Department Head: John T. Wen
Director, Doctoral Program: David Mendonca
Director, Master’s Program: William J. Foley
Director, Undergraduate Program: Charles J. Malmborg
Department Home Page: http://www.ise.rpi.edu
The Department of Industrial and Systems Engineering offers degree programs at the bachelor’s, master’s, and doctoral levels including the bachelor’s and master’s degree in Industrial and Management Engineering, and the doctoral degree in Decision Sciences and Engineering Systems. The common theme throughout the department’s academic programs is the use of mathematical, statistical, and computational/simulation models to better understand, predict, and optimize complex engineering, managerial, operational, and physical systems.
Research Innovations and Initiatives
The department’s research is focused on core disciplinary strengths in Industrial and Systems Engineering (ISE). ISE involves the application of mathematical, computational, statistical, and information science methods to model, analyze, and solve complex decision problems in engineering, business, and social systems. ISE employs methods of mathematical programming, queuing theory, computational optimization, decision analysis, applied statistics, database systems, soft computing, and discrete event simulation for solving problems related to the design, planning, and operation of complex systems where intelligent coordination is necessary to achieve optimal performance. It is distinctive from management and economics in the use of an engineering approach to design and analyze enterprise processes to optimize performance. It is distinct from computer science in its focus on the design of data and knowledge systems as the organizational nerve center where operations and enterprise systems are integrated.
The department’s faculty research aligns directly with these core strengths to exploit dynamically evolving opportunities of high relevance in such areas as Adaptive Supply Chains, Manufacturing Systems, Social and Cognitive Networks, Homeland Security, Service Systems Engineering, Energy and Environmental Systems, Healthcare Systems and Robotics.
Embrechts, M.J.—Ph.D. (Virginia Polytechnic Institute); application of neural networks and fuzzy logic for manufacturing and process control; image recognition and classification with the aid of neural networks; neural networks, fractals, chaos, and wavelets for time-series analysis; data mining and computational intelligence.
Hsu, C.—Ph.D. (Ohio State University); electronic commerce, metadatabase and information systems, enterprise integration and modeling, Internet enterprises planning, computerized manufacturing, information visualization, economic evaluation of cyberspace-augmented enterprises.
Malmborg, C.J.—Ph.D. (Georgia Institute of Technology); modeling and analysis of problems in facility design, materials handling, material flow, storage systems, simulation-based optimization methods, manufacturing systems, decision analysis.
Wallace, W.A.—Ph.D. (Rensselaer Polytechnic Institute); decision support systems, environmental management modeling process, disaster management.
Wen, J.T.—Ph.D. (Rensselaer Polytechnic Institute); control systems, robotics, motion systems, control applications.
Chan, W.K.—Ph.D. (University of California at Berkeley); discrete event simulation, design and analysis of manufacturing and service systems, mathematical statistics, queuing theory.
Mendonca, D.—Ph.D. (Rensselaer Polytechnic Institute) ; decision analysis, decision making in emergent environments, group decision making, human performance, infrastructure systems.
Ryan, J.—Ph.D. (Northwestern University); Bayesian methods for decision support systems, stochastic optimization methods for logistical systems, stochastic models for inventory control and supply chain management, analysis of make-to-stock production/inventory systems, service parts logistics, decision models for large-scale condition monitoring.
Sharkey, T.—Ph.D. (University of Florida); mathematical programming, network algorithms, combinatorial and computational optimization, supply chain logistics, demand allocation based supply chain optimization models, nonlinear network design problems.
Xie, W.—Ph.D. (Northwestern University); applied statistics, operations research and data analytics.
Grabowski, M.—Ph.D. (Rensselaer Polytechnic Institute); management information systems, knowledge-based systems, human and organizational error in large-scale systems, impact of information technology on systems and organizations.
Aboul-Seoud, M.—Ph.D. (University of Louisville); reliability engineering, quality control, operations research.
Foley, W.J.—P.E., Ph.D. (Rensselaer Polytechnic Institute); engineering design, computer simulation modeling, health applications of operations research, health case policy analysis.
