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EDAM | Doctoral Program | Fall Semester

Course Listing

Below are the courses offered in the LTI program fall semester:

EDAM Curricula Units - Fall Semester

Course	Product Design and Development
Status	Compulsory
Program	An overview of development processes and organizations Product planning Identifying customer needs Product specifications Concept generation Concept selection Concept testing Product architecture Industrial design Robust design Design for Manufacturing Prototyping Product development economics Managing product development projects
Learning Outcomes	Competence with a set of tools and methods for product design and development required to facilitate interdisciplinary problem solving and decision making Gaining confidence in ones abilities to create and assure the industrialization of a new product. Awareness of the role of multiple functions in creating a new product (e.g. marketing, finance, industrial design, engineering, production). Students will be led through the design process and connect the theory to applications. Students will learn real-world examples of today's design and manufacturing environments. Ability to coordinate multiple, interdisciplinary tasks in order to achieve a common objective.

Course	Technology Evaluation and Selection
Status	Compulsory
Program	Materials data and selection criteria (performance, manufacturing, socio-environmental, economical) Materials and process selection screening (e.g. Ashby plots) Interrelationships between properties and manufacturing/processing technology Preliminary FEA calculations and prototyping to decide on material and/or technology Decision Analysis Multi-attribute utility analysis Dynamic strategic planning Production and cost functions Investment appraisal techniques of engineering projects Life cycle assessment
Learning Outcomes	Competence to make use of methodologies and tools to select and evaluate materials and manufacturing technologies Capability to use an integrated approach of systems analysis and applied economics for selecting and evaluating technological projects

Course	Operations Research
Status	Optional
Program	Decision processes in organizations. General modeling principles and issues. Decision Support Systems: structure and components; design and implementation issues. Decision Analysis: uncertainty and risk; decision trees. Multi-criteria Decision Making. Introduction to mathematical modeling, optimization, and simulation, as applied to manufacturing. Linear programming and extensions, network flow problems, Graph Theory. Combinatorial Optimization: models and applications for manufacturing processes and systems. Heuristic techniques: design principles and implementation issues. Discrete-event simulation: models and applications. Visual interactive simulation.
Learning Outcomes	To develop or modeling skills for the implementation and solution of real problems.

Course	Applied Statistics
Status	Optional
Program	Exploratory Data Analysis: transforming data; resistant lines; analysis of residuals; location estimators Nonparametric Statistics: rank based methods; Kolmogorov Smirnov goodness of fit tests Regression: simple linear regression; Matrix Approach to Simple Linear Regression; Multiple Linear Regression; Nonlinear Regression and Correlation Analysis Design of Experiments: Single Factor Experiments; Factorial Designs; 2k Factorial Design; Analysis of Covariance; Graeco Latin Square Designs; Response Surface Methods Statistical Methods in Quality Control; Control Charts for Variables; Control Charts for Attributes; Process and Measurement System Capability
Learning Outcomes	Competence in understanding exploratory data analysis, regression modeling, design and analysis of experiments and statistical process control

Course	Computational Methods
Status	Optional
Program	Generalized eigen values problem for symmetrical matrices. Over-determined systems of linear equations Iterative methods to solve linear system of equations Solutions methods for non-linear system of equations Optimization Optimality conditions Optimization algorithms Multi-objective optimization Distributed optimization
Learning Outcomes	Capability to use computational methods to solve eigen value problems, non-linear systems of equations, classical and evolutionary optimization for large scale systems. Competence in program development and educated use of commercial programs.

Course	Production Information Systems
Status	Optional
Program	Fundamentals Production Planning and Control (PPC) main functional units Different Production paradigms, goals and applications: Conventional PPC, Mass Customization Production Systems, and Customer Oriented Production Systems The relationship among: Production paradigms, Product Data Management, Product Structure Management, and other Production Information Systems Functional Units Database management systems: Specification, design, implementation and use of a database system. Conceptual models: entity-relationship model, class model. Relational model. Relational algebra. Query languages. SQL Product Data Management (PDM) Fundamentals on: Products, Operations, Families, Parameters and variants Product Identification and characterization Bill of Materials, Routings and resources PDM representation models: Conventional Models, Multiple Bill of Materials and Generic Models PDM representation models comparison, evaluation and contextualization Requirement definition for PDM Case Studies IS requirements definition and PDM structuring for: Master Production Scheduling, Material and Capacity Requirement Planning Production Activity Control: Purchasing, Order Release, Production Scheduling and Monitoring Inventory Control, Distribution Requirement Planning, Product Costing, Sales and Marketing Application Examples
Learning Outcomes	Competencies for: identifying main PPC functional units / alternative methods that can be used to implement each PPC functional unit understanding their implications within organizational procedures specifying IS requirements that support PPC functional units selecting and use PPC software systems designing, implementing and querying relational databases and data warehouses

Course	Processing of Polymers and Composites
Status	Optional
Program	Thermo mechanical and rheological fundamentals of polymer processing Non-conventional processes and advanced technologies for thermoplastics processing Processing technologies for composite structures Special manufacturing processes, including micro-machining, micro-assembly and hybrid techniques. Engineering aspects of tool design and manufacturing Advanced process monitoring Process modeling in polymers and composites processing
Learning Outcomes	Comprehensive understanding of the processing techniques for polymers and polymer-based composites, focusing on advanced polymeric systems and complex part geometries Insight in emerging non-conventional techniques Understanding of the critical factors involved in tool and part design to assure efficient and robust manufacturing processes Familiarization with CAE and monitoring tools in polymer processing

Course	Advanced Metal Fabrication
Status	Optional
Program	Plasticity and viscoplasticity Formability Friction, wear and lubrication Numerical modeling of manufacturing processes Experimental procedures applied to manufacturing processes Advanced issues in metal forming, blanking and metal cutting processes.
Learning Outcomes	Consolidated understanding of plasticity, viscoplasticity, formability, damage, friction, wear and lubrication applied to the mechanical processing of materials (metal forming, shearing/blanking and metal cutting). General knowledge on the utilization of computer programs for the numerical simulation of manufacturing processes as well as a good understanding on the experimental techniques that can be used for obtaining data under laboratory and industrial controlled conditions. Insight on several mechanical processing technologies that are not introduced during the master course of mechanical engineering.