Major dimensions of systems engineering will be covered and demonstrated through case studies: (1) The history, philosophy, art, and science upon which systems engineering is grounded; including system thinking and guiding principles and steps in the `systems engineering approach¿ to problem solving; and (2) The basic tools of systems engineering analysis, including; goal definition and system representation, requirements analysis, system assessment and evaluation, mathematical modeling, and decision analysis.

This course provides students with the background necessary to model, store, manipulate, and exchange information to support decision making. It covers Unified Modeling Language (UML), SQL, and XML; the development of semantic models for describing data and their relationships; effective use of SQL; web-based technologies for disseminating information; and application of these technologies through web-enabled database systems. Corequisite: CS 2100 or SYS 3501.

This course examines the lifecycle of engineered systems (ES) and the public policies developed to regulate them. It covers risks, costs, benefits, and equity as common evaluation criteria for ES and their regulatory policies. It uses case studies and basic tools of decision analysis to critically evaluate the tradeoffs involved in developing and regulating ES through public policy. Pre-reqs: (STS 1500 or ENGR 1020 or ENGR 2595 - Engineering Foundations II) and (APMA 1110 or MATH 1320), and (CHEM 1410 or CHEM 1810), and (PHYS 1425 or PHYS 1420 or PHYS 1710).

Focuses on the evaluation of candidate system designs and design performance measures. Includes identification of system goals; requirements and performance measures; design of experiments for performance evaluation; techniques of decision analysis for trade-studies; presentation of system evaluation and analysis results. Illustrates the concepts and processes of systems evaluations using case studies. Pre-reqs: APMA 3120, SYS 2001, & SYS 3021.

This is an introductory course on modeling probabilistic systems. The emphasis will be on model formulation and probabilistic analysis. Topics to be covered include general stochastic processes, discrete and continuous time Markov chains, the Poisson Process, Non-Stationary Poisson Processes, Markov Decision Processes, Queueing Theory, and other selected topics. Prerequisite: APMA 3100 or MATH 3100.

A first course in the theory & practice of discrete-event simulation. Monte Carlo methods, generating random numbers & variates, spreadsheet add-ins & applications, sampling distributions & confidence intervals, input analysis & distribution fitting. Discrete-event dynamic systems, modeling, simulation logic & data structures, output analysis, model verification & validation, comparing alternative systems, simulation optimization, case studies. Prerequisite: APMA 3100, and APMA 3120

This course is an introduction to the theory, methods, and applications of risk analysis and systems engineering. The topics include research and development priorities, risk-cost-benefit analysis, emergency management, human health and safety, environmental risk, extreme events, infrastructure resilience, system interdependencies, and enterprise systems. Corequisites: a course in probability (APMA 3100 or APMA 3110 or Math 3100).

A design project extending throughout the fall and spring semesters. Involves the study of a real-world, open-ended situation, including problem formulation, data collection, analysis and interpretation, model building and analysis, and generation of solutions. Students work on the same project with the same team in SYS 4053 and 4054 in subsequent semesters.  Pre-requisite:  SYS 4053

Detailed study of a selected topic determined by the current interest of faculty and students. Offered as required. Prerequisite: As specified for each offering.

Detailed study of a selected topic determined by the current interest of faculty and students. Prerequisite: As specified for each offering.