Cyber-Physical Systems and Intelligent Robotics Smart Engineering for Smart Factory

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1 Cyber-Physical Systems and Intelligent Robotics Smart Engineering for Smart Factory Professional Education Certificate Courses at the RWTH International Academy ggmbh

2 Preface A progressive digitalisation in industrial processes and production techniques will strongly alter industries all over the world. Intelligent production environments and interconnected factory systems will be part of the new industrial revolution. Industry 4.0 has immense potential: Companies willing to accompany the digital structural change and therefore expand their service portfolio can reveal their potential in optimisation with regard to production and logistics. In order to successfully implement Industry 4.0 into existing production environments, employees work and competence profiles need to be continuously expanded, both on specialist level and on management level. They need to be empowered and motivated to implement cyber-physical systems and intelligent robotics. This is important, because both operators and decision-makers are a vital part of the integration of machine and software systems into daily work routines. While operators are faced with adaption and optimisation processes, decision-makers need to develop strategies for implementation and take care of investment decisions. Each target group faces individual challenges and scopes of duties all of which need to be addressed by means of varied qualifications in training and continuing education. The RWTH International Academy caters to these needs by offering two certificate courses on this topic: Fundamentals to Smart Engineering for Smart Factory and Cyber-Physical Systems and Intelligent Robotics. 3

3 Are you ready for Industry 4.0? We offer different lifelong education courses to comply with your personal Industry 4.0 needs. Pick and Mix to enjoy your personal compilation of subjects. data acquisition & management industrial big data smartification cyberphysical systems Robot Operating System (ROS) human-robot collaboration machine-2- machine communication visual analytics in production computational graphics 3D-printing autonomous assistance systems intelligent robotics mobile robotics in-factory logistics embedded systems decentralisation & transformation 4 5

4 Target Group & Course Outline Cyber-Physical Systems and Intelligent Robotics (CPS-IR) This course is highly suitable for professionals who want to utilise the new possibilities enabled by the ongoing research on cyber-physical systems and intelligent robotics. The programme is therefore comprised of different modules covering particular aspects of CPS and intelligent robotics. Fundamentals to Smart Engineering for Smart Factory This course is suitable and highly recommended for mechanical or electrical engineers (at least bachelor level) who actively participate by contributing experiences from their daily work. Participants wishing to complete one of the CPS-IR levels can also choose this course as one of the advanced modules. Lifelong Learning With Topics on Industry 4.0 Certificate Courses Cyber-Physical Systems and Intelligent Robotics (CPS-IR) & Fundamentals to Smart Engineering for Smart Factory Please check the following pages of this booklet to learn more about the different modules, which can be attended both as individual courses as well as combined to complete one of our CPS-IR levels. Study format: certificate course, 3 different levels Date: from 24/04/2017 with differing lengths (cf. the following pages of this booklet) Prerequisites: Bachelor of Science/Bachelor of Engineering, professional experience of minimum 1 year Prof. Dr.-Ing. Meisen, Dr.-Ing. Sebastian Reuter Credit points: ranging from 2 to 15 ECTS Course fees: (single course), 10,800 (advanced certificate course, which is a bundle of 4 single courses), 18,000 (expert certificate course, combining 4 single courses, a field project and a case study) RWTH Certificates (Executive, Advanced, Expert) Language: English Study format: certificate course Date: 08/05 12/05/2017 Prerequisites: mechanical or electrical engineers (at least bachelor level) Dipl.-Ing. Markus Obdenbusch, Chief Engineer; Prof. Dr. Ing. Christian Brecher Credit points: 2 ECTS Course fees: RWTH Executive Certificate Language: English Course Contents The certificate course Cyber-Physical Systems and Intelligent Robotics (CPS-IR) provides methodical (a systematic toolbox of concepts and approaches) and technological (knowledge and implementation solutions) skills. Furthermore, participants will learn how to identify application areas of CPS as well as robotics in their company and how to encounter technological challenges with suitable methods. The advancement of digitalisation and the widespread networking of devices and systems open new automation and optimisation potentials. Terms like Cyber-Physical Systems (CPS) address technologies and concepts to realise the next generation of networked sensing capabilities and data propagation. For the industrial domain, these terms have been further specialised (e. g. cyber physical production systems). Thereby, the changes are characterised by manufacturing entities that are, on all levels, autonomous, in the sense that they incorporate planning systems and adjust themselves in response to changing environments. The certificate course Fundamentals to Smart Engineering for Smart Factory enables participants to learn the necessary steps to put into practice a complete digital chain of planning ranging from the product to a completed production process and beyond. Apart from classic topics like PLM (Product Lifecycle Management), the potential of frontloading is demonstrated by means of examples, i.e. from assembly technique. Various basics from the engineering science sector related to the challenges of the next fully digitalised production are conveyed with a focus on engineering. Theory will then be applied to participant-specific challenges with regard to digitalisation of production. Due to variable product families and constantly decreasing product life cycles, previous methods to implement machines, facilities and processes and operating machines cease to be economic. Rather, an increased front-loading meaning a deferral of efforts into engineering must take place in the future. Fortification of digital assembly groups with metadata, virtual figures of facilities and machines as well as methods of simultaneous process protection bear great potential

