Graduate Course Descriptions
ININ 5005. Modern Optimization Methods. Three credit hours. Three hours of lecture per week. Advanced undergraduate course addressed to Industrial Engineering students to studies the most common heuristic search methods. Topics such as simulated annealing, genetic algorithms, tabu search, and combinatorial and continuous optimization problems are discussed. The main techniques and their variations presented and are critically discussed. Key papers from the literature, including applications, are discussed.
ININ 5006. Systems Engineering and Analysis. Three credit hours. Three hours of lecture per week. Introduction to systems engineering or the discipline of designing systems considering the systems lifecycle from conceptualization to disposal. The student will learn the system development process beginning with the problem definition/needs or opportunity identification, system feasibility, system’s requirements, functional analysis, conceptual design, implementation. Students learn to plan a design for operational feasibility (including reliability, maintainability, usability, and supportability), prepare documentation for development of systems, including the basic theory of system’s lifecycle management. They also learn techniques to evaluate the design. The nature of this course is a multidisciplinary one, as systems can be industrial, mechanical, electronic, and organizational. A course project encompassing the step-by-step development proves and subsequent documentation of a system is required.
ININ 5007. Complex Systems Modeling and System Dynamics. Three credit hours. Three hours of lecture per week. This course introduces system dynamics modeling for the analysis of business decision with a focus on industrial, service and public policy applications. Particularly those forced by structural changes, policies and strategies that affect how the system behaves. It provides the student with the conceptual tools to understand the structure and dynamics of complex systems. The student will learn how to apply this modeling method to build formal computer simulations of complex systems and use them to design more effective policies and organizations. Students will create decision support systems where space and time can be compressed and slowed for the decision maker to experience the long-term side effects of decisions.
ININ 5009. Lean Six Sigma Methodology. Three credit hours. Three hours of lecture per week. Discussion of the basic principles of Lean and Six Sigma methodologies to maximize the value of a product or service focusing primarily on customer satisfaction. Use of the DMAIC methodology as a structured way to integrate the tools of industrial engineering to solve problems related to processes and systems improvement.
ININ 5105. Introduction to Medical Device Design Methods. Three credit hours. Three hours of lecture per week. This course presents the fundamental methods for medical device development. It is designed for students interested in a comprehensive study of the medical device development process, from concept ideation to marketing. It discusses methods that aid completing the procedures of product definition, design, risk management, production planning and market introduction, in an environment of multiple stakeholders, FDA (Food and Drug Administration) regulations and intellectual property protections. The course includes case studies illustrating important considerations to manage the complexities of the development process.
ININ 5405. Statistical Methods in Bioinformatics. Three credit hours. Three hours of lecture per week. Study and application of statistical methods related to the most important bioinformatics analyses including: sequence analysis, gene expression and phylogenetic trees. The methods under study include inferential statistics, statistical modeling, clustering analysis and Markovian processes.
ININ 5505. Total Quality Management. Three credit hours. Three hours of lecture per week. Introduction to innovative philosophies in total quality control. The impact of leadership, organizational infrastructure and client satisfaction on quality management. Utilization and management of information, personnel, processes and product design for continuous quality improvement.
ININ 5555. Introduction to Non-Linear Optimization and Neural Networks. Three credit hours. Three hours of lecture per week. Basic Concepts of Classical Optimization Techniques. Unconstrained Optimization will Include Multivariate-searching Techniques without using Derivatives, and Optimization Techniques Based on the Gradient Method. Constrained Optimization Techniques will be focused in Sequential Quadratic Programming. Application in Industrial Settings will be focused. Neural Networks will be introduced as A Nonlinear Modeling Technique. Neural Networks will cover the Perception, The Adaline, The Backpropagation and Levenberg-marquardt Backpropagation Algorithms. Applications of Neural Networks In Industrial Setting Will.
ININ 5559. Engineering Statistics. Three credit hours. Three hours of lecture. Development of probability theory for scientific and engineering inference. Discrete and continuous random variables and distributions and their applications in engineering. Hypothesis testing and confidence intervals. Regression analysis. Applications to engineering problem solving.
ININ 5565. Measurement and Prediction of Product Reliability. Three credit hours. Three hours of lecture per week. Introduction to reliability theory; system analysis; constant failure rate models; time dependent failure rate models; state dependent systems; availability; maintainability; complete and censored data analysis (parameter estimation and distribution fitting); prediction of reliability.
ININ 5575. Sequencing and Scheduling Of Resources. Three credit hours. Three hours of lecture and/or discussion per week. Conceptual and practical aspects involved in the scheduling of resources. Examples and applications drawn from areas such as manpower, computer, and transportation.
ININ 5595. Design and Management of Service Processes. Three credit hours. Three hours of lecture per week. Industrial engineering techniques and models to design and manage the operations of service organizations or service processes in manufacturing enterprises. Development, evaluation, and implementation of alternative solutions to the operational problems of service organizations. Use of models and techniques in marketing, quality assurance and management, work measurement and design, operations research, production planning and control, engineering economics, human resources, management information systems, and facilities layout.
ININ 6005. Experimental Statistics. Three credit hours. Three hours of lecture and/or discussion per week. Applications of multiple regression to analysis of variance and experimental designs. Analysis of multiple classifications involving fixed, random, and mixed effects, including crossed and nested variables of classification. Emphasis on computer model applications.
