Undergraduate Courses
More information about SIE courses, including fees and grading bases, can be found in the UA Catalog, under Course Descriptions.
Note: Upper division courses, SIE 3xx and SIE 4xx, require Advanced Standing for registration. Students must contact the department to apply for advanced standing.
Required Minors and Technical Electives
In addition to core courses and prerequisites, systems engineering majors and engineering management majors are required to complete an engineering or thematic minor, which consists of 18 unique units primarily composed of technical electives. Industrial engineering majors do not have a minor requirement, but must complete 12 units of technical electives from upper division coursework.
- Minor Course Guide for Engineering Management (PDF)
- Minor Course Guide for Systems Engineering (PDF)
- Technical Elective Guide for Industrial Engineering (PDF)
For information about the degrees offered by the department, see the Undergraduate Degrees page.
SIE 250: Introduction to Systems and Industrial Engineering
System modeling the elementary constructs and principles of system models including discrete-time, discrete-state system theory; finite state machines; modeling components, coupling, modes, and homomorphisms system design; requirements, life-cycle, performance measures and cost measures; tradeoffs; alternative design concepts; testing plan; and documentation. Applications and case studies from engineering.
SIE 265: Engineering Management I
Fundamentals of economic analysis and the time value of money for engineers. Construction of financial models in EXCEL including Income, Cash Flow, and Balance Sheet. Estimation of required capital and project acceptance criteria. Identical to ENGR 265.
SIE 270: Mathematical Foundations of Systems and Industrial Engineering
Basics of data structures, transformations, computer methods, their implementation in MATLAB and their applications in solving engineering problems.
SIE 277: Object-Oriented Modeling and Design
Modeling and design of complex systems using all views of the Unified Modeling Language (UML). Most effort will be in the problem domain (defining the problem). Some effort will be in the solution domain (producing hardware or software).
SIE 295S: Systems Engineering Colloquium
A colloquium designed to help students understand what SIE's do. Students will interact with speakers and take tours to local companies. The course helps students select course options within the SIE programs and helps focus on possible SIE applications areas.
SIE 305: Introduction to Engineering Probability and Statistics
Axioms of probability, discrete and continuous distributions, sampling distributions. Engineering applications of statistical estimation, hypothesis testing, confidence intervals.
SIE 321: Probabilistic Models in Operations Research
Probability, Markov chains, Poisson processes, queuing models, reliability models.
SIE 330R: Engineering Experiment Design
Design and analysis of observational and factorial experiments employing numerical and graphical methods. Topics include control charts, probability plots, multiple regression analysis, confidence and prediction intervals and significance tests.
SIE 340: Deterministic Operations Research
Linear programming models, solution techniques, sensitivity analysis and duality.
SIE 367: Engineering Management II
Strategic, tactical and operational planning; innovation and technological cycles; the elements of entrepreneurship, and human relations topics for technical managers.
SIE 370: Embedded Computer Systems
Boolean algebra, combinational and sequential logic circuits, finite state machines, simple computer architecture, assembly language programming, and real-time computer control. The computer is used as an example of systems engineering design; it is analyzed as a system, not as a collection of components.Typical structure: 3 hours lecture, 3 hours laboratory.
SIE 377: Software for Engineers
Programming in C. Modular program design and verification, pointers and structures, data structures and algorithms including: lists, trees, graphs, searching and sorting.
SIE 383: Integrated Manufacturing Systems
Introduction to the integrated manufacturing enterprise and automation. Topics include computer-aided design, process planning, computer numerical control machining, machine vision, application of robots and automation. Typical structure: 2 hours lecture, 2 hours laboratory.
SIE 406: Quality Engineering
Quality, improvement and control methods with applications in design, development, manufacturing, delivery and service. Topics include modern quality management philosophies, engineering/statistical methods (including process control, control charts, process capability studies, loss functions, experimentation for improvement) and TQM topics (customer driven quality, teaming, Malcolm Baldrige and ISO 9000).May be convened with SIE 506.
