GRUNDERNA I AI, DEL 2: ATT UTVECKLA AI

Answer Set Programming (ASP) is a declarative programming paradigm designed within the field of Artificial Intelligence (AI), and used to solve complex search-problems. The declarative nature of ASP allows one to encode a problem by means of logic. In this way, unlike in imperative programming approaches, there is no need to design an algorithm as a solution for the given problem. In this sense, ASP is comparable with SAT-based encoding or constraint satisfaction problems. However, due to its stable-model semantics, ASP provides a richer representation language useful to handle uncertain situations more effectively for real world scenarios. The advantages of declarative programming together with non-monotonic nature of ASP in handling uncertainties have recently made ASP more attractive both for academia and industry. This course focuses on formalizing and solving various search problems in planning, scheduling and system configuration in ASP.

ROS (Robot Operating System) is a common set of tools used in academia to do research within autonomous systems. It shortly provides a middleware for handling communication, as well as interfacing sensors and actuators, visualization, simulation and datalogging and infrastructure where it is easy to share your own methods and algorithms. The latter has allowed a large set of different of state-of-the-art research approaches to be readily available for downloading. Due to its popularity it is also getting more widespread in the industrial community, especially in R&D. This course will give you hands-on experience how to utilize these tools and apply them to a problem of your choice.

The promise of intelligent robot systems is that they can accomplish more tasks, more efficiently than a single-purpose industrial robotic solution. Intelligent robots act competently because they can plan, sequence and enact the actions that are appropriate in the context in which they find themselves. In order to achieve this capability, intelligent robots use Artificial Intelligence (AI) Search Methods. These are general-purpose algorithms for solving combinatorial problems, in other words, they constitute a robot's "reasoning engine". This course introduces students to the most important types of AI search methods. These are then instantiated in three industrially-relevant application contexts, namely, resource scheduling, motion planning, and multi-robot coordination.

The Internet of Things (IoT) is a networking paradigm which enables different devices (from thermostats to autonomous vehicles) to collect valuable information and exchange it with other devices using different communications protocols over the Internet. This technology allows to analyse and correlate heterogeneous sources of information, extract valuable insights, and enable better decision processes. Although the IoT has the potential to revolutionise a variety of industries, such as healthcare, agriculture, transportation, and manufacturing, IoT devices also introduce new cybersecurity risks and challenges. In this course, the students will obtain an in-depth understanding of the Internet of Things (IoT) and the associated cybersecurity challenges. The course covers the fundamentals of IoT and its applications, the communication protocols used in IoT systems, the cybersecurity threats to IoT, and the countermeasures that can be deployed. The course is split in four main modules, described as follows: Understand and illustrate the basic concepts of the IoT paradigm and its applications Discern benefits and drawback of the most common IoT communication protocols Identify the cybersecurity threats associated with IoT systems Know and select the appropriate cybersecurity countermeasures Course Plan Module 1: Introduction to IoT Definition and characteristics of IoT IoT architecture and components Applications of IoT Module 2: Communication Protocols for IoT Overview of communication protocols used in IoT MQTT, CoAP, and HTTP protocols Advantages and disadvantages of each protocol Module 3: Security Threats to IoT Overview of cybersecurity threats associated with IoT Understanding the risks associated with IoT Malware, DDoS, and phishing attacks Specific vulnerabilities in IoT devices and networks Module 4: Securing IoT Devices and Networks Overview of security measures for IoT systems Network segmentation, access control, and encryption Best practices for securing IoT devices and networks Organisation and Examination Study hours: 80 hours distributed over 7 weeks Scehduled online seminars:  January 30th 2024, February 12th 2024 and 11th of March Examination, one of the following: Analysis and presentation of relevant manuscripts in the literature Bring your own problem (BYOP) and solution. For example, analyse the cybersecurity of the IoT network of your company and propose improvements The number of participants in the course is limited, so please hurry with your application!

Skills in development work are becoming increasing importance in professional life. This course offers you the opportunity to develop knowledge and skills in product development, production development, and business development, as well as the relationship between these areas. You will be introduced to systematic working methods for product development, production development, and business development, with a specific focus on innovation and creativity in practical contexts. The goal of the course is to provide a deep understanding of the application of various processes in different types of development work. The objective is for course participants to enhance their ability to understand and apply development processes and gain deeper insights into how these processes relate to organizations' innovation and business strategies in order to achieve circular flows, resilience, and sustainability in the manufacturing industry. The teaching consists of self-study using course literature, films, and other materials through an internet-based course platform, as well as scheduled webinars and written reflections. There are no physical meetings; only digital online seminars are incuded. Study hours: 40 hours distributed over 7 weeks Scheduled online seminars: 30th January, 13th February, 27th February, and 13th March 2024. The course begins on the 30th of January 2024: (Week 5) 30th January: Webinar 1: Introduction – Part 1 (Focus: Product development) (Week 7) 13th February: Webinar 2: Part 2 (Focus: Production development) (Week 9) 27th February: Webinar 3: Part 3 (Focus: Business development) (Week 11) 13th March: Webinar 4: Final presentations and course evaluation Target Group This course is primarily intended for engineers in management or middle management positions within industry, whether they are recent graduates or individuals with extensive experience. The course is suitable for individuals with backgrounds in mechanical engineering, industrial engineering management, or similar educational background. Entry Requirements To be eligible for this course, participants must have completed courses equivalent to at least 120 credits, with a minimum of 90 ntry Requirementscredits in a technical subject area, with at least a passing grade, or equivalent knowledge. Proficiency in English is also required, equivalent to English Level 6. Link to Syllabus Please note that the number of participants for this course is limited, so we encourage you to apply as soon as possible!

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. 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. Link to course syllabus 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 or equivalent and at least 2 years of full-time professional experience from a relevant area within industry. In addition, good knowledge in English, equivalent to English A/English 6 are required. 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 Students Master's/PhD degree students who are involved in energy, digitalization, controls and production fields. Scehduled online seminars: None Study hours: 80 hours distributed over 10 weeks The number of participants in the course is limited, so please hurry with your application!