Mälardalen University

Applied AI refers to AI technology that is used for practical purposes, usually within an industry or organization. Applied AI can be used to help people make better decisions, work more efficiently, and to automate processes. This course will provide you with the knowledge to collect, manage, process and analyze data to build AI applications for the manufacturing industry. You will learn the latest tools and techniques to analyze large datasets, apply machine learning algorithms, and present your results.

The information and communication technology (ICT) sector is responsible for approx. 1.8-2.8% of the global greenhouse gas (GHG) emissions in 2020, and software is both part of the problems and the solutions. Traditional software engineering principles and techniques do not consider the climate, environment, and sustainability aspects in building and using software for any purpose. We, software engineers, developers, researchers, climate scientists, and various other related stakeholders, need to think about how we can reduce the carbon footprint due to building and using software-intensive systems. Green and sustainable software engineering is an emerging concept that can help reduce the carbon footprint related to software. In this introductory course, we will introduce the concept of green and sustainable software engineering and the engineering process to build green and sustainable software. Topics Sustainable and green computing Sustainable and green software engineering Process Energy efficient computing Sustainability issues in Scientific computing You will learnBy the end of the course, you will be able to: analyze the green and sustainability issues in traditional software engineering, identify and incorporate key elements to be included in the software engineering process to make the software green and sustainable, and use techniques to make your software code energy efficient. Who is the course for?This course is designed for those who are software developers, managers and software related policy makers, or have knowledge about software development, and want to consider the green and sustainability aspects in their everyday life. Also, this course will be useful for computational scientists who build green software and want to know more about these aspects in software engineering. However, this is an introductory course, and it will show a path for life-long learning to build more in-depth knowledge in each concept introduced in this course.

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

Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.

The aim of this course is to give students insight about certification and about what it means to certify/self-assess safety- critical systems with focus on software system and to create a safety case, including a multi-concern perspective when needed and reuse opportunities, when appropriate.

This course provides an understanding of the fundamental problems in software testing, as well as solid foundation in the practical methods and tools for a systematic state-of-the-art approach to testing of software.

Responsible innovation means seeking the best improvements for society and the environment at local, regional and global levels. Responsible innovation takes into account the impact that new services, goods, behaviours, processes or business models can have on society, the economy and the environment. This means that a responsible approach to innovation aims to create changes that have a positive impact on society and the economy as well as on the environment and climate. This course is given in Swedish.

This course provides an introduction into network security and covers core security concepts such as, e.g., firewalls, authentication, certificate management, encryption, "stateful packet inspection", VPN and others. During the course you are provided with slide and video materials as well as a set of practical assignments and thus gain both theoretical and practical knowledge and skills needed for the installation, troubleshooting, and monitoring of network devices to maintain the integrity, confidentiality, and availability of data and devices.

The starting point for service innovations is a deeper understanding of user needs and context, while the starting point for product innovations is often new technology or process optimization. Service logic is the basis for a perspective and research area where everything in markets is seen as services, and where users and other stakeholders are seen as co-creators of value. Service innovation is about meeting user needs that have not yet been met. Because users and other stakeholders are involved in the development processes, service innovation processes are often open. In this course, you will learn more about how user involvement through service innovation processes can lead to service innovation. Being able to innovate, carry out development work and solve problems or challenges is a valuable skill in any profession and in this course you will try out service innovation and practical user involvement methods for working with development. This course is given in Swedish.

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

Turbulent times increase the importance for innovation and transformation in all sectors. The understanding about future trends and how to identify them is an important skill. Trend spotting is important in innovation processes to understand how needs and contexts may change from now and into the future. In this course, you will gain an understanding of how trend spotting and contextual analyses are relevant parts of the innovation process. You learn methods and tools that you can use in your professional role and other roles you have in life. As a professional worker, you can use the course's exercises in your own development work in parallel with your studies. The goal is to create knowledge about the field itself, and to provide the conditions for self-reflection and a future-oriented approach to innovation and changes. This is valuable both for individuals and on an organizational level.

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