Undergraduate Course Offerings

The follow is a sample of the undergraduate course offerings in Systems Science and Industrial Engineering. See official course listings in the University Bulletin or register for classes through BU Brain.

ISE 212, ENGINEERING COMPUTING

The objectives of the course are to: demonstrate the ability to design systems for automating processes in manufacturing, demonstrate problem-solving skills in automation, and to demonstrate the skill of using the LabVIEW and MATLAB software packages. Prerequisite: sophomore standing in engineering or consent of department chair.
Spring, 4 cr. required

ISE 231, HUMAN FACTORS

Review of the concepts involved in the application of scientific principles, methods, and history to the development of engineering systems in which people play a significant role. Primary focus is on the man/machine interface and how to design for the human being as part of an overall system. Prerequisite: MATH 222 or consent of department chair.
Fall, 4 cr. required

ISE 261, PROBABILISTIC SYSTEMS I

This course provides an introduction to probability models and statistical methods most likely to be encountered and used by students in their careers in engineering and the natural sciences. This introduction will emphasize, from the outset, that variation is the source from which all statistical methodology flows. Discussion includes the practical aspects of data collection and descriptive statistics with an introduction to the basic concepts of probability theory and probability distributions, correlation, point estimation, confidence intervals, and test of hypothesis. Prerequisites: Sophomore standing in the Watson School or consent of department chair.
Spring, 4 cr. required

ISE 295, SEMINAR

Development of the non-technical skills essential to effective engineering. Focus is on the overview of ISE curriculum and review of technical elective options. Review of internships, resume building, issues relevant to careers in ISE (e.g., typical tasks done by ISEs) are explored. Discussion and exploration of opportunities within program. Prerequisite: Sophomore standing.
Fall, 1 cr. required

ISE 311, ENTERPRISE SYSTEMS

Course introduces the concepts, design and planning of operating systems, with particular emphasis on manufacturing systems. Topics include introduction to lean manufacturing, JIT, Kanban, value stream mapping, standard times, MRP, inventory control, etc. The course includes plant tours to local industries that practice the concepts of the Toyota production system. Prerequisite: ISE 364 or consent of department chair.
Spring, 4 cr. required

ISE 312, MANUFACTURING SYSTEMS

This course has three main areas of focus: production and inventory control, planning and design of manufacturing facilities, and understanding the physical fundamentals of processes and is designed mainly for engineering students intent on following an engineering career in a manufacturing industry. This course covers the models, networking, and systems needed to design and manage a manufacturing enterprise. Topics include facility design and material handling, forecasting techniques, demand management, economic lot size, inventory management, and scheduling methods. This is considered a technical elective. Prerequisite: Sophomore standing in the Watson School or consent of department chair.
3 cr.

ISE 320, OPTIMIZATION AND OPERATIONS RESEARCH I

Operations research (OR) is devoted to determination of the optimal course of action of a decision problem given resource restrictions. This course primarily covers deterministic optimization and operations research techniques. Following a review of linear algebra, students learn how to mathematically model an engineering problem, how to solve the problem to optimality and how to perform sensitivity analyses on the results. Students learn linear programming (LP), integer programming (IP), branch-and-bound (B&B), and other optimization techniques. Special emphasis on the solution of engineering decision making includes the following areas: transportation models; network models; inventory models; assignment problems; decision making under risk and uncertainty; and game theory. For non-ISE students using this course as an elective for the Sustainability Engineering minor, application of these techniques as applied to decision-making for sustainability are included. Prerequisite: Math 304 or consent of department chair.
Spring, 4 cr. required

ISE 362, PROBABILISTIC SYSTEMS II

Methods of inference involving two independent samples and paired data are presented. The analysis of variance is examined for single-factor and multi-factor experiments. Regression analysis for simple linear models and correlation are discussed followed by non-linear and multiple regression models. A practical, yet fundamental, approach for building quality control charts from statistical concepts, as well as a goodness-of-fit test for testing discrete and continuous underlying distributions, are reviewed. Prerequisites: ISE 261 Probabilistic Systems I or permission of the instructor.
Fall, 4 cr. required

ISE 363, DESIGNING WITH EXPERIMENTS

Learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Topics include the principles of experiment design, analysis of variance, completely randomized designs, randomized block designs, other blocking configurations, general full factorial, 2k, 3k full factorial and fractional factorial designs. Blocking and confounding in a factorial experiment and alias phenomena in a fractional factorial experiment will be emphasized. Prerequisite: ISE 362 or consent of department chair.
Spring, 4 cr. required


