Industrial & Systems Engineering Undergraduate Courses

Corequisite: 14:540:202, Prerequisite: (01:640:151 or 01:640:191 or 21:640:135 or 50:640:121) 

Man-machine analysis, motion economy, time study, predetermined time systems, work sampling; introduction to robotics, facilities layout, material handling; introduction to ergonomics and anthropometric, biomechanical, and human-machine interface models. 

Credits: 3

Corequisite: 14:540:201, Prerequisite: (01:640:151 or 01:640:191 or 21:640:135 or 50:640:121)  

Experiments in robotics, time study, work measurement, workplace design and the human-machine interface, facilities layout.

Credits: 1

Prerequisite: (01:640:152 or 01:640192 or 21:640:136 or 50:640:122) 

Probability problems in engineering, conditional probability, discrete and continuous distributions, functions of random variables, interval estimates.

Credits: 3

Prerequisite: (01:640:151 or 01:640:191 or 21:640:135 or 50:640:121) AND (14:440:127) 

Introduction to programming, fundamental data types, flow control, and function; arrays, pointers, and do loops; algorithms and flow charts; GUI concepts.

Credits: 2

Corequisite: 14:540:304, Prerequisite: 14:635:407 

Properties of engineering materials; metals, polymers, ceramics and composites, bulk and sheet forming, traditional and non-traditional material removal processes, polymer processing, laser and energy-beam processes, additive layered manufacturing processes and micro/nano fabrication processes. Basic and computerized machine tools. Process chains, planning and process optimization. Engineering metrology and product quality.

Credits: 3

Corequisite: 14:540:303, Prerequisite: 14:635:407 

Experiments on machine tools: lathes, drilling machines, milling machines, and CNC milling machines; robot workplace design and computer control of machine tools.

Credits: 1

Prerequisite: Permission of departmental chairperson.  Prerequisite for industrial engineering students who wish to be James J. Slade Scholars. 

Extensive reading and study in a particular problem area of industrial engineering under the guidance of a faculty member.

Credits: 

Prerequisite: (01:640:244 or 21:640:314 or 50:640:314) 

Elements of modeling and problem solving. Use of a software package like LINDO, EXCEL to solve real life industrial engineering problems. Linear programming, duality, sensitivity analysis, integer programming, transportation and assignment problems.

Credits: 3 

Prerequisite: 14:540:210 

Statistical estimation; confidence interval; testing hypothesis; engineering applications throughout the course.

Credits: 3

Prerequisite: (14:540:210) AND (01:640:244 or 21:640:314 or 50:640:314)

Modeling and decision making under uncertainty.  Markov chains, Poisson processes, inventory models and queueing systems. 

Credits: 3

Economic decisions involving engineering alternatives, annual cost, present worth, rate of return, and benefit-to-cost; before and after tax replacement economy; organizational financing; break-even charts; unit and minimum-cost public sector studies.

Credits: 3

Corequisite: 14:540:383, Prerequisite: (01:640:244 or 21:640:314 or 50:640:314) AND (01:750:227) 

Programmable automation applied to manufacturing. Computer architecture, sensors and automatic data acquisition, computer control of actuators, continuous and discrete control of processes, computer integration, and local area networks.

Credits: 3 

Corequisite: 14:540:382, Prerequisite: (01:640:244 or 21:640:314 or 50:640:314) AND (01:750:227) 

Use of microcomputers and industrial controllers in controlling machines and processes. Assembly language programming, ladder logic programming, and interfacing controllers to sensors and actuators. Experiments in manufacturing applications.

Credits: 1 

Prerequisite: 14:540:338 

Modeling and analysis of industrial and service systems using ARENA, simulation modeling perspectives, discrete event and continuous simulation, simulation languages, statistical aspects of simulation.

Credits: 3

Prerequisites: (14:540:338) AND (14:540:382) AND (14:540:383) 

OPEN TO 540 STUDENTS ONLY Design principles, material selection, design for assembly, design for manufacturing, and effect of environmental issues on product design.

Credits: 3

Prerequisite: (14:540:303) AND (14:540:304) AND (14:540:384) AND (14:540:399) 

OPEN TO 540 STUDENTS ONLY A team approach to the redesign of a “real-life” product. Alternative engineering plans for improved designs will be developed and implemented. Both written and oral reports will be completed.

Credits: 3 

Corequisites: 14:540:434, Prerequisite: 14:540:320 

Statistical methods for monitoring and improving product quality and decreasing variation. Factorial experiments, variables and attribute control charts, acceptance sampling, on- and off-line process controls.

Credits: 3 
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Corequisite: 14:540:433, Prerequisite: 14:540:320 

Practical application of quality engineering methodologies, statistical software, gage studies, online process control, design of experiments to improve product design, industrial manufacturing processes, and system design.

Credits: 1

Prerequisites: (14:540:311) AND (14:540:338) 

Coordination of activities of both manufacturing and service systems. Systems design; input and output; planning and scheduling. Decision-making problems employing mathematical techniques of linear programming. Sequencing jobs on machines and line balancing techniques.

Credits: 3

Open to Juniors and Seniors.

Legal and ethical aspects of engineering; bids, awards, and negotiated contracts. Liabilities to the public and to employees, contract labor law. Contracts, patents, copyrights, trademarks, and engineering specifications. 

Credits: 3 

Prerequisite: (14:540:201) AND (14:540:202) AND (14:540:303) AND (14:540:304) 

Fundamentals of the design, layout, and location of industrial and nonmanufacturing facilities. Selection of machines and material handling equipment and their efficient arrangement. Emphasis on quantitative methods. Warehouse layout. Facility location theory.

Credits: 3 

Prerequisite: 14:540:320  

The course focuses on acquiring hands-on experience in the organization, modeling, and analysis of raw data to extract pertinent information and actionable insights for industrial and engineering systems. Covered topics include database management using structured query language programming, data processing, analysis, and modeling using statistical programming software, as well as the design and implementation of data science solutions and forecasting methods through project-based learning and case studies from manufacturing, materials engineering, and energy systems.

Credits: 3

Prerequisite: (14:540:311) 

This course addresses the design, analysis, modeling and optimization of selected energy systems (including conventional fossil fuels and renewable wind and solar).  This course will provide the basis for applying mathematical modeling and optimization techniques in energy systems. A set of projects and case studies focused on modeling and optimization of a variety of energy systems will be assigned to students and discussed in details. The course will have hands on experience with data collection, experimentation, simulation and optimization tools as they apply to energy systems. 

Credits: 3

Prerequisite: Permission of department 

Permission of department required. Studies in phases of industrial engineering of special interest.

Credits: 

Prerequisite: Permission of department, Graded Pass/No credit.

ntended to provide a capstone experience to the student’s undergraduate studies by integrating prior course work into a working industrial engineering professional environment. Credits earned for the educational benefits of the experience.

Credits: 3