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Information for Students

PENNSYLVANIA STATE UNIVERSITY
University Park, Pennsylvania
Department of Industrial and Manufacturing Engineering

PROGRAM BACKGROUND

Title of program
  • Human Factors/Ergonomics Option in Industrial Engineering
Year human factors/ergonomics program was established
1980
Department sponsoring program
Industrial Engineering
Contact person for more information, including applications
Andris Freivalds
Penn State University
310 Leonhard Building
University Park, PA 16802
814/863-2361
axf@psu.edu
Web site
http://www.ie.psu.edu/Graduate/graduate.html
Academic calendar
Semester
Human factors/ergonomics graduate degrees offered
MS

PhD

Goals, objectives, and emphasis of the program
The constantly increasing complexity of human-machine systems requires ergonomists to provide safe and efficient human-machine interfaces. Glaring results of poor ergonomic design are routinely observed in near catastrophes in transportation, complex industrial processes, military systems, and other human-machine environments. Engineers need a basic knowledge of ergonomics and human factors engineering, and should be specially trained to serve as ergonomic design and implementation leaders in industry.

The Human Factors/Ergonomics Engineering program provides an outstanding breadth of ergonomic knowledge plus competence within an area of specialization. The core areas include: 1) knowledge of the physical, physiological, and cognitive aspects of people, 2) research, analysis, and design methodologies, 3) mathematics and computer skills, 4) research experience via the M.S. thesis, and 5) practical experience via industrial projects, consulting experience, internships, and other university projects.

Number of degrees granted during last 3 years
3
Can students attend part-time?
Yes
Distance learning courses
Yes

APPLICATION PROCESS

Application deadlines
December 15 for Fall, September 1 for Spring
Application fees
$65
Are separate applications required for university and department?
No

ADMISSION REQUIREMENTS

Minimum requirements
Grade point average (A = 4.0): 3.0

GRE Combined: no specific minimums

TOEFL IBT 80, Spk 19, Paper 550, CBT 213

Undergrad degrees, backgrounds, or course work required or recommended for admission
A quantitative science, if not engineering.
Importance of other criteria as admission factors
Previous research activity: Low

Relevant work experience: Low

Extracurricular activities: Low

Letters of recommendation: Medium

Tuition and fees
Per semester: $9,941 for PA residents; $16,693 for nonresidents

ADMISSIONS

Number of students applying to the human factors/ergonomics program last year
61
Number of students accepted into the program last year
25
Number of students entering the program last year
7
Anticipated number of openings per year for the next two years
7

FINANCIAL ASSISTANCE

Percentage of students in program receiving financial assistance
75%
Amounts received per year
Average stipend: $9,247 + tuition shown above
Types of assistance available
Teaching assistantship (tuition exempt)

Research assistantship (tuition exempt)

Fellowships (tuition exempt)

When should students apply for financial assistance?
At the same time as submitting application for admission

DEGREE REQUIREMENTS

Graduate degree offered
MS
Number of units required
32
Exams required
None
Language requirements
None
Research required
Paper
Practical experience required
None
Typical number of years required to obtain degree
1

Graduate degree offered
PhD
Number of units required
49
Exams required
candidacy, comprehensive, and final defense exams
Language requirements
English
Research required
Yes
Practical experience required
None
Typical number of years required to obtain degree
3.5

CURRICULUM

Required courses (credit hours)
Engineering of Human Work (3), Engineering of Cognitive Work (3), Experimental Design (3)
Elective courses (credit hours)
Human/Computer Interface Design (3), Safety Systems Engineering (3), Mechanics of the Musculoskeletal System (3), Human Reliability Analysis (3)
Number of courses outside department that are required
0
Number of courses outside department that are recommended
2–3
Distance learning courses
Courses IE327, IE419, IE479, IE552, IE553, and IE558 are available online, with a Web-based certificate presented after completion.
Average or typical class size in a required course
8–10

RESEARCH/TEACHING OPPORTUNITIES

Research and support facilities available to students in the program:
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.

Human Performance Assessment and Modeling Laboratory (HPAM): With six Intel Pentium 4-class workstations and 20 PCs, this lab focuses on the understanding of operator constraints, abilities, and goals in the context of dynamic task environments and the design of systems to facilitate multi-modal man-machine interactions. Research within HPAM forms a mutually-supporting triad with human-in-the-loop simulations informing the development of inductive learning models to test hypotheses grounded in cognitive science.

Teaching opportunities available to students in the program:
MS and PhD students may serve as TAs or lab assistants. PhD students may serve as lecturers for entire classes.
Current research activities and projects being carried out by program faculty and/or students:
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.

STUDENT STATISTICS

Current number of active students in program, by gender
men: 6

women: 8

Current number of first-year students in program
2
Number of current HF/E postdocs
0
Of the number of those graduating in the past year, students gained employment in
Academia: 100%

Industry: 0%

Government: 0%

Faculty-to-student ratio
1 to 2

FACULTY

David J. Cannon, PhD 1992, Stanford University; human-machine systems, robotics, automated material handling, virtual environments
Andris Freivalds, PhD 1979, University of Michigan; biomechanics, cumulative trauma disorders
Gul Kremer, PhD 1997, University of Missouri; decision analysis, product design
Scarlett Miller, PhD 2011, University of Illinois, innovative product design, human-computer interface design
David Nembhard, PhD 1994, University of Michigan; workforce engineering, data mining
Ling Rothrock, PhD 1995, Georgia Tech; human-machine performance assessment and modeling

[Updated July 2015]

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