Possible prerequisites for IESM 372 course -cs213 iesm220 not to be used for registeration (EQOptOR)
Credits:0
Possible prerequisites for IESM 372course -cs108 iesm106 not to be used for registeration (EQStatPro)
Credits:0
Intro to MATLAB (IESM050)
Credits:3
Three hours of lecture per week. MATLAB (MATrix LABoratory) is a leading software used for numerical analysis. It provides an environment for computation and visualization. Students will work toward developing a working knowledge of MATLAB to implement and test algorithms, thus enabling a deeper understanding of and facility working with analytical engineering tools.
Analysis and Design of Data Systems (IESM301)
Credits:3
Three hours of lecture per week. Review of data systems and data processing functions; technology; organization and management; emphasizing industrial and commercial application requirements and economic performance criteria; survey of systems analysis, design; modeling and implementation; tools and techniques; design-oriented term project.
Quality Assurance and Management (IESM311)
Credits:3
Three hours of lecture per week. Principles and methods of statistical process control, quality engineering, total quality management, as applied to manufacturing and service industries.
Data Mining & Predictive Analytics (IESM313)
Credits:3
Exploratory Data Analysis; Classification: Decision Trees, Model Evaluation, Overfitting; Linear and Logistic Regression; Association Analysis; Cluster Analysis; Anomaly Detection; Model Building and Validation
Design and Analysis of Experiments (IESM315)
Credits:3
Three hours of lecture per week. Principles and methods of design and analysis of experiments in engineering and other fields, realworld applications of experimental design, completely randomized designs, randomized blocks, latin squares, analysis of variance (ANOVA), factorial and fractional factorial designs, regression modeling and nonparametric methods in analysis of variance.
Operations Research 2 (IESM321)
Credits:3
Deterministic and stochastic models and methods in Operations Research, network analysis, integer programming, unconstrained and constrained optimization, deterministic and stochastic dynamic programming, Markov chains, queuing theory.
Applied Statistics for Engineers (IESM324)
Credits:3
This course starts by introducing the probability laws as a foundation for statistical inference in engineering. The concept of the likelihood function in an engineering model is illustrated. The course provides a substantial coverage of propagation of error, as well as an emphasis on model-fitting. The use of simulation methods and the bootstrap is made for verifying normality assumptions, estimating bias, computing confidence intervals, and testing hypotheses. In the second part of the course, diagnostic procedures are introduced for linear regression models including material on examination of residual plots, transformations of variables, and principles of variable selection in multivariate models. The analysis of data from a class of experiments is discussed along with statistical quality control. Instructor led lectures and discussion. Assessment by problem sets, exams, and projects.
Simulation of Industrial Engineering Systems (IESM330)
Credits:3
Three hours of lecture per week. Design, programming and statistical analysis issues in simulation study of industrial and operational systems, generation of random variables with specified distributions, variance reduction techniques, statistical analysis of output data, case studies, term project.
Production Systems analysis (IESM331)
Credits:3
Three hours of lecture per week. Analysis, design and management of production systems. Topics covered include productivity measurement; forecasting techniques; project planning; line balancing; inventory systems; aggregate planning; master scheduling; operations scheduling; facilities location; and modern approaches to production management such as Just-In-time production.
Engineering Economics (IESM340)
Credits:3
Three hours of lecture per week. Analysis of economic investment alternatives, concepts of the time value of money and minimum attractive rate of return, cash flow analysis using various accepted criteria, e.g., present worth, future worth, internal rate of return, external rate of return, depreciation and taxes, decision making under uncertainty, benefitcost analysis, effects of inflation (relative price changes).
Supply Chain Management (IESM345)
Credits:3
This course focuses upon the strategic importance of supply chain management. The purpose of the course is to design and manage business-to-business to retail supply chain purchasing and distribution systems, and to formulate an integrated supply chain strategy that is supportive of various corporate strategies. New purchasing and distribution opportunities for businesses and inter/intra company communications systems designed for creating a more efficient marketplace are explored.
Managing Engineering and Technology (IESM346)
Credits:3
Managing Engineering and Technology is designed for engineers, scientists, and other technologists interested in enhancing their management skills, and for managers in enhancing their skills and knowledge about engineering and science. Specifically, the course is tailored to the needs of technical professionals and will cover: the historical development of management with an emphasis on the management of technology, management methods and tools, transition from technical performer to technical management, and the nature and application of management principles throughout the technology product/project life cycles._x000D_ The course will be based on a mix of theory, empirical evidence and real-life cases. Instructor-led discussion, along with reading, written, and practical assignments.
Design and Innovation of Information Services (IESM347)
Credits:3
The course aims to provide with theoretical and practical insight into the key concepts and issues that guide the design and development of modern information services. The students will explore the contextual considerations of designing information services through in-depth examination of expanding possibilities for innovation and associated risks that modern-day devices, data, content, systems and infrastructures offer. Of particular interest will be the structuring and design of problems in industries with complex ecosystems using Soft Systems Methodology and Unified Modeling Language with special stress on capturing and analyzing information requirements of parties involved._x000D_ _x000D_ No prerequisite knowledge is required. As part of the course, students will design their own information service to address a problem of their choice, using all the depth of technical and social issues facing companies, individual users and societies.
