This design is natural disaster resistant, energy efficient, and more earth-friendly during the construction process. The facility will manufacture polystyrene foam panels that will be constructed into walls prior to being shipped to the construction site.
Zero Carbon Production and Distribution Networks
Sponsor: US Department of Agriculture
Student Team: Alejandro Arias-Garcia, Diego Martin Bulacia Limpias, An Pham, Michael Villanueva
Faculty Advisor: Dr. Tongdan Jin
The project aims to model and design an eco-friendly production-distribution network under zero-carbon emission criterion. To achieve this goal, renewable energy sources including wind turbines and solar panels will be integrated into the enterprise facilities. A main challenge of adopting wind- and solar-based generation is the power intermittency and equipment cost. We tackle this complex production-distribution network design in two steps. First, a stochastic programming model is formulated to optimize the production planning and transportation schedules under intermittent energy supply. Second, we allocate onsite charge stations in manufacturing facilities and central warehouses to ensure the timely recharging of electric transportation fleet. The stochastic optimization is solved using Exel solver and its performance is further tested in different cities around the world with diverse weather profiles.
System to Replenish a Single Piece Flow Assembly Line
Sponsor: Philips Lighting
Student Team: Daniel Dawson, Reid Pierson, Richard McEvoy-Kemp, Eleazar Zavala
Faculty Advisor: Dr. Jesus Jimenez
Phillips Lighting wishes to design the “milk runs” operations of a newly improved assembly line. A milk-run is a well-known lean manufacturing practice that collects raw materials and components from different suppliers and delivers them into a centralized location, in this case the assembly line. This capstone design project attempts to evaluate the milk run operations by using discrete event simulation. The assembly line has two types of buffers, referred to as the “Buffer A” and “Buffer B”. Buffer A serves as a storage of raw materials and Buffer B serves as a storage of sub-assemblies and housing parts. The simulation model, built in Witness version 14, measures the throughput of the assembly line and the service levels associated with Buffers A and B. The factors to be simulated include the order quantities, reorder points and bin sizes of the Buffers. Results of the simulation study, as well as the recommendations for implementation will be generated as a result of this project.
Process Improvement for a Production System with Unknown Demand
Sponsor: An Anonymous Airline Company and the Lanner Company
Student Team: Meghan Travis, Gina Adibi, Samantha Ruiz, Andrew Schneider
Faculty Advisors: Dr. Jesus Jimenez, Dr. Tongdan Jin
This capstone design project targets the manufacturing and assembly process for insulated materials in kits for different airlines. This raises an issue regarding labor-intensive and high process time variability due to the deviation in each airline’s products since they are custom made. The project aims to design a more efficient system that improves the throughput rate by 10% with technology methodologies and allows the deliverables to be shipped on time.
Freestock-Vendor Managed Inventory
Sponsor: Phillips Lighting
Student Team: Ben Ruby, Jeffrey Howell, Tiffanie Martin, Alice Cook, Dax Trip
Faculty Advisor: Dr. Jesus Jimenez
In December 2014, approximately 13% of all missed delivery dates in Phillips -San Marcos were a result of Freestock-VMI not having the necessary material on site for the assembly line to complete the manufacturing process for the product. Currently there are no guidelines to what should be considered Freestock and some Freestock components have lead times upwards of 13 weeks. Additionally, planning does not have visibility to inventory or demand for Freestock items, and therefore cannot anticipate shortages that result in missed customer orders. This project aims to determine which components should be considered for Freestock-VMI versus purchase-consignment, while increasing its ability to view usage and assigning responsibility for clear ownership in the Freestock-VMI process.