IIND - Industrial Engineering

This course is the first actual contact between the student and the Industrial Engineering curriculum, along with all the possibilities that the Department and the University offer. Presents the different areas where Industrial Engineering graduated from Universidad de los Andes can contribute and develop their knowledge in Colombia and in the world. At the end of the course the students should be able to apply some of the tools, topics and contents of Industrial Engineering known and applied in a particular project (project EXPOANDES). Specifically, the course is proposed as an area of counseling and ongoing support for students in first semester to facilitate students' adjustment to their new role at university. Allows students to reinforce their decision about joining the Industrial Engineering program, or otherwise, provides the opportunity for responsible people who do not feel identified with the choice of life as an Industrial engineer to join one of the many programs offered by the Universidad de los Andes or other institutions. Finally it intends to show the university as an institution, interested in the development and training of the students as individuals.

The accompaniment program targets first semester students in Industrial Engineering. It is a voluntary program where mentors from advanced semesters support first semester students in their process to adapt to the university. Activities of different types will take place with groups of 10 students in each section with the main goal being to obtain high grade averages in the first semester of school. The Department of Psychology helped design the program based on the experiences of international universities in this area.

The course covers mathematical modeling, the algorithmic ideas behind it and the mathematical properties of optimization models. It familiarizes the student with mathematical programming packages. The main subjects are: Linear optimizations problems and its geometrical characterization, improving search, Simplex Method, initialization algorithms e.g. two-phase method, Big M method; duality theory, sensitivity analysis and Linear problems with special structures like transport and transfer applications. Finally, a brief introduction to the Branch-and Bound Method, is presented.

This course is intended to provide students with a sound preparation in stochastic processes basic concepts, and queuing and simulation theory, which enable them to better understand and use non-deterministic models in real problem formulation and solution. The course is divided in two parts: Discrete Time Stochastic Processes and Continuous Time Stochastic Processes.

Simulation enables the study of the behavior in a real system or a system proposed under present functioning conditions or under different operating scenarios. It finds increasing applicability s due to its high versatility, the inherent complexity reached by numerous modern systems, and the growing computing capacity, among other reasons. This course is oriented to manufacture and service system simulation, although it is also applicable in many other areas. Discrete simulation is highlighted but continual simulation elements are also included. Aspects such as modeling, experimentation, input and output information analysis, random variables generation, and variance reduction techniques, among others, are addressed.

This course is aimed to provide students with a comprehensive preparation in Probability and Statistic basic concepts and their applications, in such a way that they will better understand and use probabilistic models in the solution of real life problems that involve risk and uncertainty, as well as in statistic data management and analysis.

The course is focused on methods and statistics techniques. Parameter Estimation.Variability and standard error of estimators.Confidence interval, hypothesis testing, p- value.Analysis of Variance and experimental design.Linear Model and Regression analysis with emphasis in categorical variables and multicollinearity.

The course covers the basics of production planning and control operations. The main topics are: forecasting, aggregated planning, inventory systems and scheduling. The student should be able to identify, formulate and solve problems using the tools presented in the course. It is expected that after students have been exposed to current approaches they will be able to adapt them to real situations in manufacturing and service companies.

This course focuses on introducing students to fundamental concepts and tools to analyze and improve operations in manufacturing and services industries. The main subjects include work study, plant design and process flow study in manufacturing operations. The student, at the end of the course, must be capable of analyzing processes and infrastructure elements of production systems in order to identify improving alternatives from its operations standpoint. Complementary to class sessions, students develop a team-work project in a production company to analyze a real environment and put in practice concepts and tools.

The course aims to introduce System Dynamics as a way for developing  systemic thinking and understanding the behavior of complex systems,  particularly of social systems, in order to develop better skills in  policy design. Course subjects include: introduction to systems thinking  and dynamic complexity, basic concepts of System Dynamics such as causal loop diagrams, stock and flow models, model building, computer simulation tools, generic structures, evaluation of models, critical thinking and design of systemic policies.

