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Industrial Engineering

Spares Planning Manual at Tokyo Electron


Sponsor: Tokyo Electron America

Student Team: Thierno Bah, Claire Barbosa, David Bogran, Quasadia Limbrick

Currently, Tokyo Electron does not have a global spares planning manual. While work procedures do exist, there is a lack of general guidelines and methods for managing and planning spare parts. To address this issue, this project will develop a Spares Planning Manual to provide a high level guidance for the Regional Planners as well as Global Planners. The team will evaluate key performance indicators, such as forecasting error and inventory service levels, and include these in the manual in order to set baseline evaluations of the spare parts’ inventory system.

The Impact of Hospitalists Monthly Schedules on Patient Perceptions of Quality of Care


Sponsor: Central Texas Medical Center

Student Team: Kobra Dehghani, David Dzubay, Khaled El Haj, Kelsey Faubion

Hospitalists are physicians who are dedicated to the delivery of comprehensive medical care to hospitalized patients.  Hospitalists visit with patients on a daily basis and are often scheduled to be on-call to take care of patient unanticipated change of conditions. Among many responsibilities, they are also responsible for authorizing a patient’s release from the hospital. Recent research has shown that HCAHPS patient satisfaction scores are higher when patient discharges occur early in the day. The patient discharge process is complex and involves setting specific challenges that limits the generalization of solutions. The aim of this study was to assess the effect of hospitalists’ monthly schedules in the patient discharge process. The results show that when hospitalists are not scheduled to be on-call the day before their round visitations, discharge times are reduced significantly. Therefore, a scheduling model is presented that develops hospitalist monthly schedules while minimizing the number of days they are on-call the day before performing patient visitations (rounds).  A case study is presented that considers three intensive care units from a hospital located in central Texas.

Loading Tube Assembly


Sponsor: Hunt & Hunt Mechanical

Student Team: Nolan Besetzny, Danielle Duffy, Denise Lopez, Lucio Salazar

A new workstation for the assembly of a fractal loading tube at Hunt & Hunt Mechanical is not designed for optimal efficiency. Previously, the worker was assigned to the machine only, and the assembly was done elsewhere. Because the machine cycle time was so long, the worker was idle for a considerable amount of time. The worker suggested a solution where he would assemble in the same area while the part was being machined. He would now be doing two tasks at the same time. A writing desk was improvised for the assembly operation. The desk and workstation area are not optimal for the assembly process. This project will focus on designing a workstation to resolve the problems in the current design using lean manufacturing principles.

Inventory Lot Optimization and Layout


Sponsor: Hunt & Hunt Mechanical

Student Team: Thomas Caballero, Andrew Cano, Armando Cerna-Orozco, Christopher Tyrone

The company’s pipe yard lot stores raw material valued at $20M. Material locations are not optimal, resulting in higher transport times and lower throughput times since there are more efforts spent in loading & unloading operations, as well as in locating material. Due to a cluttered space, safety risks are higher when materials are being handled. Time studies, simulation modeling, cost & benefit analysis will be performed in this project in order to determine an alternative layout planning to better satisfy the flow of product in and out of the pipe yard.

Distribution Center's Order Batching Simulation


Sponsor: Undisclosed Distribution Center

Student Team: Kathryn Esparza, Kingsley Ike, Jared Krischke, Andre McCoy

Distribution centers spend most of their resources optimizing the efficiency of order picking operations. Order picking is the process of retrieving from the warehouse the stock keeping units (SKU’s) contained in an order. The purpose of this project is to apply an order-batching data-mining algorithm that groups orders with items that are ordered frequently together to reduce picking time. We will develop a simulation to test our algorithm. Our goal is to increase the orders picked per hour by one percent in relation to the existing distribution center’s performance.

Fabrication Capacity Plan


Sponsor: Philips Lighting

Student Team: Caroline Bowser, Alexander Kenis, Blake Matheson, Zaid Sohail

Currently the fabrication area within Philips Lighting is producing items to ship the same day, which leaves Philips vulnerable to shipping late orders and subsequently a potential loss of revenue from disconcerted customers. There is a capacity plan for several key workstations, but the data that feeds into the plan needs to be thoroughly validated. One area of concern is the specialized labor requirements, which instigates not only accrued overtime, but also decreases the labor-optimizing flexibility of the fabrication lead. Additionally, processing equipment is becoming obsolete, which limit the speed of the fabrication system and contribute to the back-log of production. In this project, a Lean Capacity Plan will be developed to to eliminate the long lead-time process for fabrication.

Paint Line Optimization


Sponsor: Philips Lighting, San Marcos, TX

Student Team: Latravian Haggerty, George Mikhaylov, Clinton Stoeck, Agustin Velasquez

The company’s Paint Line currently has the capacity to run 8 - 10 hours continuously.  Shifts are staggered by two hours in order to setup the line, which equates to the line running for 10 - 12 hours. Furthermore, the Finished Goods staging area is unorganized and it consistently overflows since Paint has to paint their orders 5 days in advance of customer ship dates. This project attempts to improve efficiency of this production area by using Lean Manufacturing principles.

Shredder Equipment Failure Modes and Maintenance Planning


Sponsor: CMC Steel Texas

Student Team: Jeremy DiGiovanni, Nevzat Doga Hacisalihoglu, Logan Hanson, Matthew Mitcham

Production equipment maintenance planning is a weekly practice within all production departments at Commercial Metals Company Steel Texas. Prioritizing equipment repairs and preventive maintenance work is a challenge because there is no equipment performance data to support a plan of action. This project will identify equipment’s failure modes and the effects on production throughput by using simulation modeling.

Bottleneck Problem at CEMEX-Balcones Quarry


Sponsor: CEMEX USA, Balcones Quarry

Student Team: Jonathan Edmunds, Fernando Espinosa De Los Monteros, Joshua Klein, Arda Onkol

CEMEX USA Balcones Quarry currently has a bottleneck issue with the haul trucks in the pit. The pit is the area of the Quarry where the raw material is loaded into 100-ton haul trucks. Upon being loaded in the pit, the haul trucks then take the raw material to the “dump zone” to dump the material into the primary crusher, where the raw material is crushed to a desired size and set to its allocated location. The bottleneck in the system is the damper on the amount of material that gets produced each day. CEMEX wants to know the best solution to eliminate the present bottleneck; should a second dump location be implemented. This project focuses on the use of data analysis and simulation modeling to locate the bottleneck in the current haul system. Once the bottleneck is located, the data will be further analyzed in order to determine and develop and optimized system that will create an increased product (material) throughput.