Enabling Competitive Advantage through Information Technology (IESM349)
Credits:3
This class is intended to introduce students to the critical role of information technologies (IT) in enabling competitive strategies. Our particular focus will be the impact that IT can have on non-IT companies, from industries such as transportation, supermarkets, financial institutions, and healthcare. This is not a “how-to” guide on managing enterprise information systems. Rather, the focus is on the word Enable, and we will explore how different companies have used IT to develop significant competitive advantage in the marketplace. The course will consist of case readings and discussions, short assignments, group project, and mid-term and final exams.
Alternative Energy (IESM350)
Credits:3
The course reviews: the basics of the alternative energy generation options, the respective technologies and resources, as well as the economic, environmental and urban aspects of their introduction into the modern society. Topics include: the role and the current status of the alternative energy in the modern society, energy and force – phenomena and units, solar radiation characteristics, carbon cycle and traditional sources of energy, solar thermal processes (options), such as wind, solar heat, ocean heat and wave, solar hot water, solar electricity, passive solar, solar photon processes, such as solar photovoltaics – from principles to systems, biomass, biofuel, biogas, etc, nuclear power – fusion and fission, infrastructure related economics, distributed power, energy storage, etc.
Sustainable Smart and Resource Efficient Systems 1: Systems and Technologies (IESM351)
Credits:3
The course introduces students to the latest practices and technologies in reducing the environmental impact of buildings and the built environment with specific focus on energy, water, and waste. Students will be expected to gain analytical and quantitative skills in analyzing energy, transport, water, and solid waste with the aim of estimating ways to achieve “carbon neutrality,” “zero emissions,” among other green goals. Students will also be introduced to green built environment norms established by the US Green Building Council as well as other international companies.
Sustainable Smart and Resource Efficient Systems 2: Decision Making Tools (IESM352)
Credits:3
The course will focus on non‐design decision tools. The analytical tools to be covered will include financial (payback period, NPV, and IRR), economic (Input‐Output, Cost‐Benefit), and environmental (Life Cycle Assessment, McKinsey Carbon Abatement Analysis, Carbon Footprint, Water Footprint, Ecological Footprint). Many of these analyses will be relevant for a wide range of industries including transportation, construction, manufacturing, as well as energy. The course will use cases and simulations to teach and deepen understanding of core concepts and methodologies.
Computer-Aided Design (IESM360)
Credits:3
Fundamentals of part design; computer-aided design tools and data structures; geometric modeling; transformations; CAD/CAM data exchange; mechanical assembly.
Computer-Aided Manufacturing (IESM361)
Credits:3
Introduction to manufacturing processes; cutting fundamentals; design for manufacturability; design for machining; process engineering; NC fundamentals; manual NC programming; computer-aided part programming; group technology.
Advanced CAD/CAM Applications (IESM362)
Credits:3
Advanced surface and solid modeling, top down and bottom up assembly, finite element analysis, sensitivity studies, optimization, advanced computeraided part programming and manufacturing, mold design, team work.
Portfolio Theory and Risk Management (IESM372)
Credits:3
Students in this course will become familiar with the basic concepts of interest theory, portfolio theory and risk assessment and be able to apply these in problem solving, with an emphasis on mathematical and computational approaches. The student will also become acquainted with various financial risk management instruments and use different criteria to optimize portfolios, taking into consideration the strengths and weaknesses of different portfolio selection criteria. Instructor led lecture and discussions; assessment may include problem sets, software implementation, exams, and projects.
Integrative Project in Modern Production Methods (IESM390)
Credits:3
Two hours of lecture and discussion and six hours of field work per week. This is a projectbased course that involves field work (in manufacturing or service organizations) and integrates and synthesizes knowledge gained from several courses (e.g., operations management, operations research, statistics, and quality management). Student teams, supported by several faculty members, will work with industrial companies to identify improvement opportunities and help in implementing them.
Independent Study (IESM391)
Credits:3
Special study of a particular problem under the direction of a faculty member. The student must present a written, detailed report of the work accomplished. Approval of the IESM Program Chair and the instructor is required.
Capstone Preparation (IESM395)
Credits:2
Review of Capstone objectives and procedure; faculty and industry representatives’ presentation of suggested research topics; field trips to the local companies; literature survey and classroom presentation by students. Students select the topic of their capstone project and the supervisor and prepare and submit the project proposal. Students draft a literature survey on their selected topic, which will constitute a section or chapter of the capstone project report. The completed and approved Proposal for Culminating Experience Requirement form must be filed in the College office prior to the end of the course.
Capstone: Thesis (IESM396)
Credits:4
One of the two Capstone options offered by the Program. Supervised individual study employing concepts and methods learned in the program to solve a problem of significant importance from a practical or theoretical standpoint. This option is more appropriate for those students who are interested in an in-depth R&D experience.
Capstone: Project (IESM397)
Credits:1
One of the two Capstone options offered by the Program. Supervised individual study employing concepts and methods learned in the program to solve a problem from a practical standpoint. This option is more appropriate for those students who are inclined to practical work and do not necessarily aspire for intensive research training.