Berg, D.—NAE, Ph.D. (Yale University); Institute Professor of Science and Technology (joint in Lally School of Management and Information Technology); management of technological organizations, innovation, policy, robotics, policy issues of research and development in the service sector.
Graves, R.J.—Ph.D. (State University of New York at Buffalo); manufacturing systems modeling and analysis, facilities planning and material handling system design, scheduling systems, concurrent engineering and design for manufacture, continuous flow manufacturing systems design, distributed manufacturing concepts, information infrastructure.
Raghavachari, M.—Ph.D. (University of California at Berkeley); statistical inference, quality control, multivariate methods, scheduling problems.
Sullo, P.—Ph.D. (Florida State University); reliability, life testing, statistical quality control, quality management, biostatistics, industrial statistics.
Tien, J.—NAE, Ph.D. (Massachusetts Institute of Technology); systems modeling, queuing theory, public policy and decision analysis, computer performance evaluation, and information and decision support systems, expert systems, computational cybernetics.
Wilkinson, J.—Ph.D. (University of North Carolina); regression modeling, statistical analysis.
Willemain, T.R.—Ph.D. (Massachusetts Institute of Technology); probabilistic modeling, data analysis, forecasting.
* Departmental faculty listings are accurate as of the date generated for inclusion in this catalog. For the most up-to-date listing of faculty positions, including end-of-year promotions, please refer to the Faculty Roster section of this catalog, which is current as of the May 2014 Board of Trustees meeting.
Objectives of the Undergraduate Curriculum
The Industrial and Management Engineering program is designed to prepare students for continued learning and successful careers in industry, government, academia, and consulting. Within a few years of graduation our graduates of the Bachelor of Science programs are expected to:
- pursue professional positions in industry and/or graduate study programs in their areas of interest.
- contribute to the body of knowledge in their professional discipline through problem-solving, discovery, leadership, and responsible application of technology.
- continue to develop both professionally and personally through activities such as participation in professional societies, continuing education, and community service
The Industrial and Management Engineering degree program is accredited by the Engineering Accreditation Commission of ABET, http://www.abet.org.
The ISE department offers an undergraduate curriculum in Industrial and Management Engineering (IME). The first two years of this curriculum provide a strong foundation in basic science, engineering science, mathematics, and the humanities, arts, and social sciences. These two years are oriented toward the quantitative (mathematical) approach. Computer-based technology, including simulation, computational modeling, and systems design, is emphasized. In the last two years of the program, students concentrate on building expertise in statistics, operations research, manufacturing and services engineering, and industrial engineering methods and models. Through the appropriate choice of electives, students can focus on their selected areas of interest. Design projects include problems in manufacturing, services, and public systems. It is advisable to develop a Plan of Study leading to the desired degree and concentration by the beginning of the third year. The department recommends that students declare their intent to major in Industrial and Management Engineering as early as possible in their academic career. Students are also urged to work closely with their assigned faculty advisers to ensure that all degree requirements are satisfied.
This curriculum requires a minimum of 128 credit hours and completion of the course requirements shown in the typical four-year program presented in the Programs section of this catalog.
Special Undergraduate Opportunities
Cooperative Education Program
The department encourages this option, which allows students to gain professional experience as part of the educational program. Additional information on co-op opportunities is included in the Educational Programs and Resources section of this catalog, as well as through the faculty adviser or the Center for Career and Professional Development.
The Industrial and Systems Engineering Department offers the Master of Science and Master of Engineering degrees in Industrial and Management Engineering. Both degrees require a minimum of 30 credit hours. The Master of Science degree requires a thesis. The Master of Engineering degree is a non-thesis option. All applicants to the IME master’s programs must take the Graduate Record Exam (GRE).
The Industrial and Systems Engineering Department offers the Ph.D. in Decision Sciences and Engineering Systems. All applicants to the Ph.D. program must take the Graduate Record Exam (GRE). During the first year of residency, doctoral students are required to elect courses from the restricted list of approved doctoral courses which are subject to adviser and Doctoral Program Director approval. The approved list of courses can be found under the Ph.D. in Decision Sciences and Engineering program information.
Courses directly related to all Industrial and Systems Engineering curricula are described in the Course Description section of this catalog under the department code ISYE.