The student should become familiar with the evolution of the concept of organizations so as to appreciate different dimensions to observe and to conceptualize such social systems. He should also be able to observe organizations from a systemic point of view; finally, he should be able to prepare a technical bibliography review report on an organizational topic.

The course covers evaluation of investment projects and capital budgeting alternatives. The different concepts introduced will allow the student to determine the financial viability and feasibility of an investment project. At the end of the course, the student must be able to understand the concept of time value of money, evaluate an investment project and calculate its net present value and its internal rate of return, evaluate a project under uncertainty and risk, as well as its sensitivity to the variables involved. Some of the course subjects include basic financial mathematics, selectin among mutually exclusive alternatives, and construction of cash flows, among others.

The course objective is to guide the student in his/her graduation work proposal presentation using the proposal presentation methodology, in order to structure the problem and solution knowledge gained, thus enabling research development. Based on the information supplied in the classes and through the electronic media, present to the student the elements that will allow analyzing and develop his/her graduation proposal. With the practical theory exercise, each student must prepare his/her proposal on a topic defined by him/her, and will arrange for the counseling of a professor from the Department to develop his/her research.

The graduation project is a work developed by the student, the purpose of which is to apply his Industrial Engineering concepts for problem solving. The project is developed in the last semester and consists in the application of specialized Industrial Engineering topics in problems related to government, industry and other institutions, and in the suggestion of practical, but creative and rigorous solutions. The project is developed under the counseling of a professor who shares the interest of the student in the subject selected. To develop the Graduation Project, regulations must be complied with, which require the student´s prior APPROVAL of all the mandatory subjects in levels 1 and 2.

The student enrolled in this course develops and presents the results of the capstone project.

One of the three projects carried out by the Industrial Engineering program students is the Intermediate Project, which is performed on the sixth semester. The main approach of this activity is to strengthen students´ skills to formulate problems related to work issues in the Industrial Engineering Department. Counseling of the Department´s professors is available, and subjects are defined based on the interests of students and on the Department´s decisions to support specific processes related to a particular problem. The equivalency of this project may be obtained through Business Internship. The Intermediate Project is expected to be articulated with the Graduation Project to allow students to develop projects with better impact on their environment.

This course seeks to train the student to translate concepts into context-specific operational decisions and actions in the field of marketing using analytical, quantitative and computer modeling techniques. It links theory to practice and practice to theory.

This course focuses in the development of models that represent systems that change through time (dynamic) and mostly whose states depend on random phenomena (stochastic). The main focus will be on simulation in discrete time and event driven. This has great application in Engineering and related areas for efficiency and versatility in modeling various types of systems, most of them inherently complex. Although the course focuses on discrete event simulation, it also includes elements of continuous simulation, and other topics relevant support in the fields of probability and statistics, data analysis, optimization, among others.

This course focuses in the development of models that represent systems that change through time (dynamic) and mostly whose states depend on random phenomena (stochastic). The main focus will be on simulation in discrete time and event driven. This has great application in Engineering and related areas for efficiency and versatility in modeling various types of systems, most of them inherently complex. Although the course focuses on discrete event simulation, it also includes elements of continuous simulation, and other topics relevant support in the fields of probability and statistics, data analysis, optimization, among others.

This course presents, addresses and compares different production strategies, based on the new competency models, and analyzes its applicability in the Colombian environment. Based on the changes made in the competitiveness factors, the effects of such changes on the production functions and the different strategies that this area can develop are analyzed, in order to strengthen the company´s competitive position in the market niches selected, and even to allow the development of new competitive advantages and new markets. The main subjects covered include production strategy, process strategy, automation strategy, flexibility strategies (JIT), cooperative strategy.

The current globalization and expansion trends experienced in modern economies have led many companies to develop flexible structures that will allow them to cope with the current situation or, otherwise, to disappear. Product differentiation is presented as a conclusive alternative to remain in the current market. The systematic development of products is the most adequate manner to ensure market penetration success and, therefore, for each market type and for each organizational culture type, there may be different development systems and models.

