COURSE DESCRIPTION
Den här kursen ger dig som jobbar med teknik inom det medicintekniska området de kunskaper och färdigheter som krävs för att hantera risker och säkerställa hållbarhet inom medicintekniska system. Medicinteknisk utrustning omgärdas av en speciell lagstiftning för att säkerställa hög patient- och användarsäkerhet. Hållbarhetskraven ökar inom alla branscher, så också inom life science. För företag och ingenjörer ställer detta stora krav på kunskap kring hantering av risker vid utveckling och handhavande av medicintekniska system.
Kursen tar upp risker och säkerhetsaspekter rörande medicinteknisk utrustning inom områdena el-, gas- och ickejoniserande strålning. Kursen introducerar medicinteknisk riskhantering samt hur medicinteknisk utrustning och elförsörjning ska utformas för att vara säker och hållbar för både patient och vårdpersonal.
Kursen ges på distans och är lärarledd. Kursen har 25% studietakt, och arbetstiden du behöver lägga ner motsvarar cirka 7 arbetsdagar.
Det ingår ett praktiskt moment som utförs under handledning på den egna arbetsplatsen.
Efter avklarad kurs har du en ökad kunskap om säkerhetsaspekter kopplade till medicinsk teknik. Du har även kunskap om säkerhet, lagar och bestämmelser för medicinteknisk utrustning.
Kursen riktar sig till medicintekniska ingenjörer eller andra yrkesgrupper verksamma på sjukhuset eller inom sjukvården.
Kursen ges som anpassad kompetensutveckling för yrkesverksamma mot en avgift. Läs mer om uppdragsutbildning vid Umeå universitet.
Kontaktperson: Helena.grip@umu.se
Pris: 4693 kr/person exkl moms (betalas av deltagarens arbetsgivare).
In this course, you will be made aware of the state-of-the-art in cybersecurity research and state of practice in industry. Cybersecurity vulnerabilities are a threat to progress in the business sector and society. This is an accelerating threat due to the current rapid digitalisation, which in manufacturing is termed Industry 4.0. Companies are aware of this threat and realise the need to invest in countermeasures, but development is hampered by lack of competence.
The aim of the course is to provide proficiency in cybersecurity analysis and design in industrial settings, with a special focus on smart factories and Industry 4.0. To achieve this, you will learn about advanced cybersecurity concepts, methodologies and tools. You will also be able to apply your knowledge to industrial case studies.
Den här kursen ger dig verktyg och kunskaper för att kunna identifiera och analysera miljörisker. Vi diskuterar möjligheter och behov av att kunna förebygga miljörisker, sannolikheten för att de inträffar och vilka konsekvenser de kan ha för människor, samhället och miljön, både på kort och lång sikt. Kursens mål är att ge dig förståelse för riskanalys och riskhantering. Den ger en teoretisk bakgrund till hur man identifierar, analyserar, bedömer och redovisar miljörisker, från enklare till mer komplexa incidenter. Kursens upplägg Kursen ges på distans, med 25% studietakt. Undervisningen bedrivs i form av obligatoriska zoomföreläsningar, seminarier och projektarbete. Examinationen sker både löpande via aktivt deltagande på föreläsningar, och genom skriftlig och muntlig redovisning av projektarbeten. Mål med kursen Efter avklarad kurs kan du: Identifiera, analysera och värdera risker och riskhanteringssystem inom miljöområdet. Använda och kritiskt utvärdera verktyg som används för att identifiera och bedöma risker. Presentera, diskutera och integrera sina kunskaper, argument och slutsatser inom ämnesområdet för kursen. Målgrupp Kursen passar för personal inom kommun, näringsliv och myndigheter som ska genomföra riskanalyser med fokus på miljöperspektiv för att identifiera, utvärdera och hantera potentiella miljörisker kopplade till verksamheter, projekt eller beslut. Mer information om kursstart och anmälan publiceras inom kort.
