Objectives and competences
- To gain a comprehensive understanding of computer-aided technologies (CAD–CAE–CAM–CAQ) and their role in digital product development.
- To understand the relationships between modelling, simulation and manufacturing, as well as data flow throughout the product lifecycle.
- To use CAD, CAE, CAM and CAQ tools for modelling, analysis and planning of manufacturing processes.
- To develop the ability to analyse and optimize manufacturing and engineering systems using simulations, optimization methods and artificial intelligence.
- To apply CAX approaches to solve real-world engineering problems and support informed decision-making.
Competences:
- System thinking: understanding the integration of CAD–CAE–CAM–CAQ and the digital product lifecycle.
- Problem solving: ability to model, simulate and optimize engineering systems.
- Data analysis: ability to interpret simulation and experimental results.
- Technical skills: ability to use modern CAx tools and digital engineering approaches.
- Critical evaluation: ability to validate models and assess results.
- Communication: ability to clearly present technical solutions and results.
- Collaboration and independence: ability to work effectively in teams and independently.
- Creativity: ability to develop innovative solutions using digital technologies and artificial intelligence.
Content (Syllabus outline)
Overview of computer-aided technologies (CAX) and their role in digital product development:
- introduction to CAX, digital twin and product lifecycle;
- CAD: 2D and 3D modelling, surface and solid modelling, parametric and feature-based modelling, assembly modelling, geometry management, and preparation of models for analysis and manufacturing;
- CAE: numerical simulations (FEA, CFD, DEM, MBD), analysis of stresses, deformations, flows and contacts, interpretation of results, and model validation and verification;
- CAM: process planning, CNC machining, generation, optimization and verification of toolpaths, simulation of machining processes, and manufacturability analysis;
- CAQ: quality planning and assurance, measurement procedures, statistical process control (SPC), quality analysis, and integration of quality control into the digital manufacturing process;
- integration of CAD–CAE–CAM–CAQ, digital manufacturing, integration of information systems (CAPP, CIM, MES, ERP, PLM), data management and exchange, interoperability, and concepts of Industry 4.0 and digital engineering;
- optimization methods and artificial intelligence in engineering for decision support, modelling, data analysis, model identification, and optimization of manufacturing and engineering systems;
application examples in manufacturing and assembly processes, including modelling, simulation, optimization and implementation of solutions, and project work on real engineering problems.
Learning and teaching methods
- lectures
- individual research work
- seminar
- laboratory exercises
Intended learning outcomes - knowledge and understanding
- Identify and explain the role of computer-aided technologies (CAD–CAE–CAM–CAQ) in digital product development.
- Select and apply appropriate CAD, CAE, CAM and CAQ tools for modelling, simulation, planning and verification of manufacturing processes.
- Prepare, integrate and manage models and data across different stages of the digital product lifecycle.
- Analyse and interpret simulation, measurement and manufacturing results to improve products and processes.
- Evaluate the suitability of applied models, methods and tools for real-world engineering problems.
- Design and optimize manufacturing and engineering systems using simulations, optimization methods and artificial intelligence.
Readings
1. Vajna, S., Weber, C., Bley, H., & Zeman, K. (2009). CAx für Ingenieure (2. völl. neu bearb. Aufl., str. XII, 550 str.) [Book]. Springer. https://doi.org/10.1007/978-3-540-36039-1 Gotlih, J., & Ficko, M. (2025). Optimizacije v inženirstvu [eBook]. V reševanje problemov z metahevrističnimi metodami v okolju MATLAB (1. izd.). Univerza v Mariboru, Univerzitetna založba. https://plus.cobiss.net/cobiss/si/en/data/cobib/256635651
2. Gotlih, J., & Brezočnik, M. (2025). Strojno učenje za inženirje [eBook]. V koncepti, primeri in uporaba v okolju MATLAB (1. izd.). Univerza v Mariboru, Univerzitetna založba. https://plus.cobiss.net/cobiss/si/en/data/cobib/256145411
1. Karner, T., & Gotlih, J. (2022). Programiranje industrijskih robotov (1. izd.). Univerzitetna založba. https://press.um.si/index.php/ump/catalog/book/652
Prerequisits
- The student knows the basics of CAD and 3D modelling and understands manufacturing processes and materials.
- The student applies basic knowledge of mathematics, mechanics, and engineering software tools to solve engineering tasks.
- The student analyses simple problems and participates in independent and teamwork.
