2024-2025 Academic Catalog
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
The mission of the Grado Department of Industrial and Systems Engineering is to:
Industrial and systems engineering is one of the most diverse fields in engineering. ISE is concerned with the design, improvement, and installation of integrated work systems of people, materials, equipment and technology, processes, information, and capital. The industrial engineer is concerned with creating value and improving performance of integrated systems, whether that involves improving quality and productivity, reducing costs and non-value adding activities, improving customer satisfaction, or improving worker safety.
The applications for industrial engineering capabilities include industry, government, and service organizations. Graduates of the ISE program at Virginia Tech work in manufacturing facilities, distribution warehouses, hospitals, airlines, railroads, banks, amusement parks, the military, federal government, and management consulting firms. The boundaries of where ISEs make contributions are limitless.
The mission of the ISE Undergraduate Program is to prepare industrial and systems engineering students to create value for organizations, the profession, and society. We achieve this mission by recruiting, retaining, and educating high quality and diverse students and by creating a rigorous and collegial environment enabling students to learn industrial engineering methods and tools, built upon a foundation of mathematical, physical, and engineering sciences, and to apply them in any global organizational setting. Students are able to achieve academic and professional success through opportunities to participate in various educational experiences, to develop capabilities as future leaders, and to embark on a lifelong journey of professional development and learning.
The ISE faculty, with input from our external Advisory Board, employers, and students, have defined the following Program Educational Objectives (PEOs) and Student Outcomes for our Undergraduate Program. PEOs are statements that describe the expected accomplishments of ISE graduates within 3-5 years after graduation. Student Outcomes are statements that describe what students are expected to know and be able to do at the time of graduation.
Program Educational Objectives: Within 3-5 years of graduation, ISE alumni will have:
Student Learning Outcomes: At the time of graduation, ISE students will have:
The Industrial and Systems Engineering program at Virginia Tech is accredited by the Engineering Accreditation Commission of ABET, www.abet.org, under the commission’s General Criteria and the Program Criteria for Industrial and Similarly Named Engineering Programs .
The BSISE curriculum (ISE Undergraduate Program) encompasses coursework addressing the technical, organizational, human, and economic elements of work systems. Our aim is to provide graduates with the knowledge and capabilities to enable them to successfully pursue careers in industrial engineering or to continue on to graduate study.
ISE emphasizes instruction in fundamental engineering principles based on the physical sciences, engineering sciences, mathematics, and statistics. These principles are applied in practical design experiences throughout the undergraduate curriculum.
Coursework in the physical sciences and mathematics provides a solid background for basic engineering science courses, which in turn support courses in industrial engineering. Industrial engineering courses are focused in the areas of operations research, manufacturing systems, human factors and ergonomics, and management systems. In each of these areas, modern computing and software tools support analysis and design activities. Electives provide students with the opportunity to explore other areas of engineering, as well as cultural, societal and creative experiences, which makes for well-rounded, diverse, and globally-aware engineers.
Students gain valuable hands-on experience in multiple areas of the BSISE curriculum via state-of-the-art laboratory facilities. These include the Harris Manufacturing Processes Laboratories (conventional and numerically-controlled machine tools, robotics and automation equipment, and welding and foundry facilities), the Learning Factory (Industry 4.0 sandbox laboratory for undergraduates), and the Human Factors Work Measurement and Methods Engineering Laboratory (equipment for in-class exercises and experiments in work measurement, motion economy and time study, psychophysics, human audition and vision, and work station design).
The capstone experience in the ISE Undergraduate Program is ISE 4005-ISE 4006 Project Management & System Design (also referred to as "Senior Design"). The two-course sequence involves students working in project teams with external company sponsors to solve real-world problems. This provides ISE students with engineering project experience that develops not only their capabilities in applying ISE tools and techniques, but technical and professional skills such as teamwork, communication, project management, and life-long learning skills as well. Student project teams present their findings at the annual Senior Design Symposium, which is attended by company sponsors and the ISE Advisory Board.
Many ISE students participate in Undergraduate Research to help satisfy elective requirements in the curriculum. The opportunity to work more closely with ISE faculty members, in some cases on a one-on-one basis, can provide more in-depth development of particular ISE capabilities and a more-enriching educational experience.
The ISE program also provides students with the opportunity to pursue minors, such as a Business Minor, Green Engineering Minor, or Statistics Minor. Specific information about minors available to ISE students can be found on the ISE website. Students and employers alike are seeing the benefits of these minors for adding value to the ISE major.
The ISE department participates in the Cooperative Education & Internship Program, in which qualified students may alternate semesters of study with semesters of professional co-op employment or internships. Students are encouraged to pursue these experiences before they graduate to make them more competitive in the work force. Students are also encouraged to participate in career fairs and job interviews on and off campus.
