Texas Tech University, Department of Industrial Engineering
TTU Home Whitacre College of Engineering Industrial Engineering

Research

CAD/CAM Laboratory

Primary Investigator:
Dr. Hong-Chao Zhang
Hong-chao.Zhang@ttu.edu
Phone:
806.742.3543

Website
CAD/CAM Laboratory

The Computer-Aided Design/Computer-Aided Manufacturing Laboratory is maintained in the Department of Industrial Engineering. The lab allows students and faculty to work with the latest computer-aided design and numerical control equipment including a computer-controlled turning and milling centers, CAD work stations equipped with the latest CAD/CAM/FEM/Visualization software and computer vision systems.

Ergonomics Laboratory

Primary Investigator:
Dr. Pat Patterson
Pat.Patterson@ttu.edu
Phone:
806.742.3543

Website
RF/Analog System-on-a-chip (Soc) Design Lab

Manufacturing & Design Group

Primary Investigator:


Phone:
806.742.3543

Website
Manufacturing & Design Group

The Manufacturing and Design Research Group aims to devise the efficient bulk fabrication of novel material systems for their utilization in biomedical applications. In doing so, traditional fabrication and nanotechnology principles are utilized in material design to secure that morphological characteristics of the material system coincide with native tissue architecture, while primarily nondestructive testing techniques are employed for characterization and modeling of newly devised and fabricated materials.

Stochastic Challenge

Primary Investigator:
Dr. Tim Matis
Timothy.Matis@ttu.edu
Phone:
806.742.3543

Website
Stochastic Challenge

As a part of a National Science Foundation Transforming Undergraduate Education in Science (NSF-TUES) grant involving Texas Tech, Missouri University of Science and Technology, and the University of Texas - Pan American, Dr. Tim Matis, associate professor of industrial engineering, has developed a new tool called the Stochastic Challenge.

The tool is a resource for students or anyone wanting to learn more about applied stochastic processes and can be found at www.stochasticchallenge.org. The site includes video tutorials for learning how to apply stochastic processes in real-world contexts, a wiki-style encyclopedia that anyone can edit, and web-based calculators for performing common calculations.