The School of Production Engineering and Management of the Technical University of Crete participates in the Erasmus+ Action KA1 Learning Mobility of Individuals.
All international students who are interesting in visiting the School through the Erasmus+ programme for studies and for traineeships, should carefully check and follow the procedure outlined by the Erasmus+ Programme Office of the Technical University of Crete.
The Erasmus+ academic coordinators are Assistant Professor Marios Kazasidis and Associate Professor Lefteris Doitsidis.
THE COURSES OFFERED TO INCOMING ERASMUS+ STUDENTS FOR THE ACADEMIC YEAR 2026-2027, ARE LISTED BELOW.
*** INCOMING STUDENTS MAY ONLY SELECT COURSES FROM THIS LIST ***
Fall semester courses
| Course | ECTS | Instructor |
|---|---|---|
| Mechanical Drawing (ΜΗΧ 101) | 5 | A. Antoniadis |
| Introduction to Mechanical Drawing. Basic rules. Views and sections. Dimensioning. Drawing of threads, screws, rivets, gears, cams, bearings, seals and other machine elements. Drawing of welds. Intersections and developments. Indication of Machining processes. Indication of dimensional and geometrical tolerances. 3D drawing. | ||
| Teaching: Projects, Evaluation: Exams | ||
| Mechanics – Strength of Materials (ΜΗΧ 201) | 5 | G. Stavroulakis |
| Internal forces, stresses. Strains. Stress-strain relationship. Statically indeterminate problems. Temperature effects. Shear deformation. Stress and strain distribution. Torsion. Pure bending. Asymmetric bending. Transverse loading. Transformation of stress and strain. Stresses under combined loading. Mohr’s circle. Stresses and deflections in beams. Energy methods. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Science and Technology of Materials (ΜΠΔ 202) | 4 | M. Konsolakis |
| Atomic and Molecular Structure. Structure of Crystalline Solids. Structure-Properties relationships. Mechanical Properties of Metals. Metal Alloys. Dislocations and Strengthening Mechanisms. Failure. Imperfections in Solids. Diffusion. Phase diagrams. Optical-Thermal-Electrical-Magnetic Properties. Physicochemical Characterization of Materials. Materials for Energy and Environmental Applications. | ||
| Teaching: Projects, Evaluation: Exams & Projects | ||
| Environmental Analysis and Planning (ΜΠΔ 208) | 4 | S. Papaefthimiou |
| Humanity and the environment. Concepts and principles of ecology. Environmental ethics and legislation. Environment and sustainable development. Environmental problems: global warming and climate change, stratospheric ozone depletion, acid rain, urban smog, ecosystems' destruction. Environmental Management Systems. Life Cycle Analysis. Environmental - ecological footprint. Ecological and energy labelling. European legislation and international standards and regulations on environmental and energy management and planning issues. | ||
| Teaching: Projects, Evaluation: Projects | ||
| Stochastic Processes (ΜΠΔ 303) | 5 | V. Kouikoglou |
| Introduction. Definition of stochastic processes, probability, distribution and probability density functions, correlation, moments, mean square calculus, independence, stationary processes. Wiener process. White noise. Random walk. Poisson process. Linear systems with stochastic inputs. Ergodicity. Markov chains. Introduction to information theory. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Corporate Innovation and Digital Transformation (ΜΠΔ 222) | 5 | A. Kostis |
| TBA | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Combinatorial Optimization (ΜΠΔ 426) | 5 | Υ. Marinakis |
| Mathematical models and applications of combinatorial optimization. Differences between linear and integer programming. Graphs and networks. Data structures for graphs and networks. Graph search. Shortest paths and discrete dynamic programming. Minimal spanning trees and greedy algorithms. Flow problems. Problem and algorithm complexity. Linear and Lagrangian relaxation. The branch-and-bound method. Local search. Heuristic and meta-heuristic algorithms. Approximation algorithms. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Electronic Business (ΜΠΔ 230) | 4 | P. Fafalios |
| Introduction to e-Business and e-Commerce: brief history, Intranet/Extranet/Internet, World Wide Web, mobility platform, basic types of e-commerce, main trends. Business models and related concepts: categories of business models, capital raising, pricing strategies, payment systems, impact on industry and business. Digital marketing and advertising: consumer profiling, consumer behavior, search engine marketing, display ads marketing, email marketing, social marketing, other digital marketing strategies (collaborative, viral, flash, personal, location-based), web analytics. Internet technology: history, technological components (IP, TCP/IP, HTTP, packet switching, network infrastructure, domain names, DNS, URLs, client-server model). Developing an e-commerce presence: website construction and hosting, hardware selection, design principles, presence on mobile devices. Web Technologies: Introduction to HTML, Introduction to CSS, Bootstrap Framework. The online security environment (cybersecurity): threats, solutions, cryptography, protection of communication channels, protection of servers and clients, management policies, laws. Ethical issues, privacy, intellectual property, governance. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Structural Dynamics, Vibrations and Control (ΜΠΔ 432) | 4 | G. Stavroulakis, P. Alevras |