The ISE department also provides students with many significant scholarship opportunities at the undergraduate and graduate levels to encourage and acknowledge high academic performance and achievements. The department also maintains bilateral student exchange agreements with international universities, where students can take ISE courses, which will transfer back to their BSISE. Students may also select other universities at which to perform a study abroad semester.
The ISE department also provides students with many significant scholarship opportunities at the undergraduate and graduate levels to encourage and acknowledge high academic performance and achievements. The ISE department also maintains bilateral student exchange agreements with international universities, where students can take ISE courses which will transfer back to their BSISE. Students may also select other universities at which to perform a study abroad semester.
Students are strongly encouraged to meet with one of the ISE Academic Advisors to discuss the BSISE curriculum.
Head: E.M. Van Aken
Associate Head: J.P. Shewchuk
Assistant Head and Graduate Program Director: M.A. Nussbaum
Undergraduate Program Director: N. Cherbaka
Charles O. Gordon Professor: G.D. Taylor, Jr.
Hal G. Prillaman Professor: M.A. Nussbaum
Paul T. Norton Professor: S.C. Sarin
Ralph H. Bogle Professor: Z. Kong
John Lawrence Professor: K.P. Triantis
Professors: P. A. Beling, J.L. Gabbard, M. Jeon, B.M. Kleiner, Z. Kong, M.L. Madigan, M.A. Nussbaum, S.C. Sarin, G.D. Taylor Jr., K.P. Triantis, K.L. Tsui, and E.M. Van Aken
Associate Professors: M. Bansal, X. Chen, D.E. Dickerson, K.P. Ellis, N. Ghaffarzadegan, R. Jin, B. Johnson, S.G. Klauer, A. L’Afflitto, N. Lau, P.K. Rao, J.P. Shewchuk, and E.B. Toy
Assistant Professors: R. Hildebrand, N. Hosseinichimeh, R. Kannan, S. Khodadadian, S. Lim, R.N.C. Patrick, T.G. Topcu, S. Tunc, and H. Zhong
Visiting Assistant Professor: B. Song
Collegiate Full Professor: N. Cherbaka
Collegiate Assistant Professors: K. Carper, J. Godfrey, W.P.V. Nguyen, and L. Savage
Research Associate Professor: S. Kim. T. Sun
Research Assistant Professor: K. Lee
Associate Professor of Practice: M.R. Earnest
Faculty Affiliates: P. Agee, T. Cody, X. Deng, M. Fowler, Y. Hong, S. Hotle, J. Moreland, M. Perez, N. Roofigari-Esfahan, S. Trent
Adjunct Faculty: M. Deegan, J. Geraghty, G. Keller, M. Muscatello, W. Vaneman, and P. Wach
Professors Emeritus: M.P. Deisenroth, W.J. Fabrycky, K.H.E. Kroemer, H.A. Kurstedt, H.D. Sherali, and H.L. Snyder
Associate Professors Emeritus: P. Ghare, P.T. Kemmerling P. Koelling, J.A. Nachlas, and R.E. Taylor
Academic Advisors: J. Kerstiens and P. Van Curen
Introduction to the Industrial and Systems Engineering profession through exposure to problems, principles, and practice. Systems thinking, critical thinking, and contemporary issues in industrial and systems engineering. Introduction to the ISE Department, focusing on faculty and research areas. Importance of ethics and professionalism. Academic planning for the BSISE degree.
Concepts and techniques of analysis for evaluating the value of products/services, projects, and systems in relation to their cost. Economic and cost concepts, calculating economic equivalence, comparison of alternatives, purchase versus lease decisions, financial risk evaluation, cash flow sensitivity analysis, and after-tax analysis.
Introduction to the mathematical foundations of probability theory for industrial engineers. Understanding of probability as a model for real phenomena, with applications of probability in an industrial engineering context. Review of set theory, counting (permutations and combinations), definition of probability axioms, sample spaces, random variables, independence, probability distribution functions, probability mass or density functions, expectations, moment-generating functions, joint and conditional random vectors and distributions, and distributions of functions of random variables, central limit theorem.
Investigation of data modeling, storage, acquisition, and utilization in industrial and systems engineering. Development of effective spreadsheet applications. Design and implementation of relational databases via entity-relationship modeling, relational schema, normalization, and queries. Structured query language (SQL) fundamentals and SQL relational databases. Overview of non-relational databases, Big Data, and Data Analytics. All topics covered within the context of typical industrial and systems engineering problems.
Overview of the breadth of careers and professional opportunities in the field of industrial and systems engineering. Technical approaches and solutions, emerging trends, career progression, and leadership aspects of industrial and systems engineering practice. Representation of practice across all areas of industrial and systems engineering as well as across a range of industries.