The intent of this course´s development is to offer the student a global quality function approach within organizations, both industrial and service-oriented. This subject is not a mere extension of the Statistics courses, but a comprehensive way of thinking about Quality and of being capable of understanding and solving its main problems. However, the scope presented conveniently uses techniques and methods both, quantitative and qualitative, which include statistical tools.

The intent of this course´s development is to offer the student a global quality function approach within organizations, both industrial and service-oriented. This subject is not a mere extension of the Statistics courses, but a comprehensive way of thinking about Quality and of being capable of understanding and solving its main problems. However, the scope presented conveniently uses techniques and methods both, quantitative and qualitative, which include statistical tools.

The logistics course includes different conceptual elements related to Supply Chain management. The basic components of the Supply Chain (customer service, transport management and inventory management) are analyzed from a systemic and integrator viewpoint. Students acquire Logistics Management skills, because they study the components and basic processes from an optimal management of suppliers, resources and customers’ perspective. Emphasis is made on the fact that the use of new information and communication technologies allows strengthening the efficiency of Logistics processes in the  organization. Process integration models are studied, such the SCOR model, and logistics processes are modeled through the use of mathematical models in the transportation, supply chain strategic design and inventory topics. The analysis methodology includes workshops where the logistics reality is analyzed by studying Colombian companies’ cases. In such regard, students are stimulated to use previous knowledge acquired in inventory models, forecast techniques, cost analyses, transport models, optimization and simulation techniques, among other topics.

The logistics course includes different conceptual elements related to Supply Chain management. The basic components of the Supply Chain (customer service, transport management and inventory management) are analyzed from a systemic and integrator viewpoint. Students acquire Logistics Management skills, because they study the components and basic processes from an optimal management of suppliers, resources and customers’ perspective. Emphasis is made on the fact that the use of new information and communication technologies allows strengthening the efficiency of Logistics processes in the  organization. Process integration models are studied, such the SCOR model, and logistics processes are modeled through the use of mathematical models in the transportation, supply chain strategic design and inventory topics. The analysis methodology includes workshops where the logistics reality is analyzed by studying Colombian companies’ cases. In such regard, students are stimulated to use previous knowledge acquired in inventory models, forecast techniques, cost analyses, transport models, optimization and simulation techniques, among other topics.

The purpose of the course is to educate professionals to be better trained and informed citizens, and so that as industrial engineers, they can venture into public problem analysis in a thorough, serious and agile manner. To achieve this goal, it is suggested to become acquainted with the origin, evolution and role of the Democratic State in the world, reflect on what should be the functions and responsibilities of the public and private sectors in an industry, become familiar with trends of the government size in Colombia, reflect on the major problems of Colombia and the role the government may or should play in their solution, discuss specific institutional analysis and development experiences in the public sector through conferences led by individuals well versed on the different topics.

The course follows an active learning approach that combines weekly readings, weekly lectures by former or present practitioners, much writing, and active student participation on a model republic formed by the students. We focus on issues of political economy and modern right and left ideologies, and try to find lessons to devise better Colombian public policies regarding economic development, poverty reduction and equity.

The course allows:

1. Familiarize the student with the COOPERATIVE AND COMPETITIVE models of COLLECTIVE BARGAINING and to provide him with the required tools that allow him to perform better in these processes in order to celebrate WIN-WIN labour agreements.
2. Evaluate the role of trade unionism in Colombia taking in consideration the economic, technological and social context. 
3. Enhance the student's negotiation skills and teach him how to take advantage of his emotional intelligence in the management of labor conflicts.

The purpose of the course is to introduce the student to the industrial relations field and its work implications to create abilities and skills that will allow him to better understand the human and organizational management problems. Contributes to the inter-disciplinary education of the future engineer by providing the tools required to effectively administer an industrial relations system at macro-economic and micro-economic levels.

The strategy course includes many concepts related to the development of a strategic plan in an organization. Throughout the course, basic components that make up strategy are thought (Mission, Vision, Delta Model, planning, Balance Score Cards and knowledge management among others). The main objective of the course is to create a context in which students use organizational strategic tools from a systemic perspective to develop the ability of the students to make strategic decisions. This is done through a simulation that lasts one semester in which students must make decisions every week.

