FAIL-SAFE DESIGN CONCEPTS

In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.

This course makes you acquainted with the concept of systems-of-systems (SoS), which means that independent systems are collaborating. It gives you an understanding why SoS is an important topic in the current digitalisation and provides a theoretical and practical foundation for understanding important characteristics of SoS. It also gives you a deeper knowledge in a number of key concerns that need to be considered when engineering SoS. Admitted students may join the course any time between September 2 and October 6, 2024. With the recommended study pace of 25%, the course would take approximate seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than January 19, 2025.

The purpose is to give the students an overview of issues and methods for development and assurance of safety-critical software, including details of selected technologies, methods and tools. The course includes four modules: Introduction to functional safety; knowledge that give increased understanding of the relationship between Embedded systems / safety-critical system / accidents / complexity / development models (development lifecycle models) / certification / “the safety case”. Analysis and modelling methods; review of analysis and modelling techniques for the development of safety-critical systems. Verification and validation of safety critical software, methods and activities to perform verification and validation. Architectures for safety critical systems. Safety as a design constraint.  

The course on Large Language Models for Industry is designed to cater to the demands of industries amidst the global push for sustainability and green transitions. Large Language Models (LLMs) represent a pivotal technology thatcan revolutionize how industries operate, communicate, and innovate. In this course, participants explore the intricate mechanics and practical applications of LLMs within industry contexts. The course covers the principles and technologies spanning from traditional Natural Language Processing (NLP) to Natural Language Understanding (NLU), enabled through the development of LLMs. Emphasizing industry-specific challenges and opportunities, participants learn to utilize LLMs while considering sustainability concerns. Participants gain valuable insights from adapting LLMs to tackle real-world problems through examples and exercises tailored to industry needs. By the course completion,participants are equipped to leverage LLMs as transformative tools for driving industry innovation and, at the same time, advancing sustainability goals. Three online meetings. Dates TBD – Starting mid November.

In the era of shift towards green transition, industries face unique challenges and generates numerous opportunities. This course, "Intelligent Asset Management and Industrial AI" is designed to equip professionals with the knowledge and tools necessary to support advanced technologies in achieving environmental sustainability. Industries play a major role in contributing to the global economy that is accompanied with a significant share towards environmental degradation. The growing climatic concerns and degradation of natural resources has urged the need to reduce carbon footprints, minimize waste, and optimize resource utilization such that a green transition is achieved. Intelligent Asset Management and Industrial AI are at the forefront of this transformation offering innovative solutions to enhance operational efficiency, reduce environmental impact and support the industry’s commitment to sustainability. Furthermore, the course can help a professional to optimize the usage of resources, look for energy efficient systems, consider environmental changes, develop sustainable solutions, and integrate advanced technologies towards green transition. This is a problem-based course specific to an industrial sector. The problems can be provided by the course supervisor, or the participants can bring their own problems from their work. Common problems include e.g. asset management by balancing cost against performance, identifying, detecting, predicting, and planning for unexpected outages, disruptions or failures, exploring challenges and opportunities with AI and digitisation, monitoring the condition of industrial assets, and achieving sustainability goals. Target groupThe target group includes individuals working in various industries such as railway, mining, transportation, construction, manufacturing, logistics, energy, and other organizations that are or planning to implement asset management systems. This course can be suitable for professionals ranging from asset managers, maintenance and reliability professionals, operation managers, engineers, project managers, and asset management consultants. Online seminarsDecember 10th at 14.00 to 15.00January 14th at 14.00 to 15.00January 31st at 14.00 to 15.00February 13th at 14.00 to 15.00February 28th at 14.00 to 15.00 Entry requirements Bachelor’s degree of at least 180 ECTS or equivalent, which includes courses of at least 60 ECTS in for example one of the following areas: Maintenance Engineering, Mechanical Engineering, Materials Science, Data Science, Computer Engineering, Civil Engineering, Electrical and Electronics Engineering or equivalent. Or professional experience requirements four to five years of experience in relevant industries.

Målet med kursen är att ge lärare fortbildning inom ämnet djurvälfärd och hållbarhet. Kursens mål är också att ge lärare inspiration att designa sin egen undervisning, att ge lärare möjlighet att ta till sig ny forskning och att dela med sig av läraktiviteter som kan användas av fler.