Texas Tech University

Research

Industrial engineers gain knowledge and experience in the areas of applied optimization, data analytics, engineering management, supply chain and logistics, transportation, healthcare delivery, medical decision making, economic and cost analysis, ergonomics, and safety. They also build on that knowledge to integrate decision support systems. The department is also developing research and coursework in the emerging areas of advanced and additive manufacturing utilizing a systems approach.

 

Advanced Manufacturing Laboratory

CAD/CAM Laboratory

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


The AML was established in the early 1990's under the direction of Dr. Hong-Chao Zhang. The objective of the AML is to develop advanced manufacturing technology utilizing the latest scientific and engineering advancements. The AML is comprised of faculty members who share an interest in manufacturing research and desire to develop original research projects and proposals. The AML focus on both sustainable manufacturing and sustainable design.

CAD/CAM Laboratory

CAD/CAM Laboratory

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


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

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

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

Stochastic Challenge

Stochastic Challenge

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


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.

Industrial, Manufacturing & Systems Engineering