Applications 2024-12-08
COURSE DESCRIPTION
Deepening knowledge of advanced techniques and processes for fossil-free steel production is essential for taking the next step toward a carbon-free industry. This course focuses on optimizing and implementing innovative solutions in the manufacturing process.
Course Content
What You Will Learn
Who Is the Course For?
The course is designed for professionals in the steel industry, researchers, and technical specialists with basic knowledge of fossil-free manufacturing who want to deepen their understanding of advanced techniques.
Language
The course is conducted in Swedish and English.
Additional Information
The course includes 60 hours of study and is offered for a fee.
Do you want to learn the basics of Industry 4.0, at your own pace, whenever you want? Then the MOOC (Massive Open Online Course) Introduction to Industry 4.0 is for you. You will learn basic terminology and theory while gaining insight and understanding of the fourth industrial revolution and how it affects us. The MOOC: Introduction to Industry 4.0 is part of MDU's investment in smart production. The course is divided into ten modules, each of which describes different technologies in Industry 4.0. We estimate that it will take about 40 hours to complete the course and it is in English. The MOOC can also give you eligibility to apply for these 3 university courses at Mälardalen University: Internet of things for industrial applications, 5 credits Simulation of production system, 5 credits Big data for industrial applications, 5 credits
This course is taught in Swedish. Lean production consists of a set of principles and techniques, which are included in the business's systems and processes. These can be derived into a particular business philosophy and strategy that encompasses the entire organization's operations. The course lays the foundation for continued broader and deeper studies of how operations are run at the new generation of world-leading companies with a Lean business strategy. This starting course covers the following topics: Strategies and principles for Lean production Stable processes and standardized working methods Design of value streams Pulling and pushing production systems Quality philosophy and quality methodology Teamwork, commitment and participation Management system with PDCA methodology Business collaboration along value flows Transformation to a Lean corporate culture Course structure Five two-day meetings consisting of discussion lectures, practical exercises and analyzes of operations in companies that practice Lean methodology. Course literature Jeffrey Liker, The Toyota Way, Liber, 2009 Modig & Åhlström, This is Lean Petersson et al., Lean turns deviations into success, 2009 Target group People within organizations considering and Lean business strategy. See all courses that KTH Leancentrum offers
In this course, you will learn how data analysis in virtual production can improve your organization's results! Data analytics in virtual production uses advanced techniques to collect, analyze and present data to improve production. This system is designed to help companies optimize their production and increase efficiency. By learning how to model, do scenario analysis and evaluate using industrial software, identify bottlenecks, and use AI methods and applications, you will get all the tools necessary to succeed with a full production analysis. The course is given with flexible start and study pace, but we recommend a study pace of 20 %, which means that the course takes about 8 calendar weeks.
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