| Single-degree-of-freedom linear oscillator: free vibration response, eigenfrequency, damping, forced vibration. Multiple-degree-of-freedom systems: simulation, eigenmodes, eigenfrequencies, eigenvalue analysis. Analytical dynamics: generalized coordinates, kinematic constraints, virtual work, Langrage equation, Hamilton equation. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Quality Control (ΜΠΔ 405) | 5 | Ch. Diakaki |
| Introduction to quality and quality improvement methods. Concept and techniques for quality control. Basic categories of statistical quality control. Introduction to statistics. Acceptance sampling. Single, double and multiple sampling plans. Sequential sampling plans. Other acceptance sampling techniques. Introduction to statistical process control and control charts. Control charts for variables and attributes. Other statistical process quality control techniques. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Marketing (ΜΠΔ 406) | 5 | S. Tsafarakis |
| Marketing: definition, marketing environment. Development of a competitive advantage in marketing. Marketing strategies. Market research. Market segmentation. Consumers, factors affecting consumer behavior. Lifecycle of products. Functions to express product lifecycle. Sales forecasting. Product policy and strategy. Adoption and distribution of new products. Pricing and distribution policy. Product promotion, advertising, personalized sales. Management in marketing. | ||
| Teaching: Lectures, Evaluation: Exams | ||
| Environmental Science and Technology (ΜΠΔ 504) | 4 | S. Papaefthimiou |
| Environmental pollution: air, water, soil, biosphere. Technology, industry, and environment. Air pollution: sources and impacts. Air emissions control technologies. Technologies for removal particulate matter. Wastewater treatment technologies. Management and energy utilization of solid waste. | ||
| Teaching: Projects, Evaluation: Projects | ||
| Project and Production Management and Scheduling (ΜΠΔ 409) | 5 | I. Papamichail |
| Introduction to project management and scheduling. Mathematical tools. Optimal time-scheduling with and without constraints. Resource allocation scheduling, time-cost relationship. Taxonomy of production systems. Production Process Selection and Scheduling. Layout planning, layout algorithms. CPM, PERT methods. Production line balancing. Main production planning. Material requirements planning. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Design and Optimization in Supply Chain Management (ΜΠΔ 514) | 5 | Υ. Marinakis |
| Role of supply chain management. Planning demand and supply in a supply chain. Applications and mathematical modeling. Algorithmic complexity. Traveling salesman problem, bin packing problem. Transportation and distribution of products in supply chain. Network design problem. Distribution channels. Route selection. Fleet-size problems. Vehicle-routing problem. Variants of the vehicle-routing problem (time windows, multicommodity, dial-a-ride, pickup and delivery problems). Vehicle scheduling problem. Ship routing problem. Inventory routing problem: single-period inventory routing problem, multi-period inventory routing problem, infinite horizon inventory routing problem. Location problems. Covering problems. P-center and P-median problems. Capacitated and uncapacitated facility problems. Location routing problem. Integrated logistics. E-Supply chain management. Case studies (modeling, development, and solution methodologies). | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Financial Engineering (ΜΠΔ 427) | 5 | M. Doumpos |
| Introduction to financial markets. Financial risk management. Portfolio management theory. Portfolio optimization models. Fixed income securities. Valuation models. Risk management for fixed income securities (credit risk, country risk, interest rate risk). Financial derivatives. Options and valuation models. Forwards and futures. Hedging strategies with derivatives. Value-at-risk. | ||
| Teaching: Lectures, Evaluation: Projects | ||
| Additive Manufacturing (ΜΠΔ 521) | 5 | M. Kazasidis |
| Introduction to additive manufacturing, classification of engineering materials (polymers, ceramics, composites, biomaterials) and their principal properties-applications. Additive manufacturing techniques of metallic materials (SLM, SLS, DED, WAAM), microstructure and mechanical properties. Additive manufacturing of polymers (FFF, FDM, SLA) and ceramics (LBCP). Additive manufacturing of composite materials and biomaterials. Design for additive manufacturing, optimization of the 3D model and rapid prototyping. Parameters of additive manufacturing, optimization and new research fields, effect on the product quality. Investigation of additive manufactured parts: surface, mechanical, physical and chemical properties. 3D printing and 3D scanning. Application of additive manufacturing on the fabrication of metastructures and multimaterials. Financial aspects of additive manufacturing. Hybrid manufacturing. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Computational Dynamics of Mechanical Systems (ΜΠΔ 522) | 5 | P. Alevras |