SIE 408: Reliability Engineering
This is a three-credit course configured for well-qualified seniors, graduate students, and engineering professionals and practitioners. It is concerned with determining the probability that a component or system, whether simple or complex, will function as intended. The scope of this course includes: (1) Root cause analysis of critical failures, (2) reliability models of components and systems, (3) development of statistical methods for estimating the reliability of a product, (4) use of software tools to perform model development and analysis, and (5) methodologies to influence system designs.
SIE 410A: Human Factors and Ergonomics in Design
Consideration of human characteristics in the requirements for design of systems, organizations, facilities and products to enable human-centered design which considers human abilities, limitations and acceptance.
SIE 411: Human-Machine Interaction
Basic concepts, methods, principles and skills in designing and evaluating various human-machine interfaces. Machine here is generally defined as any physical systems that can be operated by human operators. By taking this course, students can not only use several effective methods to design and prototype human-machine interfaces based on the needs and characteristics of users (e.g., PPT method, Visual Basic Applications user interface programming skills; simple Web design techniques etc.), but also apply both quantitative and qualitative evaluation methods to optimize the human performance, mental workload and aesthetics. To broaden students’ view in HMI, relative new topics in HMI are also introduced in this course.
SIE 414: Law for Engineers and Scientists
Topics covered in this course include patents, trade secrets, trademarks, copyrights, product liability contracts, business entities, employment relations and other legal matters important to engineers and scientists.
SIE 415: Technical Sales and Marketing
Principles of the engineering sales process in technology-oriented enterprises; selling strategy, needs analysis, proposals, technical communications, electronic media, time management and ethics; practical application of concepts through study of real-world examples.
SIE 422: Engineering Decision-Making Under Uncertainty
Application of principles of probability and statistics to the design and control of engineering systems in a random or uncertain environment. Emphasis is placed on Bayesian decision analysis.May be convened with SIE 522.
SIE 430: Engineering Statistics
Statistical methodology of estimation, testing hypotheses, goodness-of-fit, nonparametric methods and decision theory as it relates to engineering practice. Significant emphasis on the underlying statistical modeling and assumptions. May be convened with SIE 530.
SIE 431: Simulation Modeling and Analysis
Discrete event simulation, model development, statistical design and analysis of simulation experiments, variance reduction, random variate generation, Monte Carlo simulation. May be convened with SIE 531.
SIE 433: Fundamentals of Data Science for Engineers
This course will provide senior undergraduate and graduate students from diverse engineering disciplines with fundamental concepts, principles and tools to extract and generalize knowledge from data. Students will acquire an integrated set of skills spanning data processing, statistics and machine learning, along with a good understanding of the synthesis of these skills and their applications to solving problem. The course is composed of a systematic introduction of the fundamental topics of data science study, including: 1) principles of data processing and representation, 2) theoretical basis and advances in data science, 3) modeling and algorithms, and 4) evaluation mechanisms. The emphasis in the treatment of these topics will be given to the breadth, rather than the depth. Real-world engineering problems and data will be used as examples to illustrate and demonstrate the advantages and disadvantages of different algorithms and compare their effectiveness as well as efficiency, and help students to understand and identify the circumstances under which the algorithms are most appropriate.
SIE 440: Survey of Optimization Methods
Survey of methods including network flows, integer programming, nonlinear programming, and dynamic programming. Model development and solution algorithms are covered. May be convened with SIE 540.
SIE 454A: The Systems Engineering Process
Process and tools for systems engineering of large-scale, complex systems: requirements, performance measures, concept exploration, multi-criteria tradeoff studies, life cycle models, system modeling, etc. May be convened with SIE 554A.
SIE 455: Sensor Systems Engineering
The primary purpose of this course is to provide students with a system-level understanding of sensor development. The student will see the development of remote sensing techniques beginning with high level requirements through concept of operations, architecture development, subsystem modeling and culminating in integration, validation and verification. The student will be exposed to key design parameters for radar and Electro Optical sensing systems that drive both system cost and performance. Advanced multi-sensor systems and adaptive signal processing will also be discussed.