Laboratory exercises and experimentation in manufacturing processes. Emphasis on using production machines and equipment to make products using multiple manufacturing processes, coupled with inspection per engineering drawings. Processes include assembly, casting, machining, forming, welding, and non-traditional machining, performed manually and/or via computer programming. Also covers basic shop floor operation and documents used for monitoring and controlling part production.
Deterministic operations research modeling concepts. Linear programming, integer programming, and non-linear programming modeling, assumptions, algorithms, modeling languages, and modern optimization software. Graphical solution, Simplex tableau method and its graphical interpretation. Branch and bound and branch and cut methods. Duality, sensitivity analysis, and Karush-Kuhn-Tucker (KKT) Optimality Conditions with economic interpretation. Network models (formulations and algorithms) including transportation problems, assignment problems, shortest path problems, maximum flow problems, minimum cost network flow problems, and minimal spanning tree problems.
A systems approach to designing, building, verifying, deploying, operating, and sustaining complex engineered systems. Emergent properties of systems, system lifecycle, and systems engineering as a process driven discipline. Technical management of processes regarding acquisition, contracting, and development. Problem formulation and elicitation of requirements. Creation of system elements: resource components, functions, internal and external interfaces. Introduction to decision analysis and risk management, model-based systems engineering and system architectures.
Introduction to basic accounting concepts and operating characteristics of accounting systems. Principles of financial, cost and activity-based accounting, design of accounting systems, techniques of analysis, and cost control. Emphasis on interpretation of accounting for decision-analysis, including the benefits of limitations of accounting information.
Fundamentals of effective technical writing. Structure, presentation, and utility of common engineering documents: laboratory reports, technical reports, proposals, progress reports, and project reports. Practice in writing common engineering documents, both individually and collaboratively. Strategies and practice for effective oral technical presentations, both individually and group-based. Ethical and legal considerations in technical writing and oral technical presentations. All topics covered within the context of typical engineering problems and practice.
Survey of manufacturing processes including casting, forming, machining, welding, joining, and nontraditional processes such as electrical-discharge machining. Basic manufacturing materials and their properties, structure of metals, metal deformation and heat treatment. Mathematical modeling of common manufacturing processes; process planning and the effect of plans on cost; impact of product design on manufacturability and assemblability. Recent trends in manufacturing, sustainable manufacturing. Also includes topics in inspection and testing, computer-aided manufacturing, and numerical control.
Theory, concepts, and methods for designing and analyzing facilities and material flow in manufacturing, storage, and distribution environments. Topic areas include material handling systems, facility layout, facility location, warehousing, distribution, logistics, and transportation. C- or better in ISE 2014, 2404, and 3414.
This course introduces probability models used to investigate the behavior and performance of manufacturing and service systems under conditions of uncertainty. Major topics include probability, conditioning, elementary counting processes, and Markov chains and Markov processes. Emphasis is on the use of these tools to model queues, inventories, process behavior, and equipment reliability. C- or better required in STAT 4105, MATH 2224 or 2204, MATH 2214 or 2214H, and ISE 2004.
Analysis and design of work systems through static and dynamic simulation. Topics include an introduction to systems analysis and modeling, simulation optimization, model development and testing, and problem analysis through simulation. C- or better required in ISE 3414 and STAT 4105.
Advanced concepts in deterministic operations research, including theory of complexity, integer programming, advanced linear programming techniques, nonlinear programming, dynamic programming. Covers modeling languages and optimization software for integer programming and nonlinear programming problems. Grade of C- or better required in ISE 2004, 2404 and MATH 2204 or 2224.
Investigation of human factors, ergonomics, and work measurement engineering, with emphasis on a systems approach toward workplace and machine design. Discussion of basic human factors research, discipline-specific ethics, design/evaluation methods for industrial and artificial intelligence (AI) systems including human machine interactions, human information processing, visual and auditory processes, design of display and control, effects of environmental stressors on humans, visualization and sonification of large datasets, human factors role in the design of machine learning and AI applications.
Introduction to ergonomics and work measurement with an emphasis on people at work. Discussion of methods for work measurement, ergonomic assessment, and evaluation, with major topics including productivity and performance, manual materials handling, work-related musculoskeletal disorders, safety, training and legal issues. C- or better required in ISE 3614.
A theory of cooperative behavior in formal organizations, including the structure and elements of formal organizations. The executive process and the nature of executive responsibility also are examined.
Capstone design experience for ISE majors. 4005: Structured systems engineering and project management methods and tools to plan, manage, and execute technical industrial and systems engineering projects. Students work in teams to apply industrial and systems engineering and project management tools to define and analyze a real-world problem and communicate results effectively. 4006: Designing, implementing, and evaluating work system solutions, all via students working in teams. Communication of solutions to various project stakeholders.
Capstone design experience for ISE majors. 4005: Structured systems engineering and project management methods and tools to plan, manage, and execute technical industrial and systems engineering projects. Students work in teams to apply industrial and systems engineering and project management tools to define and analyze a real-world problem and communicate results effectively. 4006: Designing, implementing, and evaluating work system solutions, all via students working in teams. Communication of solutions to various project stakeholders.