| Approximate modal analysis using appropriate commercial finite element software. Galerkin reduction, method of assumed mode shapes. Numerical integration of the equations of motion for complex mechanical systems using mathematical modelling software. Numerical determination of periodic responses (collocation method, harmonic balance method). Local and global bifurcations. Free and forced nonlinear vibrations, stability of steady-state solutions, existence and stability of periodic solutions. Self-excited oscillations. Parametric resonance. Continuation method for periodic solutions. Identification of dynamic characteristics of existing systems and components. Basic methods and description of equipment for experimental vibration analysis of mechanical systems. The syllabus and theory are organized around the following applications with concurrent training in modern computational analysis tools: Determination of the dynamic behaviour of vehicle components and other complex mechanical systems. Dynamic response determination of electromechanical systems and vibration energy harvesters. Vibration suppression of machines with vibration absorbers. Dynamic power transmission with geartrains. Machining vibrations (chatter) and CNC machining centres, aeroelastic vibrations of blades and structures. Vibrations of machines with rotating parts and rotating blades. Mechanical vibrations of Micro-Electro-Mechanical Systems (MEMS). | ||
| Teaching: Projects, Evaluation: Projects | ||
| Composite & Smart Materials & Structures (ΜΠΔ 520) | 5 | G. Stavroulakis, P. Alevras |
| The course provides knowledge relevant to the design and manufacturing technology of composite amd smart materials and structures using classical and additive manufacturing. Production technology and applications. Composite materials, homogenization theory, and elements of anisotropic elasticity. Fiber-reinforced composites (CFRP) and materials with functionally graded properties (Functionally Graded Materials). Classical theories of laminated materials/structures, computational methods using finite elements (as a continuation of the computational mechanics course and advanced discussion of shell structures). Smart materials / metamaterials / intelligent structures, smart materials due to microstructure and geometry or due to the integration of multi-physics elements (piezoelectric, microelectronic, and other related elements). Smart materials with mechanical logic gates. | ||
| Teaching: Projects, Evaluation: Projects | ||
Spring semester courses
| Course | ECTS | Instructor |
|---|---|---|
| Engineering Statistics (ΜΠΔ 228) | 6 | Ch. Diakaki |
| Introduction. Basic concepts. Time-series analysis. Regression analysis. Principal component analysis. Simple and multiple correspondence analysis. Factor analysis. Discriminant analysis. Cluster analysis. Q-analysis. Conjoint analysis. Hierarchical analysis. Forecasting techniques. Technology forecasting. Applications and case studies. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Machine Elements (ΜΠΔ 305) | 6 | P. Alevras |
| Introduction to Mechanical Design. Strength of materials. Criteria of static failure. Fatigue and failure criteria under dynamic loading. Shafts, failure analyses under static and dynamic loads. Manufacturing materials. Spur, helical, bevel gears and planetary systems. Gear tooth bending failure and tooth surface pitting. Mechanical power transmission with geartrains. Mechanical power transmission with elastic components. Screws and fasteners. Welds. Ball bearings and selection. Computational methods. Miscellaneous mechanical components. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Political Economy (ΚΕΠ 102) | 4 | K. Tsagarakis |
| Includes an analysis of basic notional categories and relations in political economy, as well as a brief review of recent economic history. Particular references are made to: the theory of valuation, surplus value, pricing, the relationship between competition and distribution, the fundamental trends and incongruities of amplification, and financial crisis phenomena. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Game Theory (ΜΠΔ 407) | 4 | Y. Marinakis |
| Introduction, Games with two players. Zero-sum games. Pure and mixed strategies. Matrix and bi-matrix games. Equilibria and saddle points. Minmax theorem. Solution of matrix games using linear programming. Solution of Bi-matrix Games using nonlinear programming. Nash equilibriums and Pareto points. Hierarchical games. Stackelberg equilibria and disequilibria. Bi-level programming. Application to microeconomics: Cournot duopoly. Application to traffic planning: traffic assignment problem. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Introduction to Artificial Intelligence (ΜΠΔ 306) | 4 | S. Tsafarakis |
| Introduction to Artificial Intelligence. Problem Solving. Knowledge Representation and Reasoning. Uncertainty and Fuzzy Knowledge. Planning. Expert Systems. Machine Learning. Rough Sets. Neural Nets. Evolutionary and Genetic Algorithms. Fuzzy Sets. Data Mining. Intelligent communication methods (natural language processing, vision, robotics). Agents: intelligent agents, multi-agent systems, applications. | ||
| Teaching: Lectures, Evaluation: Exams | ||
| Data Analysis (ΜΠΔ 323) | 4 | G. Atsalakis |
