Applications 2023-09-01
COURSE DESCRIPTION
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.
Following are suggested modules in the virtual commissioning course, each with its own specific role in the process. These modules work together to create a comprehensive virtual commissioning process, allowing engineers to test and validate control systems and production processes in a simulated environment before implementing them in the real world.
Pre-requisite
75 university credits in production technology, mechanical engineering, product and process development, computer technology and/or computer science or equivalent or 40 credits in technology and at least 2 years of full-time professional experience from a relevant area within industry. In addition, English A/English 6 are required.
Expected outcomes
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.
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
Students
Master's/PhD degree students who are involved in energy, digitalization, controls and production fields.
Scehduled online seminars: None
The number of participants in the course is limited, so please hurry with your application!
In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data. This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.This course is for experienced developers working in the industry. The course includes the following: Supervised learning, different types of data and data processing, Algorithms for handling text documents, Algorithms for handling data with numerical and categorical attributes, Neural Networks and Deep Learning for image recognition
To be translated Svensk industri möter nu en av de största utmaningarna sedan den industriella revolutionen. Vad innebär det för dig som ledare eller blivande ledare i industrin? Hur bibehåller du drivkraften hos dina medarbetare?Välkommen till kursen tekniskt ledarskap för framtidens industriprocesser. Den här kursen är särskilt framtagen för dig som har, eller strävar efter att ha en ledande roll i en industriell organisation. Kurser ger dig fördjupad kunskap inom området teknisk ledarskap med hänsyn till både mänskliga faktorn och ekonomin utöver den tekniska baskunskapen, den så kallade fullt integrerade teknikern eller ingenjör. Vi tittar närmare på och diskuterar olika ledaregenskaper och ledarstilar. Vad innebär det att vara en ledare med tekniskt ansvar?Stora förändringar krävs för att svensk industri ska fortsätta vara konkurrenskraftig. Genom studier av praktikfall och arbetsrelaterade fall skapas djupare förståelse för under vilka förutsättningar tekniska ledare arbetar och vilka krav som ställs. Kurskod, anmälningskodVP737A, HS-26353 Ansökan, behörighet och antagningOm du arbetar inom industrin, men saknar akademiska meriter, kan du ansöka om att bli bedömd på så kallad reell kompetens. Läs mer på den här sidan his.se/ansokindustrikurser
To be translated Svensk industri möter nu en av de största utmaningarna sedan den industriella revolutionen. Vad innebär det för dig som ledare eller blivande ledare i industrin? Hur bibehåller du drivkraften hos dina medarbetare?Välkommen till kursen tekniskt ledarskap för framtidens industriprocesser. Den här kursen är särskilt framtagen för dig som har, eller strävar efter att ha en ledande roll i en industriell organisation. Kurser ger dig fördjupad kunskap inom området teknisk ledarskap med hänsyn till både mänskliga faktorn och ekonomin utöver den tekniska baskunskapen, den så kallade fullt integrerade teknikern eller ingenjör. Vi tittar närmare på och diskuterar olika ledaregenskaper och ledarstilar. Vad innebär det att vara en ledare med tekniskt ansvar?Stora förändringar krävs för att svensk industri ska fortsätta vara konkurrenskraftig. Genom studier av praktikfall och arbetsrelaterade fall skapas djupare förståelse för under vilka förutsättningar tekniska ledare arbetar och vilka krav som ställs. Kurskod, anmälningskodVP737A, HS-26355 Ansökan, behörighet och antagningOm du arbetar inom industrin, men saknar akademiska meriter, kan du ansöka om att bli bedömd på så kallad reell kompetens. Läs mer på den här sidan his.se/ansokindustrikurser
To be translated Kursen vänder sig till dig som arbetar inom, eller är intresserad av att förstå tekniskt ledarskap inom industrin och inte har tidigare erfarenhet av att ha ett uppdrag som innebär ledning av andra individer. Du kan vara ny i din roll som arbetslagsledare eller liknande och hanterar gruppnivåer utan personalansvar eller önskar få grundläggande kunskaper som stöttar dig på väg in i ett sådant uppdrag.Då förändringstakten ökar ställer detta krav på ökad flexibilitet och förståelse för hur produktionsprocesser och beslut går till. För att medarbetare och ledare ska kunna utveckla sitt ledarskap för att klara hantera en fullt integrerat miljö med djup förståelse i teknik och förståelse för medarbetare och ekonomi i ett företag, krävs förståelse för individ och grupp samspelar. Kursen är utformad för att kunna få arbeta med problemställningar som finns på arbetsplatsen utifrån ett tekniskt ledarskapsperspektiv där du får diskutera, presentera och beskriva dina förslag till lösningar i ett sammanhang som bygger på vetenskaplig grund som kan användas inom praktiken i industrin. Efter avslutad kurs kan du utförligt redogöra för och diskutera viktiga begrepp, ansatser och ledarstilar inom tekniskt ledarskap för industrin i omställning,presentera och kritiskt diskutera ett praktiskt fall inom området tekniskt ledarskap för industri i förändring och förstå vikten av hastigheten i genomförandet och vikten av att beakta en föränderlig omvärld,diskutera ledarskapets betydelse och ansvar i relation till etiska aspekter av teknikutveckling, hållbarhetsaspekter av teknisk utveckling och jämställdhetsaspekter i tekniska organisationer/grupper. Kurskod, ansökningskodPR024G, HS-21800 Ansökan, behörighet och antagningOm du arbetar inom industrin, men saknar akademiska meriter, kan du ansöka om att bli bedömd på så kallad reell kompetens. Läs mer på den här sidan his.se/ansokindustrikurser
