Undergraduate ENP Course Descriptions

ENP 61 - Introduction to Human Factors and Ergonomics:
This course is an introduction to the engineering principles of Human Factors design, through the Mechanical Engineering department. Students learn about human performance, safety, and legal concerns of Human Factors designers. Topics also include: applied descriptive and inferential statistics, mechanical drawing, model making, anthropometrics, biomechanics and environmental concerns, such as heat, stress, noise levels, and lighting. The professor draws examples from his own experiences to illustrate topics. Grade is based on homework assignments, labs, a group design project presentation and report, which allows the student to apply all course work, and a final exam, as well as class participation. Taught by Professor Kreifeldt.

ENP/PSY 120 - Project Study in Human Systems:
This is a project class taught by faculty from both Mechanical Engineering and Psychology departments. Real problems for group projects are provided by several local companies each year. Past areas of study have been: consumer product design, computer hardware and software evaluation, control and display design for a nuclear control station, and workspace/space design. This course should be taken as far into the student's program as possible because it is intended to bring together all of the prior Human Factors knowledge that the student has obtained. This course is cross listed as ENP 120 and PSY 120. Grade is based on the three oral group presentations (proposal, interim, and final) and three written reports (proposal, interim, and final). One day each week is devoted to faculty and guest lectures while the other is provided to the students for their own site visits and group meetings. Prerequisites: Junior standing, consent, and ENP 161. Co-taught by Professors Kreifeldt and Soraci each Fall.

1 of the following 2 courses must be taken:

ENP 152 (CE 152/ES 152) - Engineering Systems: Stochastic Models:
This course involves the study, evaluation, and design of complex stochastic systems, emphasizing probability. Topics that are discussed and exemplified include: Markovian systems, birth-death processes, queuing theory, probabilistic decision analysis, quality control, computer simulation techniques, and discrete system simulation programs. Grades are based on homework assignments, a midterm exam, a final exam and an individual project. The course is designed for upper-level students, and although probability and statistics are not required, they are highly recommended as prerequisites to this course. CE 152 can be taken independently of 151. Prerequisite: Junior standing or consent, as well as ES 15, ES 16, an ENT, and an END. Taught by Professor Levine in the Spring semester.

ENP 161 - Human Factors in Product Design:
This course provides a thorough understanding of the Human Factors product design process. Topics include: patent search, literature search, morphological ordering, ergonomic critiques, interviews, questionnaires, focus groups, time/motion studies, brainstorming techniques, design specifications, design concepts, prototyping, testing, and refinement. Students are required to carry out most of the preceding steps in an individual design project, and all of these steps for a group design project. The group project includes a proposal, interim report, final report, and oral presentation. Grade is determined by these 2 assignments and 2 Psychophysics lab reports. Prerequisites: Junior standing and ENP 61 or consent. Taught every Spring by Professor Kreifeldt.

ENP 162 - Man-Machine Systems Design:
Students taking this course learn fundamental and advanced techniques for human-machine systems design. The dynamic and cognitive characteristics of humans and machines are explored, emphasizing the importance of this concern in designing an efficient, functional relationship. This course is valuable to Human Factors designers because they learn the tools of evaluating equipment and system design by focusing on the human-machine interactions. Some topics discussed include: information theory, decision-making, reaction time, human-machine models, human-computer interaction, signal detection theory, and human reliability. Much of the material is theoretical, and those theories are supported by examples in lecture, laboratory experiments, and homework assignments. Grade is based on five laboratory reports, five homework assignments, and a final exam. Prerequisite: ENP 61 Taught by Professor Kreifeldt every Fall semester.