REEDEAM

Would you like to know what advanced and rapid production is about? Then this course is for you! In the course, we look at enabling technologies for advanced and rapid production from an industrial perspective. The course covers many topics, and you will learn the basic terminology related to discrete and rapid production, connected factories and automation in assembly. You will get an in-depth knowledge, practical skills and strategic insights relevant to modern production paradigms. The course discusses potential benefits and challenges with different possible techniques. Upon completion of the course, you will have a conceptual understanding of key concepts and technologies and how this can be applied in industry. After completion of the course you will be able to: Show understanding for rapid discrete production and its basic philosophy, strategies and principles. Analyze, plan and implement an improvement project of a production segment in an industrial activity. Show understanding for the various major technology areas within connected factories. Show understanding for various major technology areas regarding automation in assembly. Analyze and describe different basic principles for development and implementation of automation in assembly. Examples of professional roles that will benefit from this course are manufacturing engineers, production managers and automation engineers. This course is given by Mälardalen university in cooperation with Luleå University of Technology. Study effort: 80 hours

This course explores the integration of artificial intelligence (AI) in decision support systems specifically tailored for the energy and production sectors. Students will learn how AI technologies, such as machine learning, optimization, and data analytics, are transforming traditional operational strategies, enhancing decision-making processes, and driving efficiency in energy and production operations. The curriculum will cover foundational concepts of AI and decision support systems, along with practical applications such as predictive maintenance, demand forecasting, process optimization, and real-time decision support. Through hands-on projects, case studies, and industry-relevant examples, participants will gain insights into designing and implementing AI-driven solutions that improve operational performance, reduce costs, and support sustainability goals. By the end of this course, students will be equipped with the skills to develop and apply AI-driven decision support systems to solve complex challenges in energy and production environments. This course is ideal for professionals and students interested in leveraging AI for operational excellence in the energy and production industries.

This course is designed for engineers, scientists, operators, and managers interested in utilizing AI-based methods for condition monitoring and prognostics in industrial systems and high-value assets. Participants will learn to identify common failure causes and predict Remaining Useful Life (RUL) using historical data, involving tasks such as data processing, feature selection, model development, and uncertainty quantification. Led by experienced professionals from industry and academia, the course covers the basics of prognostics and introduces various AI methods, including deep learning. It represents state-of-the-art AI-driven prognostic techniques, advanced signal processing, and feature engineering methods.

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

The main goal of the course is to look into Virtual and Augmented Reality and investigate how this technology, together with the recent developments in AI and Robotics, support sustainability and green transition. The course starts with a brief overview of the concept of reality and virtuality and looks into some fundamentals of human perception and action. It explores, for example, how we build mental representations and why we perceive some artificially created experiences as real even when we know that they are fictional. We will also apply the concept of artificial sensory stimulation to other living organisms and look into experiments on virtual reality for other animals and even ants. The course then proceeds to look into the fundamental research in reality-virtuality continuum and an overview of relevant technologies. We will see how modern graphics and rendering technology allows to “hijack” human sensory input and how tracking technologies allow to collect data from human actions. This vital concept and technology part will serve as a foundation to discuss further questions related to application of Virtual and Augmented Reality. Those include ethics of extended reality applications, for example related to neuroplasticity effects of virtual reality or user profiling, or cybersecurity aspect of possible user identification. However, the main focus of the course is on sustainability and green transition. The course looks beyond the potential ability of virtual and augmented reality technologies to reduce the need for physical travel (e.g. through telepresence), and discusses such topics related to Industry 5.0. For example, design and simulation, where modern technology allows to reduce the needs for physical prototyping and helps to optimize product development processes, or industrial process optimization through digital tweens, or immersive training and education, allowing adaptive learning pace for each student. The course includes an invited lecture with industry professionals. 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 dates): -January 15 -Februry 5 -March 19 Study hours: 80 This course is given by Örebro University.

This course is designed for you who wants to learn more about functional safety of battery management systems. The course will also cover other aspects of safety such as fire safety in relation to Rechargeable Energy Storage Systems (RESS) and associated battery management systems. In the course you will be able to develop skills in principles of battery management systems, functional Safety as well as of other aspects of safety such as fire safety, hazard identification, hazard analysis and risk assessment in relation to battery management systems. The course also provides a broader understanding of the multifaceted nature of safety. The course is given with a low study pace. This course is primarily intended for engineers that need to ensure that battery management systems are safe, reliable, and compliant with industry standards. The course is suitable for individuals with backgrounds in for example functional safety, battery systems, automotive or risk assessment.  

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.

Hydrometallurgy is vital for the green transition and the growing production and need for critical metals. In hydrometallurgy, metals are produced with the help of liquids instead of high temperatures, this approach requires less energy and can be used on complex materials. The course provides knowledge about hydrometallurgical processes used for the extraction and recovery of metals from various primary and secondary raw materials. It focuses on the theory behind unit operations such as leaching, separation, and metal recovery, as well as environmental management of waste products. The content is delivered through online-accessible lectures, interactive seminars, guest lectures, and laboratory exercises. Through quizzes, assignments, and presentations, students are trained to apply theoretical principles and understand the technological environmental challenges in the field. The course is designed to enable studies besides daily work. Study hoursHydrometallurgy is vital for the green transition and the growing production and need for critical metals. In hydrometallurgy, metals are produced with the help of liquids instead of high temperatures, this approach requires less energy and can be used on complex materials. The course provides knowledge about hydrometallurgical processes used for the extraction and recovery of metals from various primary and secondary raw materials. It focuses on the theory behind unit operations such as leaching, separation, and metal recovery, as well as environmental management of waste products. The content is delivered through online-accessible lectures, interactive seminars, guest lectures, and laboratory exercises. Through quizzes, assignments, and presentations, students are trained to apply theoretical principles and understand the technological environmental challenges in the field. The course is designed to enable studies besides daily work. SeminarsSeminar lab: December 10th 2025 at 16:00-18:00 Seminar assignments: January 14th 2026 at 16:00-18:00 Entry reqirements180 credits in science/technology, including a basic course in chemistry of 7.5 credits (e.g. Chemical Principles, K0016K). Good knowledge of English, equivalent to English 6 or equivalent real competence gained through practical experience. Target groupProfessionals in industry, academia or institute, everyone that fulfills the criteria is welcome but the course is created for further education.

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