The purpose of the course “Artificial Intelligence for Managers” is to give managers and decision makers a principle understanding of AI and to increase their understanding of opportunities, difficulties, benefits, and risks connected to AI. It is neither an “Introduction to AI” nor an “AI for dummies” course. Instead, it is set to demystify AI and to transform it into an actionable tool for manages and decision makers. Target groupThis course is for product managers, project managers, executives, and engineering managers in organizations that have already made, or are about to make, the transition to working with AI. ContentThe course is organized in three modules. The initial module will focus an introduction to AI, giving an understanding of what type of cases can be addressed with AI and what managers need to know about AI technology. Module two will cover tools and concrete on how to set up an AI strategy and roadmap, how to get started on AI projects, how to integrate AI and IT development, how to (self) evaluate AI in use, and, not to forget, the ethical and legal aspects of AI. The third module will give the participants the chance to use their new knowledge and tools and work with their own practical cases and how they could be addressed using AI. The goal of the course is to empower the participants to: Describe the principal concept of AI, its strengths, and shortcomings Understand opportunities, myths, and pitfalls of AI Identify problem areas in industry, society, and in management where AI could be utilized Analyze how AI can be applied in a particular problem area Manage an AI strategy and get started: implement a strategy and a roadmap to apply AI in a particular problem area Understand how to integrate AI with IT development Assess the maturity of AI utilization in an organization Reflect on applications of AI from an ethical and legal perspective as well as the future challenges (technical, organizational, social, etc.) Practical informationAll materials will be accessible and include reading material, lecturer slides etc. The lectures can either be attended live via Zoom or later using the recordings at a time that is convenient for the participants. There will be 3 onsite workshops with a focus on interaction with the teacher and the co-participants of sharing real-life experiences and insights. The course will be delivered in a flexible manner to facilitate the combination of course work with your ongoing professional commitments. The total effort to pass this course is typically around 200 hours. Teaching language: English Entry requirementsThe basic eligibility for this course is a bachelor’s degree. Candidates with corresponding work experience are also invited to apply. Two years of relevant work experience is considered equivalent to one year of university studies at bachelor level. The course is free
The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. About the course Smart Healthcare with Applications, 4 credits Who is this course for?The course suits you with any Bachelor’s degree (equivalent of 180 Swedish credit points / ECTS credits at an accredited university) who have an interest in applying Artificial Intelligence (specifically Machine Learning) to healthcare. Leadership/management experience in health-related organization/industry OR a Bachelor degree in computer science is advantageous. What will you learn from this course?Healthcare as a sector together with other health-related sources of data (municipalities, home sensors, etc.), is now in a place and can take advantage of what data science, Artificial Intelligence (AI), and machine learning (ML) have to offer. Information-driven care has the potential to build smart solutions based on the collected health data in order to achieve a holistic fact-based picture of healthcare, from an individual to system perspective. This course aims to provide a general introduction to information-driven care, challenges, applications, and opportunities. Students will get introduced to artificial intelligence and machine learning in specific, as well as some use cases of information-driven care, and gain practice on how a real-world evidence project within information-driven care is investigated. What is the format for this course?Instruction type: The lectures, announcements, and assignments of this course will be fully online via a learning management system and presented in English. Each lecture is delivered through a video conference tool with a set of presentation slides displayed online during each class session. Online practical labs (pre-written Python notebooks) are also provided in the lectures.