Current course schedules, deadlines, and other information are available via the University Registrar. Below is a list of courses offered by the Department of Industrial and Systems Engineering.
Credits: 3; can be repeated with a change in content up to 6 credits; Prerequisite: MAC 2312 with a minimum grade of C.
Computer programming and the use of computers to solve engineering and mathematical problems. Emphasizes applying problem-solving skills; directed toward technical careers in fields employing a reasonably high degree of mathematics. The programming language used depends on the demands of the departments in the college. Several languages may be taught each semester, no more than one per section. Those required to learn a specific language must enroll in the correct section. (M)
Credits: 0-3; Prerequisite: Department permission
Provides firsthand, supervised research with a faculty advisor or postdoctoral or graduate student mentor. Projects may involve inquiry, design, investigation, scholarship, discovery, or application.
Credits: 1
Introduction to the field of industrial and systems engineering. Provides an overview of methodological and application areas as well as career paths.
Credits: 3; Prerequisite: ESI 3215C and EGM 2511 with minimum grades of C.
Introduces the techniques/concepts to understand users and workplace requirements for the design and sociotechnical systems. Topics covered include methods for work measurement, human cognitive and physical capabilities and limitations, and workplace requirements. Applications for design, including computer displays, noise, repetitive and high physical effort tasks are presented.
Credits: 3; Prerequisite: MAC 2312 with a minimum grade of C.
Basic principles and applications of economic decision-making between alternatives encountered in engineering systems projects. Analysis includes methodologies of economics and finance in addition to engineering fundamentals.
Credits: 3; Prerequisite: PHY 2049 and ESI 3215C with minimum grades of C.
Safety history and litigation; accident causation; safety organizations and agencies. Approaches to occupational safety and risk management. Product defects and safety program development; product liability; Consumer Product Safety Commission. Hazard communication standard. Workers’ compensation. OSHA safety standards and codes; OSHA record keeping. Common occupational hazards.
Credits: 3; Prerequisites: EIN 3241 and EGM 2511 with minimum grades of C.
Covers advanced topics on human factors and usability concepts and methods, including prototyping and design, usability testing, design of experiments, forensics, and systems design applied to typical human factors domains such as IT, healthcare, transportation, and command and control.
Credits: 3; Prerequisites: EIN 3241 and EGM 2511 with minimum grades of C.
Focuses on applications of advanced topics in human factors and design within various industrial engineering-related domains. Students will be introduced to important domains for human factors work in industry and academia, such as user experience in information technology, healthcare human factors, traffic safety and driving, aviation, and command and control. Students will apply human factors methods and concepts to problems within these domains through case study projects and assignments.
Credits: 3; Prerequisites: ESI 4312, ESI 4313, ESI 4523, STA 4322, ESI 4356, EIN 4354 and EGS 4034 with minimum grades of C and 5EG standing.
Integration of industrial and systems engineering methodologies; emphasizes methods of successful implementation. Project and case-study oriented.
Credits: 3; Prerequisites: ESI 4321 and ESI 4313 with minimum grades of C.
Develops analytic abilities to formulate and solve inventory and logistics problems faced by today’s firms. Learn to take a comprehensive view of complex inventory and supply-chain systems; develop abilities to model, optimize, and design such systems.
Credits: 4; Prerequisites: ENC 3250 or ENC 3254 and EML 2023 or equivalent with minimum grades of C; Co-requisite: EIN 4354.
Introduces fundamental concepts in several main areas of industrial engineering, such as facility planning, material handling systems, work analysis and design. Covers topics such as analysis and design of workspace and flow, facility location and layout, material handling systems, motion and time studies, and work sampling.
Credits: 3; Prerequisites: ESI 4312 and STA 4321.
Design of flow line, cellular, and flexible manufacturing systems. Design and control of lean manufacturing systems. Continuous improvement, small lot production, setup-time reduction, equipment improvement,t and maintenance. Principles and control of push and pull manufacturing systems. Production planning and operations scheduling.
Credits: 1 to 4; can be repeated with a change in content up to 9 credits.
Problems and systems studies associated with honors programs representing undergraduate research. Selected advanced topics including new developments and techniques in industrial and systems engineering. To register, students must submit a petition for approval.
Credits: 3; Prerequisites: EIN 4354 and EIN 4360 with minimum grades of C; Co-requisite: ESI 4221C with minimum grade of C.