SIE 457: Project Management
Foundations, principles, methods and tools for effective design and management of projects in technology-based organizations. This course focuses on the scope, time, cost, performance and quality concerns of engineering projects characterized by risk and uncertainty. Initiating, planning, executing, monitoring, controlling and closing process are addressed. Students design and complete a project from concept through completion. Project Management software is utilized.
SIE 458: Model-Based Systems Engineering
An introduction to model-based systems engineering (MBSE), which is the formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. The course emphasizes practical use of the Systems Modeling Language (SysML) and MBSE methods.
SIE 462: Production Systems Analysis
Production systems, quantitative methods for forecasting, aggregate planning, inventory control, materials requirement planning, production scheduling, manpower planning and facility design.
SIE 464: Cost Estimation
Focuses on principles of cost estimation and measurement systems with specific emphasis on parametric models. Approaches from the fields of hardware, software and systems engineering are applied to a variety of contexts (risk assessment, judgment and decision-making, performance measurement, process improvement, adoption of new tools in organizations, etc.). Material is divided into five major sections: cost estimation fundamentals, parametric model development and calibration, advanced engineering economic principles, measurement systems and policy issues.
SIE 465: Supply Chain Management
Fundamentals of Supply Chain Management including inventory/logistics planning and management, warehouse operations, procurement, sourcing, contracts and collaboration. May be convened with SIE 565.
SIE 466: Life Cycle Analysis for Sustainable Design and Engineering
This course will provide senior undergraduate and graduate students the conceptual, methodological, and scientific bases to quantify and improve the impact of engineering decisions on the environment, with a focus on applying life cycle analysis (LCA). The course will foster students to assess the environmental sustainability early on in their research to help design and develop more sustainable materials, products, and processes including manufacturing, logistics, and supply chain. Main topics covered include concept of life cycle thinking, computational structure of LCA, process based LCA, economic input-output LCA, LCA software tools and databases, case studies, recent development, and advanced topics in LCA. The students will be able to approach problems with life cycle perspectives, conduct LCA according to the ISO 14040 standards, and understand the strengths and weaknesses of LCA studies.
SIE 471: Systems Cyber Security Engineering
The purpose of this course is to introduce selected topics, issues, problems and techniques in the area of System Cyber Security Engineering (SCSE), early in the development of a large system. Students will explore various techniques for eliminating security vulnerabilities, defining security specifications / plans, and incorporating countermeasures in order to achieve overall system assurance. SCSE is an element of system engineering that applies scientific and engineering principles to identify, evaluate, and contain or eliminate system vulnerabilities to known or postulated security threats in the operational environment.
SIE 472: Information Security and Research (INSuRE)
This course engages students in diverse and varied national cybersecurity/information systems security problems, under an existing and very successful umbrella program called "INSuRE," that enables a collaboration across several universities, Cyber professionals and cross-disciplined Cyber related technologies. Led by Purdue University, and made possible by a grant from the NSA and NSF, INSuRE has fielded a multi-institutional cybersecurity research course in which small groups of undergraduate and graduate students work to solve unclassified problems proposed by NSA, other US government agencies, and/or private organizations and laboratories. Students will learn how to apply research techniques, think clearly about these issues, formulate and analyze potential solutions, and communicate their results with sponsors and other participating universities.
Working in small groups under the mentorship of technical experts from government and industry, each student will formulate, carry out, and present original research on current cybersecurity/information assurance problems of interest to the nation. This course will be run in a synchronized distance fashion, coordinating activities with other INSuRE technical clients and sponsors, along with partnering universities which are all National Centers of Academic Excellence in Cyber Defense Research (CAE-R), i.e., Purdue University, Carnegie Mellon University, University of California Davis and several others.