ISE 364,
ENGINEERING ECONOMICS AND PROJECT MANAGEMENT

This course deals with economic analysis of engineering, in particular, with the evaluation of projects in terms of time and cost. It also deals with managing engineering projects from design through completion. Topics include interest rates, time value of money, present and future worth, economic evaluation of alternatives, taxes, inflation and justification of new technologies. Also included are project related management tools, such as project planning, budgeting, work breakdown structure, monitoring and completion. This course emphasizes the early stages of project development, which have a great impact on the quality, cost and schedule of a project. Appropriate computer tools are used. Prerequisite: Junior standing or consent of department chair.
Fall, 4 cr. required

ISE 370, INDUSTRIAL AUTOMATION AND CONTROL

Industrial automation is a major field in the application of computer controls and the many advances in computer systems. The objectives of this course are to: demonstrate the ability to design systems for automating processes in manufacturing, demonstrate problem-solving skills in automation, and safely use the machines in the engineering laboratory to complete designated experiments. Lectures and laboratories include exploring the use of sensors, industrial robotics, numerical control, programmable logic controllers, machine vision, electrical circuits and the fundamentals of common electrical devices, fuzzy control, the implementation of online computer control, and the ability to use industrial technical software including Pro-Engineer and AutoCAD. Laboratory work and technical reports are required. Prerequisites: Junior standing in ISE or consent of department chair.
Fall, 4 cr. required

ISE 415, OPERATIONS MANAGEMENT OF SUPPLY CHAINS

Course deals with management of supply chains, in particular, with the operational aspects. A broad overview of supply chains of a company is introduced, together with performance measures and needed critical success factors. The course concentrates on supplies, inventories, manufacturing, and logistics of distribution. Managerial aspects as well as mathematical modeling for better planning and control will be covered. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing in ISE or consent of instructor. Cross-listed with SSIE 515.
3 cr.

ISE 419, APPLIED SOFT COMPUTING

Covers relatively new approaches to machine intelligence known collectively as “soft computing”. Introduces various types of fuzzy inference systems, neural networks, and genetic algorithms, along with several synergistic approaches for combining them as hybrid intelligent systems. Emphasis is on applications, including modeling, prediction, design, control, databases and data mining. This course is considered a technical elective for undergraduate students. Prerequisites: Senior standing, basic knowledge of calculus and discrete mathematics and competence in at least one programming language, or consent of department chair. Cross-listed with SSIE 519.
3 cr.

ISE 420, OPTIMIZATION AND OPERATIONS RESEARCH II

Operations research (OR) is devoted to the determination of the optimal course of action of a decision problem given resource restrictions. This course is intended as a second course in an Optimization and OR sequence and builds upon the material presented in ISE 320. ISE 320 primarily restricts attention to deterministic OR models. In addition to covering additional deterministic techniques (e.g., deterministic dynamic programming and additional inventory problems not covered in ISE 320, among others), ISE 420 covers probabilistic and advanced OR topics such as Monte Carlo simulation, fundamentals of queueing theory, probabilistic dynamic programming, and others. The course also introduces the student to emerging optimization techniques including, but not limited to, tabu search, simulated annealing, and genetic algorithms. Prerequisite: ISE 320 or consent of department chair.
Fall, 4 cr. required

ISE 421, MODELING AND SIMULATION

Model building, nature of simulation and material on the full range of simulation activities, such as input analysis, output analysis, verification and validation, and model animation. Includes random number generation; distribution functions and random variates; applications of discrete event simulation methods to queueing, inventory control and production planning problems; Markov processes, queueing theory and decision analysis. Prerequisites: ISE 362 and ISE 320 or consent of department chair.
Fall, 4 cr. required

ISE 422, DECISION MODELING

Course provides a broad foundation in decision models and techniques used in industry and research for technical and managerial problems. Topics include: decision theory, risk and uncertainty, value of information, preference measurements, prioritization of alternatives, multiple objectives, and hierarchical decisions. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 362 or permission of the department chair. Cross-listed with SSIE 522.
3 cr.

ISE 434, HEALTH SYSTEMS ENGINEERING

One of the growing systems in our society is that of the healthcare delivery system. The purpose of this course is to introduce the concepts behind the healthcare delivery systems and to focus upon the systems improvement or continuous improvement techniques available for complex systems. Topics would include improvement to, and problems with: organizational structure, managing change, the financial structure, the responsibility structure, quality data and implications of quality measures, use of clinical decision support systems and the caregiver’s role in the system. There will also be a focus upon suppliers to the healthcare delivery system and the unique requirements placed upon their products and processes. This course is considered a technical elective for undergraduate students. Cross-listed with SSIE 534.
3 cr.