The first part of a two-course sequence in which multidisciplinary teams of engineering and business students partner with industry sponsors to design and build authentic products and processes on time and within budget. Working closely with industry liaison engineers and a faculty coach, students gain practical experience in teamwork and communication, problem-solving and engineering design, and develop leadership, management, and people skills.
Credits: 3; Prerequisites: 3EG or 4EG classification and EGS 4034 with a minimum grade of C.
The second part of a two-course sequence in which multidisciplinary teams of engineering and business students partner with industry sponsors to design and build authentic products and processes on time and within budget.
Credits: 1 to 3; can be repeated with a change in content up to 3 credits. Prerequisites: 4EG classification and EGS 4034 with a minimum grade of C.
One term of industrial employment, including extra work according to a pre-approved outline. Practical engineering work under industrial supervision as set forth in the Herbert Wertheim College of Engineering regulations. (S-U)
Focuses on analysis of data encountered in ISE applications, including systems reliability, demand forecasting and inventory control, simulation, and quality control. Specific engineering applications are discussed through case studies. Introduction and use of computational tools to implement various data analysis techniques are important components of this course.
Credits: 3; Prerequisite: ESI 3327C with a minimum grade of C.
Introduces deterministic optimization modeling, algorithms, and software to aid in the analysis and solution of decision-making problems.
Credits: 3; Prerequisites: MAC 2313 and MAS 3114 with minimum grades of C.
Theory and application of vector, matrix, and other numerical methods to systems problems. Simultaneous linear equations, characteristic values, quadratic forms, error analysis, use of series, curve fitting, nonlinear equations, discrete methods. The laboratory sessions will emphasize numerical solutions using common programming languages.
Credits: 3; Prerequisites: ESI 3215C with a minimum grade of C.
Factors affecting variation in product quality: use of control charts to evaluate and control manufacturing processes. Techniques for acceptance and reliability testing. Laboratory exercises illustrate the operation and control of manufacturing processes and hazard functions. Typical failure distributions, redundant systems, models of repair and maintenance.
Credits: 3; Prerequisites: ESI 3327C and ESI 3215C with minimum grades of C.
Introduces stochastic models and methodologies for analyzing and providing solutions to decision-making problems with uncertainties.
Credits: 3; Prerequisites: ESI 3312 and ESI 4313 with minimum grades of C.
Discusses advanced operations research topics on non-linear optimization, convex optimization, dynamic programming, and stochastic optimization. Studies large or complex problems from two different perspectives: the static approach and the dynamic approach.
Credits: 4; Prerequisites: COP2273 or COP2271 with a minimum grade of C; Corequisite: ESI 3312 with a minimum grade of C.
Applications of decision support systems in industrial and systems engineering; developing and implementing decision support systems arising in industrial and systems engineering using popular database management and spreadsheet software.
Credits: 3; Prerequisites: COP 2273 or COP 2271 and ESI 3215C with minimum grades of C.
Simulation methodology and languages (such as General Purpose Simulation System – GPSS). Design and analysis of simulation experiments as well as applications to solutions of industrial and service system problems.
Credits: 3; Prerequisites: COP 2273 or COP 2271 and ESI 3215C with minimum grades of C.
Provides a basic understanding of the skills necessary for managing and analyzing data. The concepts covered include exploratory data analysis, data manipulation, data cleaning, data wrangling, and machine learning models. A basic understanding of data management with SQL is also provided. All technical skills will be motivated by different examples involving data. Python is the programming language used.
Credits: 3; Prerequisite: ESI 4610 with a minimum grade of C.
Second course in the data analytics ISE sequence that focuses on how and why algorithms work using an application-oriented approach. Studies advanced analytical and learning models that enhance decision-making by converting data to information. Provides insight into how to choose the most effective tool for implementing a specific model.
Credits: 3; Prerequisites: ESI 3312 with a minimum grade of C and (ESI 4610 or COP 2273, both with a minimum grade of C).
Studies methods for designing and evaluating analytics systems for optimizing decision-making. Teaches technical and programming skills for implementation and feedback of an analytics pipeline from input data curation, processing, and validation, to prescribing outcomes.
Credits: 1 to 3; can be repeated with change in content up to 3 credits; Prerequisite: EGS 4034 with a minimum grade of C.
Practical engineering work under industrial supervision, as outlined in the Herbert Wertheim College of Engineering regulations. (S-U)
* Required course