The strategy course includes many concepts related to the development of a strategic plan in an organization. Throughout the course, basic components that make up strategy are thought (Mission, Vision, Delta Model, planning, Balance Score Cards and knowledge management among others). The main objective of the course is to create a context in which students use organizational strategic tools from a systemic perspective to develop the ability of the students to make strategic decisions. This is done through a simulation that lasts one semester in which students must make decisions every week.

The objetives of the course are:

• Contribute to the fulfillment of the main functions of the University: research, train integral people who recognize the ethical implications of their decisions, putting at the service of the community to which their professional knowledge belongs, developing projects in areas of entrepreneurship and innovation in engineering . 

• The formulation of projects (prototypes of products or services) will be supported, which will seek to support the creation of new companies, develop innovative projects or solutions in an existing company or solve any problem related to social, economic or environmental issues , applying the knowledge of Engineering.

• Offer a space for reflection to the student to integrate the different knowledge that he has acquired during his career, around the formulation of a project, specifically the design of a prototype and business model that solves a problem or takes advantage of an opportunity identified in the context. The aim is that the course contributes to the personal fulfillment of the student and contributes to the social and economic development of Colombia, with criteria of entrepreneurship and innovation for sustainable development.

• Promote work and collaborative learning in interdisciplinary groups, likewise seek, among others, to stimulate creative thinking, the application of negotiation tools, in which students apply knowledge of their career in the different stages of the identification process. creative process for the proposed solution, evaluation of alternatives, prototype design and business model.

This course is intended to provide conceptual framework and basic tools to analyze and understand the financial decision-making process in a corporation that operates within the framework of an efficient capitals market. The course content covers the different basic components of the investment and financing decisions financial theory within the context of a capitals market. Subjects include capitals market and efficiency lessons, share, risk and profitability valuation, investment decisions under uncertainty, capital structure and financing decisions, CAPM and the Modigliani & Miller propositions.

The Company Valuation course teaches students the methodologies used to valuate going concerns. The course is developed using the case methodology. The subjects addressed during the course include free and discounted cash flow, valuation using multiples, and the EVA concept as valuation and management method, and actual option valuation. The student will review the capital cost, terminal value concepts, and the basic financial statement projection methodologies for valuation purposes.

The Professional Practice is a learning alternative that complements the academic activities. It is based on the experience that students can have when they are immersed in the context of companies and institutions.

The purpose of Thesis I is to introduce students to the theoretical framework of their thesis and advances in the approach of the solutions to the selected problem. To enroll to this subject, the student must have a counselor (a task to be achieved by the student), must complete the corresponding form and obtain the Coordination permit.

During the second Thesis semester, students will devote all their time to research. Should more time be required, a maximum term of one semester will be granted (grace semester). To enroll in Graduation Thesis II, students must have passed Thesis I and must have completed the corresponding form.

The student enrolled in this course is finalizing the research project  and presents the results to a group of experts.

The purpose of this course is to teach students to estimate the parameters of linear models in order to quantify ratios between variables, compare theories and effects of various factors, prepare forecasts and build behavior models. The most commonly used and popular techniques in the statistical field are analyzed, the application of which covers a wide variety of natural science and social areas to tackle, in more detail, problems related to decision theory, market research, quality control, management, project evaluation, finance, etc. The main subjects studied include multiple regression analysis and design models for variance analysis. Specialized software, such as SAS, SPSS, MATLAB and Econometric Views are used.

The course presents various optimization subjects, such as lineal programming, restricted optimization, whole and combinatory programming. Among these, some specific subjects include convex analysis, simplex model, degeneration, cycling, duality, sensitivity analysis, Karush-Kuhn-Tucker conditions, inner point algorithm, single-modularity, Branch and Bound method, implicit numbering, decomposition, matroids and non-lineal programming elements.

