Client: Los Barrios Unidos Community Clinic
Team: Shorjoe Bhattacharya and Harvey Hauw
Faculty Advisors: Drs. Barr, Bing Year: 2017
Documents: Presentation, Report
Los Barrios Unidos Community Clinic, located in West Dallas, offers services in many different healthcare areas including pediatric care, behavioral health, and obstetrics. The focus of this project was in the obstetrics department, at which patient satisfaction was dropping due to long wait times leading to long appointment durations.
Our team was tasked with collecting time and motion data, mapping out current workflows of the clinic, running a simulation model, and analyzing the results. We collected data with a simple yet effective time and motion study where we asked the individual patients to log their times as they went station to station in the clinic. We also learned the workflows and layout of the clinic by talking to staff members at the location. This was data was used in a computer simulation model of the Obstetrics wing, developed using “MedModel” (specialty healthcare facilities simulation software). The simulation results revealed ways to reduce patient wait times to improve the patient experience at LBUCC.
Client: Frito Lay
Team: Matt Alfano, Brittany Masi
Faculty Advisor: Dr. Barr Year: 2010
Documents: Presentation, Report, Video
The project is to design and create an out-of-stock inventory tool that is user-friendly and able to historically scan data while predicting inventory shortfall at the club/SKU level. More features of this project include determining what Inventory is needed by club/SKU and determine delivery frequency by club. We decided that only these opportunities fell into the scope of our project.
After consolidating all of the available information into one database we removed unnecessary tables to increase the processing speed of analyzing the product “Spy Reports” generated by their current database queries. We analyzed two of the highest-demand product lines that Frito Lay stocks at Sam’s Clubs nationwide. These two products are Smart Mix and Variety Mix. Read more…
Categories: Final report, Forecasting, Inventory management, Manufacturing, Operations, Planning, Presentation, Statistical Methods, Transportation, Uncategorized, United States, Video Tags:
Client: Frito Lay
Team: Rodrigo Cantu, Sergio Hueck, Rafael Virzi
Faculty Advisor: Dr. Barr
Year: 2012
Documents: Presentation, Report, Video
Gamesa, a subsidiary of Frito-Lay, is a Mexican Cookie company that sells its product in many different countries, including the United States. Their products, which includes different types of cookies and crackers, are targeted to the Mexican population. The company’s United States sales force consists of 38 representatives in 16 different regions, organized by their different routes to market, location of warehouses, and population density. Today, they dominate the U.s. Hispanic cookie market occupying 50 percent of the market.
The problem we address for Gamesa is: should they should deploy more sales representatives and, if so, where would their optimal locations be? With the current economic recession and the entering of Gamesa’s main competitor, Bimbo, sales have been dropping in the different regions. This resulted in Gamesa asking themselves if they needed a bigger sales force. They also wanted to know what regions could be good to add representatives in the future depending on the migration of the population or the strategy of the competition. Read more…
Categories: Final report, Forecasting, Manufacturing, Marketing, Operations, Optimization, Presentation, Real estate, Simulation, Statistical Methods, Uncategorized, United States, Video Tags:
Client: Frito Lay
Team: Javier Gonzalez, Fernando Sada, Marcelo Sada
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
In order to satisfy the large Hispanic market in the United States, Frito Lay imports products manufactured in Mexico by Gamesa, a sister company to Frito Lay due to the fact that they are both owned by PepsiCo. Gamesa has plants all across Mexico, having the main ones located in Celaya, Vallejo, Obregon and Monterrey. In the past, all products being imported into the U.S were produced in Obregon, a city in Northwestern Mexico. As of today, the Hispanic population has dispersed all across the country, increasing Gamesa’s market to a large portion of it. Gamesa’s products are now being distributed all the way from California, to Texas, and onto the East Coast and Midwest. Imports have increased so much that in order to satisfy the demand, Gamesa has started producing all across Mexico for exports. Read more…
The stories of three Senior Design projects from the clients’ point of view, including North Texas Food Bank, Texas Department of Transportation, and Southwest Airlines:
Client: Carrollton Concentra
Team: Daniel Olivares, Beverly Ross, Devin Kyles
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
Concentra presented the problem of cross-staffing some of its employees throughout its centers. The problem addresses a potential decision of staffing methods of which the options were to staff to the market or create a cross-staffing model. These decisions relied upon the variability of patient visits among the centers and the ability to schedule based on future forecasted patient visits. Ultimately, the question was to find if there is an opportunity to staff across all centers or must it be dynamically adjusted based on forecasting by center. A solution to this problem would potentially decrease patient wait times and turnaround times (a patient’s check-in time to checkout time), idle times in which staff members are not performing any duties, and times in which centers experience a heavier traffic flow. Read more…
Client: Texas Plaza, Prof. Peiser
Faculty advisor: Dr. Barr
Year: 1982
Documents: Final report (PDF)
Appeared in different form as a journal cover article. R. Peiser and Scot Andrus, Phasing of Income-Producing Real Estate, Interfaces 13:5 (1983) 1-9.
Integer programming techniques were used to determine the order in which to build office buildings and when to put the space on the market for a seven-building, 90-acre, mixed-use real estate project in Texas. The output of the optimization provided development managers with the schedule for opening each building, the amount of space to be leased each year in each building, and the annual cash flows to the owner.
Client: Lockheed Martin Missiles and Fire Control
Team: Stephen Beckert, Brandon Joslin, Pierce, Meier
Faculty Advisor: Dr. Barr
Year: 2010
Documents: Final Report, Presentation
Lockheed Martin presented us with a project more exciting than we could ever imagine: aiding the research into ways to model the effects of an Electromagnetic Pulse (EMP). EMP is extremely devastating and can be caused by both natural and man-made events. EMP primarily affects electronic devices, rendering them useless or destroyed. Since the United States is heavily dependent on electronic interfaces, we are extremely vulnerable to this effect. In addition to this vulnerability to the EMP effect, the United States has a complex system of connected critical infrastructures that have not been studied as interrelated systems. This presents a major problem, how can one forecast the possible failures of such a massive complex system? Read more…
Categories: Computational probability, Dallas-Ft. Worth Area, Defense, Energy, Final report, Forecasting, Government, Integer programming, Nonlinear programming, Operations, Planning, Presentation, Reliability analysis, Scheduling, Simulation, United States, Video Tags:
Team: Robert Walters, Donnet Phillips
Faculty advisor: Dr. Barr Year: 1986
Documents: Final report (PDF)
There are many optimization procedures and algorithms that can be implemented for delivery operations. The thrust of this paper concerns the following topics and their relavance to delivery vehicles: equipment replacement, truck utilization and optimization, and efficient routing practices. Read more…
Client: Arlington Texas Police Department
Team: Ron Andrews, Blake Robinson
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
The Arlington Police Department is responsible for policing the city of Arlington to achieve a safer community. The policing of the city is divided roughly into four main areas (north, south, east, and west) with each respective area possessing its own police station. The Arlington Police Department requested insight into the placement of the police stations to see if they were effectively located to process the level one crimes that originate from each main area. If a main area was not adequately covered, areas could be hypothetically redrawn to accommodate effective policing.
Our method of analysis included the use of in-depth data analysis and a pure network model that had the potential to take into consideration Euclidean distances, time schedules, crime severity and political issues. Our findings indicated that the placement of police stations given current population levels were placed reasonably close to where our model suggested they should be placed. It was also discovered that complex issues such as political issues and crime severity are hard to quantify within a model given due to the ambiguous nature of the data.