This course explores the role of intelligent sensor systems in driving sustainability and enabling the green transition. Participants will learn the fundamentals of sensor technologies and their integration into intelligent, distributed systems. Emphasis is placed on applications in energy efficiency, environmental monitoring, and sustainable automation. The course covers topics such as basic sensor technologies, embedded systems, distributed computing, low-resource machine learning approaches, and federated learning for privacy-preserving, decentralized model training across sensor nodes. Through a combination of lectures, practical examples, and hands-on project work, participants will gain experience in designing and deploying intelligent sensor systems tailored to real-world sustainability challenges. The students bring their own case study example as the background for a practical project, through which the student is also finally examined. Recommended prerequisites: At least 180 credits including 15 credits programming as well as qualifications corresponding to the course "English 5"/"English A" from the Swedish Upper Secondary School. Online meetings (estimated): 14 Oct.: Introduction11 Nov.: Project Idea16 Dec.: Project Presentation Study hours: 80 This course is given by Örebro University.
Batteries and battery technology are vital for achieving sustainable transportation and climate-neutral goals. As concerns over retired batteries are growing and companies in the battery or electric vehicle ecosystem need appropriate business strategies and framework to work with.This course aims to help participants with a deep understanding of battery circularity within the context of circular business models. You will gain the knowledge and skills necessary to design and implement circular business models and strategies in the battery and electric vehicle industry, considering both individual company specific and ecosystem-wide perspectives. You will also gain the ability to navigate the complexities of transitioning towards circularity and green transition in the industry.The course includes a project work to develop a digitally enabled circular business model based on real-world problems. Course content Battery second life and circularity Barriers and enablers of battery circularity Circular business models Ecosystem management Pathways for circular transformation Design principles for battery circularity Role of advanced digital technologies Learning outcomes After completing the course, you will be able to: Describe the concept of battery circularity and its importance in achieving sustainability goals. Examine and explain the characteristics and differences of different types of circular business models and required collaboration forms in the battery- and electric vehicle- industry. Analyze key factors that are influencing design and implement circular business models based on specific individual company and its ecosystem contexts. Analyze key stakeholders and develop ecosystem management strategies for designing and implementing circular business models. Explain the role of digitalization, design, and policies to design and implement circular business models. Plan and design a digitally enabled circular business model that is suitable for a given battery circularity problem. Examples of professional roles that will benefit from this course are sustainability managers, battery technology engineers, business development managers, circular developers, product developers, environmental engineers, material engineers, supply chain engineers or managers, battery specialists, circular economy specialists, etc. This course is given by Mälardalen university in cooperation with Luleå University of Technology Study effort: 80 hrs
Understanding and optimizing battery performance is crucial for advancing electrification, sustainable mobility, and renewable energy systems. This course provides a comprehensive overview of battery performance, ageing processes, and modelling techniques to improve efficiency, reliability, and service life. Participants will explore battery operation from a whole-system perspective, including its integration in electric vehicles (EVs), charging infrastructure, and energy grids. The course covers both physics-based and data-driven modelling approaches at the cell, module, and pack levels, equipping learners with tools to monitor, predict, and optimize battery performance in real-world applications. Through this course, you will gain the ability to assess battery health, model degradation, and evaluate second-life applications from both technical and economic standpoints. Course content Battery fundamentals and degradation mechanisms Battery modelling Battery monitoring and diagnostics Operational strategies for battery systems Techno-economic performance assessment Battery second-life applications You will learn to: Explain the principles of battery operation and degradation mechanisms. Develop battery performance models using both physics-based and data-driven approaches. Apply methods for State of Health (SOH) estimation and Remaining Useful Life (RUL) prediction. Analyze key factors influencing battery lifespan economics in different applications. Evaluate battery second-life potential and identify suitable applications. Target group: Professionals in energy, automotive, R&D, or sustainability roles Engineers and data scientists transitioning into battery technologies Technical specialists working with electrification, battery management systems, or energy storage