ININ 6008. Network Flows and Graphs in Management Science. Three credit hours. Three hours of lecture and discussion per week Principles of network flows and graphs theory and their applications in management science. Classical network flow problem formulations including maximal flow-minimal cut, assignment, transportation and others. Representation of optimization problems as network formulations, and the use of the out of kilter algorithm for their solution. Single versus multi-commodity flow, as well as the relation of graphs and networks to combination problems.
ININ 6010. Multiple Regression Analysis. Three credit hours. Three hours of lecture per week. Analysis of unplanned experimental data to develop models for predicting complex systems behavior. Topics include: matrix formulation and properties of least squares estimators in multiple linear regression; analysis of residuals; diagnostics for influential data; strategies for variable selection; diagnostics, effects, and corrective measures for problems with correlated predictor variables; biased regression and other estimation criteria; autocorrelated residuals; simultaneous inference, model validation; use of computer programs to analyze real data and to develop a model.
ININ 6016. Human Factors Engineering. Three credit hours. Three hours of lecture and discussion per week. Human factors applications in the design of equipment and work environment. Methods for the analysis of human errors and skills and their utilization in the design of control systems and information displays.
ININ 6019. Advanced Production Control. Three credit hours. Three hours of lecture and discussion per week. Advanced topics in forecasting, inventory and applied stochastic processes as they relate to production control systems. Integration of these topics in the production planning process using mathematical optimization techniques and case studies.
ININ 6020. Queueing Theory and Applications. Three credit hours. Three hours of lecture per week. Development and use of analytical models for the design of queuing systems. Introduction to stochastic-process models. Applications to analysis, design, and optimization of queuing systems in service and manufacturing organizations.
ININ 6025. Linear and Discrete Optimization. Three credit hours. Three hours of lecture and discussion per week. Basic theory and development of the simplex method for solving linear programming problems with discrete variables. Dual problems and sensitivity analysis. Formulation of problems with discrete variables. Developments of implicit enumeration and related methods for integer problems. Application of linear and discrete optimization methods to problems of industry and government. Use of computer programs.
ININ 6026. Systems Simulation. Three credit hours. Three hours of lecture and discussion per week. Principles of feedback dynamics; levels; rates, delays. Simulation languages and their applications in industrial and service systems. Analysis and interpretation of results. Recommendation and justification of proposed alternatives.
ININ 6030. Advanced Economics For Engineers. Three credit hours. Three hours of lecture per week. Formulation of economic problems in terms of quantifiable models. Use of deterministic, probabilistic, risk and multiattribute techniques to evaluate design alternatives and to select an acceptable solution.
ININ 6036. Introduction to Time Series Analysis. Three credit hours. Three hours of lecture per week. Univariate and bivariate time series in frequency and time domain, use of autocorrelation and spectral analysis for model identification. Uses of model diagnostic and forecasting techniques, dynamic systems modeling and stochasting estimation by means of the Kalman filter.
ININ 6045. Material Handling Systems. Three credit hours. Three hours of lecture per week. Fundamentals of material handling systems including types of equipment and their applications, relationship between material handling and design of facilities, computer control, and automation. A project will be required.
ININ 6046. Advanced Industrial Experimentation. Three credit hours. Three hours of conference per week. Applications, analogies and differences among confidence intervals, prediction intervals, and tolerance intervals. Fundamental concepts and applications of response surface methodology and evolutionary operations to manufacturing processes. Case study of manufacturing experiments with dichotomous or polytomous response variables. Use of logistic regression for modeling the relationship between a categorical variable and a set of covariates. Effective modeling strategies and the interpretation of results are emphasized. Fundamental concepts in the design and analysis of experiments with mixtures. Statistical techniques and methods for designing, modeling, and analyzing mixture data. Extensive use of software packages for statistical data analysis.
ININ 6048. Knowledge Discovery in Engineering Multivariate Data. Three credit hours. Three hours of lecture per week. Development of empirical linear and non-linear model building skills using a variety of tools from multivariate statistics and data mining. Development of skills to identify the model that best represents the natural relationship between a numerical and/or categorical response, and a high-dimensional set of explanatory variables. Special attention is given to data pre-processing, missing value imputation, outlier detection, feature extraction/selection, and model validation. Introduction to unsupervised learning and modeling techniques for multiple response variables.
ININ 6055. Mathematical Models in Distribution Logistics. Three credit hours. Three hours of lecture per week. Study on the logistics involved in transporting finished goods from manufacturers to customers. Particular emphasis is given to the design and operation of container terminals, cross-docks, and distribution centers, as well as the management of freight transportation modes. Emphasis will be given on mathematical models for the optimization of distribution systems and their implementation.
ININ 6078. Quality Control Systems. Three credit hours. Three hours of lecture per week. Advanced topics in statistical process control. Design of control charts. EWMA charts. The SPRT and its applications in quality engineering: CUSUM and continuous sampling plans. Multivariate control charts. Principles of quality engineering and Taguchi methods. The loss function and its applications to multiresponse experiments.
ININ 6995. Special Programs. One to three credit hours. One to three hours of lecture per week. Study of previous work and literature on a selected topic of the industrial engineering field.
ININ 6998. Engineering Project. Three to six credit hours. Comprehensive study of a special industrial engineering problem selected so as to integrate the knowledge acquired in the graduate program study. This project fulfills one of the terminal requirements of the Master of Engineering program, and will be governed by the norms established for this purpose.
ININ 6999. Thesis. One to six credit hours. Research in the Industrial Engineering field leading to the presentation and approval of a thesis.