Automotive Production Engineering & Artificial Intelligence

<p>This module covers modern manufacturing technologies such as additive manufacturing, laser technology, and fiber-reinforced plastics. In addition, Python is used to generate CNC machine tool data for simulation purposes in predictive maintenance.</p> <p>Software used:​</p> <ul><li>AI-assisted programming with Python &amp; Power Automate</li></ul>

<p>This module covers the fundamentals of artificial intelligence and data science, as well as key application areas such as conversational and generative AI. It also addresses automated machine learning, business applications, and ethical and legal considerations.</p> <p>Software used:</p> <ul><li>AI application development platforms (e.g., IBM Watsonx portfolio)</li><li>General-purpose AI (e.g., ChatGPT, Claude, Gemini)</li></ul>

<p>This module promotes independent and methodical academic work on current topics in production and digitization. Students work in small groups of two to three.</p> <p>Software used:</p> <ul><li>Select any digital technology or software for evaluation</li></ul>

<p>This module provides an introduction to artificial intelligence and an overview of software applications in industry. It focuses on the evaluation of digital technologies and the practical implementation of automation solutions using low-code and RPA.</p> <p>Software used for practical projects:</p> <ul><li>Make or</li><li>Power Automate or</li><li>UiPath or</li><li>N8N</li></ul>

<p>This module covers the fundamentals of production systems, process-oriented approaches, and lean manufacturing. It also addresses machine tools, capacity planning, and methods such as MTM and REFA, as well as Design for Manufacturing and Assembly.</p> <p>Software used:</p> <ul><li>Halocline VR Planning, Assistant</li></ul>

<p>This module delves into machine learning approaches, including classical and deep learning methods, and covers the data science workflow. It also addresses the customization of large language models (LLMs), such as through retrieval-augmented generation, as well as the development and prototyping of use cases. Additionally, the module distinguishes between predictive and causal data analysis.</p> <p>Software used:</p> <ul><li>Anaconda, Python, Jupyter Notebook, ML libraries (e.g., scikit-learn, TensorFlow, Keras) ​</li><li>Coding assistants​</li><li>AI Application Development Platforms</li></ul>

<p>This module covers fundamentals of automation and equipment engineering, including PLC programming in industrial manufacturing, an overview of robotics applications, robot types and kinematics, and basics of vectors and matrices. It also addresses robot programming methods (online/offline) and fundamentals of robotic perception, including CNN-based visual data processing.</p> <p>Software used:</p> <ul><li>Automation Software Automation: Siemens TIA Portal, Factory IO</li><li>Robot Software: Polyscope (Universal Robots), Phyton</li><li>Robot Control: KUKA KRC4</li></ul>

<p>This module covers the fundamentals of big data as well as various data types and structures. Topics include relational and NoSQL database systems, optimized storage formats, distributed file systems, and computing frameworks.</p> <p>Software used:</p> <ul><li>SQL, Python​</li><li>Databases (e.g., Postgres)​</li><li>Orchestration tools (e.g., AirFlow)​</li><li>Containerization (e.g., Docker)</li></ul>

<p>This module addresses engineering processes in the automotive industry, including product and process development, requirements and quality management methods, and pre-series processes and systems engineering. It also covers modeling with SysML and SPICE for assessing process capability, maturity levels, and performance indicators.</p> <p>Software used:</p> <ul><li>Engineering: Cameo or CATIA Magic</li><li>SPICE: Polarion, DOORS, Tessy, etc.</li></ul>

<p>The master's thesis teaches students how to conduct independent academic research, from defining the problem and conducting research to selecting methods, analyzing data, and presenting results. The focus is on a systematic approach, logical reasoning, and goal-oriented work.</p> <p>Software used:</p> <ul><li>Select any digital technology or software for evaluation or application</li></ul>

<p>This module covers modern manufacturing technologies such as additive manufacturing, laser technology, and fiber-reinforced plastics. In addition, Python is used to generate CNC machine tool data for simulation purposes in predictive maintenance.</p> <p>Software used:​</p> <ul><li>AI-assisted programming with Python &amp; Power Automate</li></ul>

<p>This module covers the fundamentals of artificial intelligence and data science, as well as key application areas such as conversational and generative AI. It also addresses automated machine learning, business applications, and ethical and legal considerations.</p> <p>Software used:</p> <ul><li>AI application development platforms (e.g., IBM Watsonx portfolio)</li><li>General-purpose AI (e.g., ChatGPT, Claude, Gemini)</li></ul>

<p>This module promotes independent and methodical academic work on current topics in production and digitization. Students work in small groups of two to three.</p> <p>Software used:</p> <ul><li>Select any digital technology or software for evaluation</li></ul>

<p>This module provides an introduction to artificial intelligence and an overview of software applications in industry. It focuses on the evaluation of digital technologies and the practical implementation of automation solutions using low-code and RPA.</p> <p>Software used for practical projects:</p> <ul><li>Make or</li><li>Power Automate or</li><li>UiPath or</li><li>N8N</li></ul>

<p>This module covers the fundamentals of production systems, process-oriented approaches, and lean manufacturing. It also addresses machine tools, capacity planning, and methods such as MTM and REFA, as well as Design for Manufacturing and Assembly.</p> <p>Software used:</p> <ul><li>Halocline VR Planning, Assistant</li></ul>

<p>This module delves into machine learning approaches, including classical and deep learning methods, and covers the data science workflow. It also addresses the customization of large language models (LLMs), such as through retrieval-augmented generation, as well as the development and prototyping of use cases. Additionally, the module distinguishes between predictive and causal data analysis.</p> <p>Software used:</p> <ul><li>Anaconda, Python, Jupyter Notebook, ML libraries (e.g., scikit-learn, TensorFlow, Keras) ​</li><li>Coding assistants​</li><li>AI Application Development Platforms</li></ul>

<p>This module covers fundamentals of automation and equipment engineering, including PLC programming in industrial manufacturing, an overview of robotics applications, robot types and kinematics, and basics of vectors and matrices. It also addresses robot programming methods (online/offline) and fundamentals of robotic perception, including CNN-based visual data processing.</p> <p>Software used:</p> <ul><li>Automation Software Automation: Siemens TIA Portal, Factory IO</li><li>Robot Software: Polyscope (Universal Robots), Phyton</li><li>Robot Control: KUKA KRC4</li></ul>

<p>This module covers the fundamentals of big data as well as various data types and structures. Topics include relational and NoSQL database systems, optimized storage formats, distributed file systems, and computing frameworks.</p> <p>Software used:</p> <ul><li>SQL, Python​</li><li>Databases (e.g., Postgres)​</li><li>Orchestration tools (e.g., AirFlow)​</li><li>Containerization (e.g., Docker)</li></ul>

<p>This module addresses engineering processes in the automotive industry, including product and process development, requirements and quality management methods, and pre-series processes and systems engineering. It also covers modeling with SysML and SPICE for assessing process capability, maturity levels, and performance indicators.</p> <p>Software used:</p> <ul><li>Engineering: Cameo or CATIA Magic</li><li>SPICE: Polarion, DOORS, Tessy, etc.</li></ul>

<p>The master's thesis teaches students how to conduct independent academic research, from defining the problem and conducting research to selecting methods, analyzing data, and presenting results. The focus is on a systematic approach, logical reasoning, and goal-oriented work.</p> <p>Software used:</p> <ul><li>Select any digital technology or software for evaluation or application</li></ul>