ROBOT SYSTEM 1

The purpose is to give the students an overview of issues and methods for development and assurance of safety-critical software, including details of selected technologies, methods and tools.

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.

The starting point for the course is Lean Production, with an understanding of principles and concepts that can lead to higher efficiency. Then we introduce computer-based application for modelling and simulation of production systems. This provides the opportunity to simulate a production system, perform experiments on it according to different conditions, and optimize the system to increase efficiency. This course is for professionals who work with production systems at different levels with a responsibility for individual production lines, departments, or has a role as production manager or production development. The course will mainly focus on the manufacturing industry in application examples, but principles that will be addressed will be applicable to a number of industries, including consulting companies working towards the manufacturing industry. The course contains the following: Production systems and concepts such as Industry 4.0 and Smart Industry Lean Production and workshop with the Lean game Programming exercises with event-based simulation of production systems Analysis and optimization of production systems The majority of the course will take place on Campus (Växjö), and at a distance according to the schedule below. Some of the exercises are preferably attend on Campus, but we plan for it to be possible to follow the full course at a distance due to the Covid-situation.

With the ongoing digitalization of the industry towards "Industry 4.0" i.e. smart factories with more efficient production, shorter lead times, higher quality, etc. increase the need to measure different quantities and associated processing of this measurement data. This includes the collection of signals via different types of sensors and signal processing of these signals in order to e.g. provide "smart industrial cyber-physical systems" (SICPS) with information for the purpose of monitoring, maintaining, controlling activities, etc. in order to achieve smart factories. The course will focus on sensors, analog-to-digital converters, quality of measured data and signal processing where we, among other things, highlights the choice of sensors and data collection systems and introduces some robust signal processing methods in the light of the digitization of the industry. This course is for professionals who work professionally with programming and development - regardless of industry or sector. You may be in the industry, the IT sector or a larger company in a completely different industry, you may be working in a development department within a company or as an IT consultant or. The course contains the following: Sensors for measuring vibrations, force, elongation, speed and associated signal conditioning Measurement uncertainty Analog-to-digital converter and "Effective Number Of Bits (ENOB)" Folding when sampling signals and anti-folding filters Fourier transform - Discrete Fourier transform Stochastic processes and relevant statistical concepts Power density spectrum, Power spectrum and associated systematic and random errors

You will acquire knowledge about planning and implementing industrialization activities for achieving a faster time-to-market and time-to-volume with higher quality. During the course you will work on one of your company’s industrialization challenges as a “project case” and analyse ways to tackle them in an efficient way.

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.