Course teachers: Biserka Runje, Amalija Horvatić Novak
Course objectives: Introducing students with contemporary settings, strategies, management systems and ways to ensure and improve quality in engineering. Student’s education for the practical application of tools and methods for quality control. Encourage students to express critical opinions based on scientific research.
Expected learning outcomes:
- To design and independently conduct testing procedures and quality management processes in the field of narrower specialisation.
- To apply acquired knowledge about the elements of the smart technical systems and processes, and their interactions throughout their entire life cycle.
- To design smart technical systems and processes in the area of functional specialisation and conduct prototyping and documentation.
Course teachers: Bojan Jerbić, Bojan Šekoranja, Filip Šuligoj, Marko Švaco
Course objectives: The aim of the course is to provide a basic understanding of the theory of biomimetic systems and humanoid robots and practical knowledge of locomotion system, perception of the environment, manipulation of objects and interaction between man and robot.
Expected learning outcomes:
After successfully mastering a course, students will be able to:
- Explain the principles of work and define concepts related to biomimetic robotic systems
- List the main features and classify humanoid robots
- Use the principles of teamwork and collaboration among teams in shaping technical solutions
- Use the knowledge acquired to develop technical solutions for solving the elementary problems in robotics
- Analyze and critically evaluate the performance of biomimetic and humanoid robots
Course teacher: Žmak Irena, Matijević Božidar
Course objectives: Becoming acquainted with the advanced engineering materials, their properties, applications and production methods.
Expected learning outcomes:
- To apply advanced knowledge in the field of natural and technical sciences to solve complex technical problems in the interdisciplinary context.
- To develop, prescribe and evaluate groups of materials and technologies in the field of narrower specialisation, given the requirements of the smart technical systems and the constraints that result from the quality and cost-effectiveness.
- To validate materials, technology and technical systems from business and social context and environmental concerns.
Course teachers: Prof. dr. sc. Joško Deur, Prof. dr. sc. Joško Petrić
Course objectives: The course deals with modelling and analysis techniques and energy management control principles for electric and hybrid vehicles. The course objective is to make students familiar with different electric and hybrid vehicle configurations, kinematic and dynamic powertrain models, power flow analysis techniques, control variable optimisation tools, control system design methods, and computer simulation verification tools. The consideration will be extended to e-mobility systems including smart charging techniques and vehicle-grid integration aspects.
Expected learning outcomes:
• To understand various concepts and configurations of electric and hybrid vehicles
• To develop mathematical and simulation models of hybrid vehicle powertrains
• To conduct power flow analyses for complex hybrid powertrains
• To acquire knowledge on hybrid powertrain control variable optimisation
• To design energy management strategies
• To use and adapt computer simulation tools for advanced vehicle powertrains
• To understand e-mobility systems including electric vehicle-grid integration aspects
Course teachers: Đukić Goran, Opetuk Tihomir
Course objectives: The goal of the course is to introduce students with the definition, objective, importance and key activities of logistics and Supply Chain Management, as well as with selected engineering logistics models, methods and tools for logistics systems/processes design and management. Presentation of concepts in automated storage and retrieval systems design and order picking system design within warehouses, providing guidelines for analysis and improvement of existing systems as well as design of new systems. Introducing students with computerized warehouse management systems (WMS) and application of modern identification and communication technologies in warehouses. Presentation of transportation management systems (TMS) and problems, focusing on vehicle routing problems (VRP) and solution algorithms. Presentation of discrete-event simulation (DES) theory and practice of practice of using commercial software tools for building simulation models of manufacturing and logistics systems.
Expected learning outcomes:
- To define logistics and supply chain management’s goals, importance, activities, similarities and differences.
- To identify, select and/or evaluate the systems and equipment of automated storage and retrieval systems and/or order-picking systems.
- To evaluate auto identification and communication technologies in logistics warehousing systems.
- To understand tasks of transportation management.
- To understand different types of transportation problems and to apply appropriate algorithms to solve them.
- To explain the basics of the Discrete Event Simulation (DES) and determine when this is a useful engineering tool.
- To create a simulation model and to run simulation experiment of a manufacturing or logistics system using a professional (commercial) DES software.