Introduction to a systems approach for the design and improvement of management systems used in organizations. Discussion of organizational improvement approaches to improve the design and operation of management systems used in managerial decision-making. Analysis of success and failure of organizational improvement projects. Discussion of performance measurement systems, evaluation, and assessment tools.
Systems approach to management, domains of responsibility, structured and synergistic management tools, management system model, contextual frameworks, information portrayal, automation objectives model, evaluation, shared information processing, information modeling. A management process for definition, measurement, evaluation and control, the organization as an information processor, corporate culture, scoping agreements, schemas and management elements, structured design.
Planning and control of operations in both manufacturing and service industries. Management and utilization of resources to support cost effective products and services. Principles, models, and techniques used for production planning and inventory control.
Overview of Lean Manufacturing principles, theory, methods, and techniques in modern manufacturing enterprises. Lean philosophy and basic concepts, master production scheduling and production smoothing, assembly line sequencing, setup time reduction, U-shaped line balancing/operation, machine arrangement, kanban, autonomation, and value stream mapping. Investigation and discussion of lean manufacturing case studies. C- or better required in ISE 4204.
Survey of various technologies employed in industrial automation, with emphasis on industrial applications of robotics, machine vision and learning, and programmable controllers. Introductory robot motion modeling, investigation into problems in Computer- Aided Design (CAD)/Computer-Aided Manufacturing (CAM) integration. Examination of components commonly employed in automation systems, their aggregation, and related production process design.
Industrial management topics of current interest explored from a global perspective. Current domestic and international challenges resulting from a global marketplace and the proliferation of information and technology. Industrial management and organizational performance, total quality management, business process re-engineering, leadership, organizational change, role of communication and information, and ethics. Examination and comparison across international boundaries.
Application of statistical methods and probability models to the monitoring and control of product quality. Techniques for acceptance sampling by variables and attributes. Shewhart control charts for both mean and range of quality characteristics. Design of experiments and analysis of variance for effective data-generation processes. Motivation behind, and theoretical development and application of, both control charts and design of experiments. Design of effective quality control procedures.
Implementation of statistical quality control techniques in an industrial setting. Development and analysis of cost models for use in the design of optimal quality control plans. Also included are new techniques, advanced quality control models, and an examination of the role of industrial statistics in the overall product quality assurance function. C- or better required in ISE 4404.
Introduction to the key issues in the integrated support of a product or process. Synthesis of topics from earlier studies to provide a cohesive approach to their applications. Logistics engineering provides a survey of product support issues and methods of resolving them within the context of the overall production activity. C- or better required in ISE 3414.
Mathematical models, algorithms, and tools to support the design/redesign and management of supply chain systems. Resiliency, reliability, efficiency, and effectiveness of supply chains; collaboration and coordination among the different decision-makers in supply chains; impact of new developments on supply chain engineering, including the growth of the internet and e-commerce, the need to build suitable and environmentally-friendly supply chains. Mathematical modeling and system-wide optimization of the entire supply chain system under certainty.
Physical ergonomics assessment methods, including cardiorespiratory testing, metabolic energy expenditure and balance, strength, anthropometry, endurance and fatigue, electromyography, biomechanics, thermal stress.
Introduction to human factors principles applied to surface transportation for industrial engineers. Understanding of human factors research methods, with applications for safety to the transportation system. Haddon’s Matrix, human factors research methods, crash countermeasures, public policy implications, and automated driving systems.
Introduction to the fields of risk assessment, risk and hazard control, safety management, process safety, and system safety engineering through exposure to problems, principles, and practice. Integrated systems approach to problem solving. Industrial accident and disaster case study analysis and review of contemporary issues. Review of risk analysis and control techniques and overview of global regulations and guidelines for process, industrial, and occupational safety. C- or better required in ISE 3614.
Introduction to the foundations of the field of Industrial Hygiene, that discipline devoted to the anticipation, recognition, measurement, evaluation, and control of occupational health hazards. Includes biological (e.g. microbial agents, allergens), chemical (e.g. solvents, carcinogens, dusts), and physical (e.g. radiation , temperature) hazards. Overview of control of health hazards, such as personal protective equipment, administrative controls, and engineering controls. Will involve lecture and participatory case-study activities. Will provide ample opportunity for hands-on use of monitoring equipment, protective equipment and controls testing devices.
Computer-aided approach to analyze and make better decisions in complex industrial systems. Systems thinking and causal loop modeling of complexity over time. Interconnectivity of industrial systems, production, and service. Stock-flow diagrams. Systems modeling of product development and market adoption. Simulation of dynamic problems arising in complex systems. Systems modeling and simulation-based decision analysis to improve performance in service and manufacturing.
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