DJURVäLFäRD OCH HåLLBARHET

This is a course for professionals and PhD students seeking a wider understanding of our current global predicaments, how to make sense of them, and how to respond. The first module introduces the Anthropocene, The Great Acceleration, Planetary Boundaries along with causal relationships between energy, technology, economy, values and the human and more-than-human experience. The second module explores how our own cognition, values, norms and emotions guide our responses to the crises of our time, and how we can formulate coherent responses based on our experiences. The third introduces a way of reasoning about the world in terms of interconnected systems instead of independent problems, and explores what such a view means for us. The course is run online with 2h highly interactive seminars connected to each module along with recorded material, readings and exercises.

Miljö, klimat och hälsa Kursen ger en fördjupad förståelse för hur hälsa samspelar med globalisering och miljö- och klimatförändringar, och hur hållbara lösningar kan utvecklas på lokal och global nivå för att möta framtidens utmaningar.   Kursens innehåll Globala processer såsom miljö- och klimatförändringarDe globala hållbarhetsmålen / Agenda 2030HälsokonsekvensanalysKlimatanpassningRamverk inom miljö- och klimatpolitik.  Vidare behandlar kursen specifikt klimatförändringar och deras effekter på hälsa i vårt nordeuropeiska klimatområde. I det sammanhanget behandlas också särskilt utsatta miljöer respektive känsliga patientgrupper och individer. Även värmens effekter vid arbete samt klimatanpassning och förebyggande av väderrelaterade risker för boende och inom hälso- och sjukvård ingår. Larmkedjor, handlingsplaner och beredskapsfrågor inom vård- och omsorg tas upp, och effektiviteten av förebyggande åtgärder inom vård- och omsorg.   Omfattning Kursen är uppdelad i tre delar, med totalt 15 filmade föreläsningar.   Medverkande Christofer Åström (Medicine doktor, Folkhälsa och klinisk medicin, Umeå universitet) Maria Nilsson (Professor, Epidemiologi och global hälsa, Umeå universitet) Chris Ebi (Professor, Center for Health and the Global Environment, University of Washington) Eva-Lotta Glader (Docent, överläkare, Folkhälsa och klinisk medicin, Umeå universitet) Gustav Strandberg (Filosofie doktor, SMHI)

In this course package you will get a basic introduction to the concept of sustainable development. Among other things, we will discuss: The three pillars of sustainability (economic, social and ecological sustainability) Planetary boundaries Resource management  You will also learn about key competences for sustainability such as systems thinking and values thinking, and get an overview of the basic mechanisms of Earth’s climate and climate change. See all free online courses that KTH offers

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.

Virtual commissioning (VC) is a technique used in the field of automation and control engineering to simulate and test a system's control software and hardware in a virtual environment before it is physically implemented. The aim is to identify and correct any issues or errors in the system before deployment, reducing the risk of downtime, safety hazards, and costly rework. The virtual commissioning process typically involves creating a digital twin of the system being developed, which is a virtual representation of the system that mirrors its physical behaviour. The digital twin includes all the necessary models of the system's components, such as sensors, actuators, controllers, and interfaces, as well as the control software that will be running on the real system. Once the digital twin is created, it can be tested and optimized in a virtual environment to ensure that it behaves correctly under various conditions. The benefits of using VC include reduced project costs, shortened development time, improved system quality and reliability, and increased safety for both operators and equipment. By detecting and resolving potential issues in the virtual environment, engineers can avoid costly and time-consuming physical testing and debugging, which can significantly reduce project costs and time to market. The course includes different modules, each with its own specific role in the process. Together, the modules create a comprehensive virtual commissioning process that makes it possible to test and validate control systems and production processes in a simulated environment before implementing them in the real world. Modeling and simulation: This module involves creating a virtual model of the system using simulation software. The model includes all the equipment, control systems, and processes involved in the production process. Control system integration: This module involves integrating the digital twin with the control system, allowing engineers to test and validate the system's performance. Virtual sensors and actuators: This module involves creating virtual sensors and actuators that mimic the behavior of the physical equipment. This allows engineers to test the control system's response to different scenarios and optimize its performance. Scenario testing: This module involves simulating different scenarios, such as equipment failures, power outages, or changes in production requirements, to test the system's response. Data analysis and optimization: This module involves analyzing data from the virtual commissioning process to identify any issues or inefficiencies in the system. Engineers can then optimize the system's performance and ensure that it is safe and reliable. Expected outcomes Describe the use of digital twins for virtual commissioning process. Develop a simulation model of a production system using a systems perspective and make a plan for data collection and analysis. Plan different scenarios for the improvement of a production process. Analyze data from the virtual commissioning process to identify any issues or inefficiencies in the system and then optimize the system's performance. Needs in the industry Example battery production: Battery behaviors are changing over time. To innovate at speed and scale, testing and improving real-world battery phenomena throughout its lifecycle is necessary. Virtual commissioning / modeling-based approaches like digital twin can provide us with accurate real-life battery behaviors and properties, improving energy density, charging speed, lifetime performance and battery safety. Faster innovation (NPI) Lower physical prototypes Shorter manufacturing cycle time Rapid testing of new battery chemistry and materials to reduce physical experiments Thermal performance and safety It’s not just about modelling and simulating the product, but also validating processes from start to finish in a single environment for digital continuity. Suggested target groups Industry personnel Early career engineers involved in commissioning and simulation projects Design engineers (to simulate their designs at an early stage in a virtual environment to reduce errors) New product introduction engineers Data engineers Production engineers Process engineers (mediators between design and commissioning) Simulation engineers Controls engineer System Integration