The purpose of this course is to train students on how to manage useful statistical techniques to explore and model data collections, characterized by a large number of variables taken from a wide set of observations. The course content includes multi-varied measuring comparison, case study and tests of hypothesis of major interest, profiles and contrasts, analysis of main components, factorial analysis, correspondence analysis, and other segmentation methods, Conjoint Analysis, case presentation and analysis using the techniques and models studied.

A balanced consideration of factors influencing future events and perfect familiarity with the various existing forecasting techniques are required in order to properly make a forecast. The course’s main objective is studying techniques and tools which allow identifying the behavior or pattern of a time series (observations or data taken periodically throughout time) in order to predict its future behavior. The course has three modules: in the first one a review is made of the fundamentals of traditional forecasting methods for trend processes and for processes exhibiting some sort of seasonal pattern, in the second, ARIMA models and their GARCH extensions and transfer models are presented, the third module alternates sessions presenting cases illustrating the construction, identification and validation phases of the model with workshop sessions making extensive use of computers. Prerequisite: Linear Models or solid knowledge of statistics.

The objective of this course is to introduce modeling and optimization of stochastic systems with IIND-2104 as the prerequisite. The course will focus on formulation and analysis of industrial systems with stochastic components using analytical techniques such as continuous-time Markov chains, queues with batching, priorities, balking, open/closed queuing networks among others. Stochastic optimization techniques such as Markov Decision Processes and Stochastic Dynamic Programming will be discussed to conclude the course.    

Students who have demonstrated responsibility and interest for a specific area are offered this alternative, which gives them the opportunity to gain further knowledge of the area topics, under the guidance of a department professor. To take this course, the authorization of the academic coordination is required.

The general objective of this course is to give the students an integral view of systems and general industrial equipment for energy conversion (be it supply or consumption equipment). The student will use the general engineering fundamentals to analyze the performance of such systems and prime movers. The course is oriented towards the knowledge development for analysis, design of energy conversion systems, frequently used in industry.

This course introduces common technological methods involved in manufacturing and processing of products, made with different engineering materials. In order to achieve these objectives, the student will attend tutorials and discussion classes and will make guided investigations in the commercial and industrial environment. He also will participate in laboratory practice guided by the professor, class monitor or specialized technicians.

The course offers an analysis of manufacturing systems from the mathematical techniques standpoint (optimization and control) used to model and analyze the manufacturing production systems. It applies flow-shop and job-shop type systems and basic programming algorithms. Furthermore, it addresses topics such as flexible manufacturing, group technology, quadratic assignment methods and task sequencing, classic material management problems, queue and simulation models.

Students who have demonstrated responsibility and interest for a specific area are offered this alternative, which gives them the opportunity to gain further knowledge of the area topics, under the guidance of a department professor. To take this course, the authorization of the academic coordination is required.

This course provides the student with the tools required for the design of experiments and analysis of resulting data applied to solving engineering problems. The purpose of the course is to learn how to plan, design and carried out experiments efficiently and effectively, as well as to analyze the data produced by the experiment to reach objective conclusions under conditions of uncertainty. Concepts developed under this course can be applied in the execution of engineering processes, including design and development of new products, process development and improvement of manufacturing processes.

This purpose of this course is to lead the student in the application of advanced statistical methodologies to determine the conditions under which an industrial process must operate. Topics are related to quality management, data gathering, analysis of information, monitoring using control graphics, process capacity analysis, auto-correlation, among others.

The purpose of this course is to provide conceptual and methodological tools to understand, analyze, diagnose and redesign social organizations, and to promote the development of a self-management culture using the systemic approach, particularly the organizational cybernetics approach.

This course seeks to explore new simple means - mechanisms and models - to interpret and work in complex systems through the use of tools, the design of which is based on cellular automaton and physical models, among others. Tools will be used and applied in Mathematics. To enroll in this course, students are expected to be competent in Physics 3, Differential Equations and Probability content. Compliance with these pre-requirements is subjected to the consideration and responsibility of each student. A master´s degree program student must observe the programs of these courses to establish his compliance with the pre-requirements.

