The School of Engineering at Jönköping University is one of the country's largest educators of university engineers. We collaborate with the business community regionally, nationally, and internationally to make education adapted to the needs of the market. Therefore, our educations include not only technical knowledge but also entrepreneurship, leadership, communication, sustainable development, and the opportunity to make international contacts during studies. The research at the School of Engineering focuses on knowledge-intensive product realization in collaboration with business community.
AGILE PRODUCTION DEVELOPMENT Build the required knowledge and skills for efficient cross-disciplinary production development work. The course combines latest theories with practical cases from participating companies. The course gives students the required knowledge and skills for efficient cross-disciplinary production development work. Assignments are based on theory and industrial needs, that will be further developed in practical cases selected in close collaboration with their respectively companies. The students will be trained in agile planning methods/principles and an iterative way of working in a structured manner. The aim is to meet challenges/deviations in production development projects by implementing agile feedback-loops and innovative methods and principles. The course includes the following elements: Knowledge Intensive Product Realisation Challenges in industrial companies Overview processes and change management Organize for Information exchange and learning Agile Project Management Agile history and background, including methods and principles Project management and decision making Organization, collaboration and communication. Iterative development methods Planning, including Visible Planning (VP) Production Concept Development Requirement management, Product architecture and Production system Innovative thinking and activities Tools and methods for innovation and evaluation Production Concept Selection and Decisions Decision support and evaluation of alternatives Tools and methods for concept presentation and selection Implementation and follow-up
PRODUCTION AUTOMATION - TECHNOLOGY & INTEGRATION PRODUKTIONSAUTOMATION - TEKNIK & INTEGRATIONThe main purpose of the course revolves around the introduction of the applications that automation systems could have for production and manufacturing operations. The course consists of different themes, including industrial robotics, automation equipment and hardware components, as well as practical insights and discussions on why and how to automate in productions. The course aims to provide knowledge and skills in automation so that after completing the course, participants can identify technologies that are available and suitable for implementing automation. The course also helps to increase knowledge of how new automation solutions can be integrated with existing production equipment and technologies. The course includes the following elements: Introduction to the main elements of automation projectsIdentification of elements suitable for automationTechnologies used in automation, e.g. sensors, material handling equipment, end-of-arm-tooling (EOAT), etc.Conceptual design of automated stationsBenchmarking of automation technologies
EXPLAINABLE ARTIFICIAL INTELLIGENCE (XAI) Artificial Intelligence is increasingly playing an integral role in our daily activities. Moreover, AI based solutions are used more and more in areas such as criminal justice, healthcare, and education, and therefore, their impact is high. The dominant role played by AI models in these domains has led to a growing concern regarding potential bias, and a demand for model transparency and interpretability. Why did the system make this prediction? Do I trust it? What would happen if I change some parameter? As a consequence, AI researchers and practitioners have focused their attention on explainable AI to help them better trust and understand AI models. In this course, we present an introduction to Explainable Artificial Intelligence (XAI). We describe the challenges associated with the use of black-box models and how we can overcome such challenges using interpretable and explainable methods. Moreover, we study other aspects related to interacting with AI-based systems, for example, trust, acceptance, evaluation, and Fairness Accountability and Transparency-issues. The course is given in English and is targeted for working professionals in the industry. This course gives an introduction to Explainable AI (XAI), providing an overview of relevant concepts such as interpretability, transparency and black-box machine learning methods. The course provides an overview of state-of-the-art methods for generating explanations, and touches upon issues related to decision-support, human interaction with AI/intelligent systems and their evaluation. In summary, the Explainable AI course covers the following topics: Definitions and concepts such as black-box models, transparency, interpretable machine learning and explanations. Decision-making and decision support, Human-Computer Interaction (HCI) and AI. Explainable AI. Methods for Explainable AI. Applications and examples. Trust and acceptance. Ethical, legal and social issues of explainable AI. Evaluation methods and metrics. After a successful course, you will be able to: Show familiarity with concepts within Explainable AI and interpretable machine learning. Demonstrate comprehension of current techniques for generating explanations from black-box machine learning methods. Demonstrate comprehension of current ethical, social and legal challenges related to Explainable AI. Demonstrate the ability to select and assess Explainable AI methods. Demonstrate the ability to review, present and critically assess state-of-the-art papers in relevant areas within Explainable AI.
Product and Production Platforms The course applies both theoretical and practical perspectives. This includes fundamental concepts together with current research and industrial practise in the area. Different means for planning, developing and analysing product and production platform design are introduced and practised. The impact on business processes of different platform strategies are discussed as well as their use in different sectors and applications. The course includes the following elements: Fundaments of product and production platforms theory Product platforms and related platforms in industrial practice Business opportunities and challenges associated with implementing and managing platform strategies Means to plan, design and analyse product and production platforms Models, methods, and tools used in product and production platform architecting and development The use of product platform strategies in different sectors and applications
APPLIED PRODUCTION FLOW SIMULATION By working with a simulation project at your company and supported by simulation-based optimization to locate the best productivity improvements, this course develops your skills to the next level to implement simulation projects as part of the production engineering work.