SIE 473: Engineering of Trustworthy Secure Systems
The purpose of this course is to explore widely accepted security frameworks, industry standards, and techniques employed in engineering trustworthy secure and resilient systems. We will study and explore several National Institute of Standard and Technology (NIST) frameworks such as the Cyber Security Framework (CSF), the Risk Management Framework (RMF), and other standards. These widely adopted standards have been developed to ensure that the appropriate security principles, concepts, methods, and practices are applied during the system development life cycle (SDLC) to achieve stakeholder objectives for the protection of assets—across all forms of adversity characterized as disruptions, hazards, and threats. We will also explore case studies within the Department of Homeland Security’s (DHS) 16 Critical Infrastructure elements (shown in the figure below), to understand how government and private sector participants within the critical infrastructure community work together to manage risks and achieve security and resilient outcomes. Cyber resiliency is the ability to anticipate, withstand, recover from, and adapt to adverse conditions, stresses, attacks, or compromises on systems that use or are enabled by cyber resources regardless of the source.
SIE 477: Introduction to Biomedical Informatics
Driven by efforts to improve human health and healthcare systems, this course will cover relevant topics at the intersection of people, information, and technology. Specifically, we will survey the field of biomedical informatics that studies the effective uses of biomedical data, information, and knowledge from molecules and cellular processes to individuals and populations, for scientific inquiry, problem-solving, and decision-making. We will explore foundations and methods from both biomedical and computing perspectives, including hands-on experiences with systems, tools and technologies in the healthcare system.
SIE 482: Lean Operations and Manufacturing Systems
Survey of lean and variability reduction principles as applied to manufacturing and non-manufacturing environments.
SIE 483: Computer-Integrated Manufacturing (CIM) Systems
Modern manufacturing systems with emphasis on information requirements and data management. Includes CAD, CAM, CAPP, real-time scheduling, networking, and system justification. May be convened with SIE 583.
SIE 492: Directed Research
Directed research is one of the best ways for an undergraduate to engage in interesting research and get individual guidance from faculty. Please download the proposal form and contact the faculty member with whom you have interest in working. (1-3 units)
SIE 493: Internship
Specialized work on an individual basis, consisting of training and practice in actual service in a technical, business, or governmental establishment. (1-3 units)
SIE 496: Information Analytics in Engineering
This course is designed to provide a flexible topics course across several domains in the field of Systems Engineering, Industrial Engineering, and Engineering Management. Students will develop and exchange scholarly information in a small group setting. Selected advanced topics in Systems and Industrial Engineering and Operations Research, such as 1) optimization, 2) stochastic systems, 3) systems engineering and design, 4) human cognition systems, and 5) informatics. Course may be repeated for a maximum of 9 units or 3 completions.
SIE 496: Information Analytics in Engineering
This course is designed to provide a flexible topics course across several domains in the field of Systems Engineering, Industrial Engineering, and Engineering Management. Students will develop and exchange scholarly information in a small group setting. Selected advanced topics in Systems and Industrial Engineering and Operations Research, such as 1) optimization, 2) stochastic systems, 3) systems engineering and design, 4) human cognition systems, and 5) informatics. Course may be repeated for a maximum of 9 units or 3 completions.
SIE 498A: Senior Design Projects II
Teams of students will use material taught in the SIE curriculum to address a customer's needs and help a real-world client design or improve a system. Students will use a system design process, discover system requirements, identify project and technical risks, and develop a project plan and schedule. Students will communicate orally and in writing. A series of design reviews will monitor project goals, schedule, risk and progress. 498A should be taken in the student's second-to-last semester. (2-3 units)
SIE 498B: Systems Engineering Senior Design
Teams of students will use material taught in the SIE curriculum to address a customer's needs and help a real-world client design or improve a system. Students will use a system design process, discover system requirements, identify project and technical risks, and develop a project plan and schedule. Students will communicate orally and in writing. A series of design reviews will monitor project goals, schedule, risk and progress. Continuation of SIE-498A.