PENNSYLVANIA STATE UNIVERSITY
University Park, Pennsylvania
Department of Industrial and Manufacturing Engineering
Title: Human Factors/Ergonomics Option in Industrial Engineering (MEng, MS)
Granted last 3 years: MS 5, PhD 6
Distance learning available: yes
HFES student chapter: yes (http://www.ie.psu.edu/orgs/hfes/index.html)
Program: This flexible option allows students to customize a program to their specific interests within the full spectrum of human factors applications and interest areas. Throughout the program, emphasis is placed on empirical/statistical data analysis with hands-on lab research and/or practical industrial field studies. Students are encouraged to conduct cross-disciplinary research within areas such as manufacturing, operations research, psychology, bioengineering, engineering science, management, computer science, kinesiology, mining engineering, and safety. At the MS level, the student will have achieved both the technical tools and practical experience needed for an industrial position, while at the PhD level the student will have attained the intellectual rigor and academic competence to work in an academic or research setting.
Contact: Andris Freivalds, Penn State University, 310 Leonhard Building, University Park, PA 16802; 814/863-2361; email@example.com,
Catalog: Graduate Office of Admissions, Kern Bldg., Pennsylvania State University, University Park, PA 16802
Deadlines: February 15 fall, September 1 spring
GRE: v + q + a required, but no minimum
Other: TOEFL IBT 80, Spk 19, Paper 550, CBT 213. Those without a bachelor's degree in engineering must take approximately 40 semester credits of quantitative content, including math (through differential equations) and physics.
Work experience: medium
Students applying last year: 14
Entered program: 7
TUITION AND FEES:
% receiving: 70
Available: Fellowship, TA, RA, scholarship, tuition and fees covered.
Apply: with application
MS: 32 units, research required, no exams, languages, or practical experience, 1 1/2 years
Nonthesis option: no
PhD: 49 units, candidacy, comprehensive and final defense exams, research required, English required, no practical experience required, 3 1/2 years
Required courses (units): Engineering of Human Work (3), Engineering of Cognitive Work (3), Experimental Design (3)
Electives: Human/Computer Interface Design (3), Safety Systems Engineering (3), Mechanics of the Musculoskeletal System (3), Human Reliability
Required courses outside department: 0
Recommended courses outside department: 2-3
Distance learning: Courses IE327, IE419, IE479, IE552, IE553, and IE558 are available online, with a Web-based certificate presented after completion.
Class size: 8-10
Research facilities: Ben Niebel Work Design Lab: computers, energy expenditure measurement equipment, strength testers, electromyographic equipment, bicycle and other ergometers, sound/hearing analysis equipment, light/vision analysis equipment, eye-tracking system, motion analysis system, video capture and digitizing equipment. Additional facilities include extensive arrays of robotics, machining equipment, workstations, quality control, and virtual reality hardware. Center for Cumulative Trauma Disorders, Noll Human Performance Lab: environmental heat/cold stress chambers. Center for Locomotion Studies: large array of locomotion research equipment. Pennsylvania Transportation Institute: Mack/Renault truck simulator, 5,000 ft. oval test track, crash impact tester. School for Information Science and Technology: software usability labs. Interdisciplinary projects have been conducted using the facilities and resources of the Psychology, Mechanical Engineering, Gerontology, Physiology, and Kinesiology Departments.
Teaching: MS and PhD students may serve as TAs or lab assistants. PhD students may serve as lecturers for entire classes.
Current research: Models to predict CTD risk for jobs; strain-gauge and FSR instrumented glove to measure job stressors; cadaver hand studies to validate biomechanical hand models; development of improved and innovative telerobotic and virtual reality interfaces; analysis of system complexity and its impacts on technology development and strategy, product/process interactions, and human/technical interfaces; technology forecasting and decision making under uncertainty; supply chain integration, S-curve modeling, and information technology-assisted advanced Web search methods; analysis and modeling of skilled human performance in complex systems and environments; human-environment interactions in cognitively demanding tasks using inductive inference methods, acquisition of complex cognitive skills, development of adaptive interface technologies, applications to human-computer interfaces, medical product design, consumer products, and air traffic control; improving the health and well-being of individuals.
Active: 18 men, 6 women
First-year students: 10
Mean scores: MS: GRE 473 v, 758 q, 770 a, GPA 3.5; PhD: GRE 487 v, 763 q, 601 a, GPA 3.6
David J. Cannon, PhD 1992, Stanford U; human-machine systems, robotics, automated material handling, virtual environments
Andris Freivalds, PhD 1979, U Michigan; biomechanics, cumulative trauma disorders
Gul Kremer, PhD 1997, U Missouri; decision analysis, product design
Scarlett Miller, PhD 2011, U of Illinois; innovative product design, human-computer interface design
David Nembhard, PhD 1994, U of Michigan; workforce engineering, data mining
Matt Parkinson, PhD 2004, U of Michigan; anthropometry, design for human variability
Ling Rothrock, PhD 1995, Georgia Tech; human-machine performance assessment and modeling
Conrad Tucker, PhD 2011, U of Illinois; innovative design using social media, product families
[Updated May 2012]