ISE 437, INDUSTRIAL AND SYSTEMS ENGINEERING IN HEALTH CARE

Introduction to health systems and health care delivery. The application of industrial and systems engineering principles to continuous process improvement in the health care domain will be studied. Concepts that will be addressed will include, but not be limited to, process mapping, optimization, scheduling, lean and flexible systems, quality enhancement, simulation, supply chain management, inventory control, and information management. The course is considered a technical elective for undergraduate students. Prerequisites: Senior standing in ISE or consent of instructor. Cross-listed with SSIE 537.
3 cr.

ISE 439, HUMAN FACTORS ENGINEERING IN HEALTHCARE

This course introduces and emphasizes the role that human factors engineering/ergonomics plays in healthcare systems, with a focus on its applications to help improve quality, safety, efficiency, and effectiveness of patient care. Focused topics include human factors in workflow models; work system design for patient safety; human error analysis/taxonomies to reduce medical errors; task analysis and data collection methods in healthcare environments; clinical staff workload and patient safety; physical ergonomics in healthcare and human performance modeling; and diffusion and adoption of technology in healthcare, with emphasis on the usability and design of medical devices and information systems. Prerequisite: Senior standing in ISE or consent of instructor. Cross-listed with SSIE 539.
3 cr.

ISE 440, INTRODUCTION TO SYSTEMS SCIENCE

Includes the following: a general characterization of systems science as a field of study; intellectual roots, philosophical assumptions and historical development of the field; an overview of fundamental systems concepts, principles and laws; and a survey of application areas of systems science and its implications for other fields of study. This course is considered a technical elective for undergraduate students. Prerequisite: Junior standing or consent of instructor. Cross-listed with SSIE 501.
3 cr.

ISE 456, EXPERT SYSTEMS IN MANUFACTURING

Computer-based decision-making tools in which a domain expert's knowledge is embedded are known as knowledge-based expert systems (KBESs). Expert systems allow such expert knowledge to be widely disseminated (e.g., throughout a company or throughout different facilities that a company has). This course introduces the student to all steps of development (e.g., knowledge representations, knowledge acquisition, and expert system development, among others) with special emphasis on manufacturing applications. The course will culminate with the students developing functioning prototype expert systems in a manufacturing area of their choice. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing in ISE or consent of department chair. Cross-listed with SSIE 556.
3 cr.

ISE 462, COST ESTIMATING FOR ENGINEERS

Changes in our society have resulted in major changes in manufacturing to the point at which labor costs are no longer the controlling cost, or even the major cost. Major costs have shifted to the material and material-related costs, with the overhead and burden costs almost as significant. While innovative design is critical to engineering, being profitable is also critical, and profit starts with determining the proper costs for a product or idea. Topics include costs of labor, equipment, material, overhead or burden, volume/cost relationships, use rates, collection, build-up of costs, costing of manufacturing operations, standard costs and variances. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 364 or consent of department chair.
3 cr.

ISE 464, ELEMENTS OF FUZZY LOGIC AND FUZZY SET THEORY

Simple introduction to basic elements of fuzzy logic and fuzzy set theory, including an overview of classical logic and classical set theory. Included are basic concepts and properties of classical sets and fuzzy sets, classical relations and fuzzy relations, classical logic and fuzzy logic, and fuzzy arithmetic. The practical utility of fuzzy logic and fuzzy set theory is illustrated by describing selected applications in various areas of human affairs. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 261 or consent of the instructor.
3 cr.

ISE 473, ELECTRONICS MANUFACTURING

The purpose is for the students to gain a broad knowledge and understanding of the basics of printed circuit board manufacturing and assembly. The course offers an introduction to surface mount and insertion mount components, materials and processes as well as to PCB design and manufacturing. Lectures will introduce assembly process flows and component types, PCB construction and defects solder paste printing and equipment, placement processes and equipment, reflow and ovens, flip chip assembly and underfilling, defects and mitigation, reliability optimization and testing. Efforts will be made to include visits to local industrial assembly facilities as well as equipment on campus. The overall goal is to provide the students with a basis for communicating and working with subject matter experts. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing in ISE or consent of instructor. Cross-listed with SSIE 578.
3 cr.

ISE 491, SYSTEMS DESIGN

Covers the design process from the definition of requirements through the final output. Focus is on the design principles and design methodologies used to ensure a quality outcome. Prerequisite: Senior standing or consent of department chair.
Fall, 4 cr. required

ISE 492, SYSTEMS DESIGN PROJECT

The capstone project for the undergraduate degree. Students are expected to work in multi-disciplinary teams to provide solutions through design. Prerequisite: ISE 491 or consent of department chair.
Spring, 4 cr. required

ISE 497, INDEPENDENT STUDY

every sem., var. cr.

Last Updated: 11/27/13