Mälardalen University

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.

This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation. You will learn: Understand algorithmic test generation techniques and their use in developer testing and continuous integration. Understand how to automatically generate test cases with assertions. Have a working knowledge and experience in static and dynamic generation of tests. Have an overview knowledge in search-based testing and the use of machine learning for test generation.

In this course, we will go through different commands and techniques to create advanced shapes. You will also learn how to analyze the appearance of surfaces and shapes, and you will learn how to use top-down modeling to create models. You will also learn how to create products from sheet metal and products made from standard profiles. The software used is SolidWorks. This course is given in Swedish.

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.  

Would you like to know what Industry 4.0 is about? Then this course is for you! In the course, we look at enabling technologies of Industry 4.0 from a human and industrial perspective. The course covers many topics and you will learn the basic terminology related to Industry 4.0 as well as insight and understanding of the Fourth Industrial Revolution and how it is set to affect industry and individuals.

Do you want to deepen your knowledge in Industrial Internet of Things? In this course, you will gain deeper knowledge and understanding of the Industrial Internet of Things (IIoT), platforms and cloud services used in manufacturing industries. You will learn to understand the use of IoT platforms and how to design and implement simple systems and how to create value by using IoT solutions within industrial systems. The course will provide you with practical and theoretical knowledge in IIoT, platforms and cloud services as well as in-depth knowledge in production, logistics and product development.

Learn how to use the Internet of Things (IoT) to develop smart products and services. The Internet of Things (IoT) is a collective term for the technologies that enable devices with embedded electronics and internet connectivity such as appliances, machines, and vehicles to be controlled or exchange data over a network. In this course, you will gain basic knowledge of the various components that make up Industrial Internet of Things (IIoT) systems, including sensor technologies, smart tags, data communication, and cyber security. You will learn What requirements are imposed on data communication Understand computer communication technologies and their possibilities, limitations and expected role in the development of IIoT Understand appropriate measures against common security issues

This course provides a fundamental knowledge of IoT, targeting physical devices, communication and computation infrastructure. The course gives theoretical knowledge as well as hands-on experiences to build an IoT application.

This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.

A smart factory is an industrial manufacturing facility that uses technology such as the Internet of Things (IoT), automation, and artificial intelligence (AI) to increase productivity and profitability. Smart factories use sensors and other technology to collect, share, and analyze data that helps improve production, increase safety, reduce energy consumption, and improve product quality. You will learn The various major technological areas of smart factories Fundamental principles of operation and control of smart factories Understand and describe how smart machines and products interact in smart factories

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.