| Introduction. Basic concepts. Time-series analysis. Regression analysis. Principal component analysis. Simple and multiple correspondence analysis. Factor analysis. Discriminant analysis. Cluster analysis. Q-analysis. Conjoint analysis. Hierarchical analysis. Forecasting techniques. Technology forecasting. Applications and case studies. | ||
| Teaching: Projects, Evaluation: Projects | ||
| Human Resource Management (ΜΠΔ 302) | 4 | A. Kostis |
| TBA | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Renewable Energy Sources (ΜΠΔ 516) | 4 | S. Papaefthimiou |
| Introduction and general definitions. Forms of energy and energy needs. Solar energy: photothermal, photoelectric and passive solar systems. Wind energy: key characteristics of wind - wind turbine technology. Biomass - Biofuels. Geothermal energy. Hydraulic power and hydropower plants. Ocean and tidal wave energy. Principles of energy saving and energy efficiency. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Decision Support Systems (ΜΠΔ 324) | 4 | E. Siskos |
| Introduction to information systems and information technology. Data, information, knowledge. Decision making and decision theory. Decision making under risk and uncertainty. Multi-criteria decision analysis. Outranking and functional multicriteria decision models. ELECTRE I and II, PROMETHEE I and II methods. Criteria importance elicitation and calculation methods. The linear and additive value function. Group decision making and negotiations. Decision Support Systems (DSS). Architecture of a DSS. Human-computer interaction systems. Database management systems. Model database management systems. Intelligent DSS. Applications of DSS in energy, administration, production, environment, etc. Case studies. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Computer-Aided Design (CAD) (ΜΠΔ 423) | 5 | M. Kazasidis |
| CAD, Definition and Applications, Product Development and CAD, Solidworks system, 3D models (wireframe, surface, solid models), Parametric solid modelling, Constructive Solid Geometry (C-rep) Assembly, Assembly methodology (top-down, bottom up), Additive manufacturing, Reverse Engineering, Freeform curves (Bezier, Ferguson, B-Splines, NURBS). | ||
| Teaching: Projects, Evaluation: Projects | ||
| Mechatronics (ΜΠΔ 431) | 4 | E. Doitsidis |
| Introduction and examples. Simulation of engineering systems. System dynamics and oscillations. Types and simulation of sensors and actuators. Processing of measurement data. Intelligent control (hierarchical control, hybrid control, fuzzy, neural and fuzzy-neural control). Dynamical system diagnostics. Applications. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Control Systems II (ΜΠΔ 430) | 4 | D. Ipsakis |
| Advanced Single Input - Single Output Control Design / Synthesis: Feedback Control, Feedforward Control, Feedforward/Feedback Control, Cascade Control. Introduction to multivariable control systems: State-space models, Linearization of Differential/Algebraic Equations, Controllability, Observability, Stability. Multivariable Control: Pole placement, State-Feedback control, LQR Control, State-Observer. Introduction to Optimal Control. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Strategic Management (ΜΠΔ 506) | 4 | A. Kostis |
| TBA | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||
| Business Intelligence, Analytics and Big Data Analysis (ΜΠΔ 518) | 4 | P. Fafalios |
| Business Intelligence, Customer Intelligence, Cloud Business Intelligence, Mobile Business Intelligence. Business Analytics. Data Science, Big Data, Big Data analytics technologies, distributed systems, MapReduce, Apache Hadoop, relational and non-relational (NoSQL) databases, Cloud Computing, big data and business. Decisions, decision support systems, decision making process, decision making under uncertainty and risk, decision trees. Data, information, knowledge, understanding, wisdom. Knowledge management. Data Warehouses. Online Analytical Processing (OLAP) systems. Data Mining and Machine Learning, models of knowledge discovery processes, Machine Learning paradigms, categories of Machine Learning problems, limitations and issues of Machine Learning. Data preprocessing: quality, integration, cleaning, completion, smoothing, inconsistency resolution, redundancy removal, data reduction, dimensionality reduction, numerosity reduction, data normalization. Classification: decision trees, classification algorithms, evaluation. Clustering: clustering algorithms, hierarchical algorithms, partitioning algorithms, density-based algorithms, quality measurement. | ||
| Teaching: Lectures & projects, Evaluation: Exams & projects | ||
| Computational Mechanics (ΜΠΔ 515) | 4 | G. Stavroulakis |
| Numerical methods in structural mechanics: classical methods Rayleigh, Ritz, Galerkin, finite differences and finite elements. The finite element method: equilibrium conditions, compatibility material constitutive law, Discretization, stiffness and mass matrix, matrix assembly, solution, post processing of data. Variational principles, detailed study of finite elements for rods, beams and two-dimensional linear elasticity problems, technology of finite element programs. Related applications to heat transfer and fluid mechanics problems. Application examples using existing software. | ||
| Teaching: Lectures & projects, Evaluation: Projects | ||