This seminar contributes to the conflict understanding and to the negotiation processes and, this way, it allows moving ahead with the organizational process knowledge. The Organizational Metaphor methodology proposed by Morgan (1986) is followed, and work is carried out to propose an organization image seen as negotiation systems. In addition to the techniques and analytic skills that allow finding optimum solutions to problems, we must base ourselves on the fact that negotiation is the art and science implies ensuring agreements between two or more independent parties, therefore, the purpose of this course is to develop skills that allow negotiating the implementation of such solutions (or its subsequent modification, in accordance with the situation diagnosis).

This course covers decision-making in negotiation processes and general dispute resolution. The course explains how the different decision-making techniques can be used in dispute resolution processes. Special emphasis is made on how the use of different rationalities can lead to different negotiation schemes. Throughout the course, the student designs and conducts a decision-making research in dispute resolution processes.

This course is part of a research project on social networks. The scope used to work in this research is the complex network theory. Attendees to this course are invited to actively participate in the research. The situations studied refer to the economic dynamics of the world system, to the development of urban spaces and to mechanisms of trust construction. The course pretends to present conditions that enable systemic setup relations among subjects, locations and countries. Those registered in the course may attend to the presentations of lecturers throughout the investigation, as well as to workshops, colloquium, seminars and other activities related and announced in advance.

Basic concepts of algorithms design and analysis. At the end of the course the student should be able to apply developing techniques like divide and conquer, dynamic programming, and general search algorithmic, analyzing temporal and spatial complexity. Practical limitations for algorithmic solutions (e.g. NP-completeness) are studied at an introductory level.

The course is a research seminar for addressing basic questions and issues on engineering, its difference with science,  engineering knowledge, methods & engineering ethics. and provides tools and heuristics for coping with the challlenges of developing and applying engineering in and for social (human) systems.

This course aims to build a solid understanding of social and organizational systems and their dynamics through the application of agent-based computational approaches. Several key aspects are presented in the course, such as the emergence of cooperation and conflict in organizations, socio-technical system design, problems of aggregation in social systems, and organizational adaptation.

In this course students develop skills and abilities in their capability to analyze, structure and solve problems of decision making under risk and uncertainty, taking into account one or multiple decision criteria. In particular, as a result of the course the student must be able to: 

1) Identify and structuring a strategic type in a company decision problem and designing a methodology to solve it, using decision models appropriate to do so. 

2) Identify situations in which can make use of some of the appropriate methodologies for analysis of decision under uncertainty, with an emphasis on the importance of using structured methodologies and tools appropriate to support rational decision making in organizations. 

3) Build models for the analysis of decisions that involve risk and uncertainty.

4) Usecomputational tools best known in the field of decision analysis, which should be applied in home works, and in the development of their final project of the course.

The Financial Risk Management course is an advanced finance course that assumes that students have had a minimum exposure to basic micro-economy and macro-economy concepts, particularly in those aspects pertaining to utility functions, risk aversion and financial market balance. On the other hand, concepts on the assumption of basic statistics, finance and mathematics tools knowledge, particular intensive work will be conducted with models and tools that imply a minimum knowledge of concepts, such as random variables, statistical moments of first and second order, linear regression and time series, as well as the basic calculus and lineal algebra concepts. The course approach is clearly quantitative, with respect to what is currently known as "finance in continuous time " however, discrete binomial tree models will also be intensively used. However, the course is not an stochastic calculus course in finance, and neither a derivatives course.

The student enrolled in this course delves into a topic of interest, that is relevant to their research project but that is not covered by any course offered by the Department or by other university programs.

The student enrolled in this course is developing an international research experience.

The student registered in this course dedicates an equivalent time to 4 CR to advance in his research topic.

The student registered in this course dedicates an equivalent time to 8 CR to advance in his research topic.

The student registered in this course dedicates an equivalent time to 12 CR to advance in his research topic.

The student registered in this course dedicates an equivalent time to 16 CR to advance in his research topic.