5 Communication in Modern Production Systems Course Schedule - Foundation Module Fundamentals to Smart Engineering for Smart Factory Course Schedule - Foundation Module This foundation course enables you to implement CPS and intelligent robots based on the concept of microservices and a modern communication middleware. As a result you will be able to interconnect these systems and form interactive information networks. This course offers practical units and an overview on the basic communication technologies in modern production facilities and a survey on common theoretical concepts as well as corresponding technologies that implement the concepts like OPC UA, DDS and RabbitMQ. In this foundation course semantic modelling in different application areas and middleware solutions that allow data centred communication in dynamic distributed systems will be exemplified. As a conclusion, you will implement an integrated solution on real hardware. In this certificate course you will learn the necessary steps to put into practice a complete digital chain of planning ranging from the product to a completed production process and beyond. Apart from classic topics like PLM (Product Lifecycle Management), the potential of frontloading is demonstrated by means of examples, i.e. from assembly technique. Various basics from the engineering science sector related to the challenges of the next fully digitalised production are conveyed with a focus on engineering. Theory will then be applied to participant-specific challenges in regards to digitalisation of production. This course serves as an introduction to technical requirements and challenges for the digitalisation of production, providing technical and engineering-based approaches and concepts for implementation. Day 1 Day 4 Day 1 // Introduction I Day 4 // Communication in Modern Production Systems I Introduction to communication networks in modern production systems (intra-device / device-2-device / machine-2- machine / machine-2-application / intra-factory) Making information explicit using ontology-based modelling Introduction to Industry 4.0 Enabling technologies for Industry 4.0 Challenge of consistent information flows - from engineering to production Innovative human machine inter-faces (production planning, operation...) Introduction to communication networks in modern production systems (intra-device / device-2-device / machine-2-machine / machine-2-application / intra-factory) From intra-device to inter-machine communication using DDS Modern robotics using microservices in ROS Day 2 Day 5 Day 2 // Introduction II Day 5 // Communication in Modern Production Systems II From intra-device to inter-machine communication using DDS Machine-2-machine communication using OPC UA Bringing it all together - holistic communication Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) New control paradigms for future production systems Smart automation lab Case Study: Industry 4.0 Optimization of exemplary production side Making information explicit using ontology-based modelling Machine-2-machine communication using OPC UA Bringing it all together - holistic communication Day 3 Day 3 // Product Lifecycle Management Modern robotics using microservices in ROS 04/09/ - 08/09/2017 Prof. Dr.-Ing. Tobias Meisen, Dr.-Ing., Sebastian Reuter, Dipl.-Ing. Max Hoffmann MBA, Dipl.-Ing. Thomas Thiele, Philipp Ennen M.Sc. Introduction to Product Lifecycle Management (PLM) // Software architectures and development processes // Data modelling and database systems // Robot based assembly and product lifecycle management (PLM), integrated, collaborative Robotics // Making information explicit using ontology-based modelling // Machine-2- machine communication using open platform communications (OPC), Unified architecture (OPC UA) // Bringing it all together - holistic communication tbd Dipl.-Ing. Markus Obdenbusch; Prof. Dr. Ing. Christian Brecher, Chief Engineer Dipl.-Ing. Thomas Thiele, Philipp Ennen M.Sc

6 Integrating, Mining and Analysing Data for Production Systems Course Schedule - Advanced Module Decision Making Using Expert-Systems and Machine Learning Course Schedule - Advanced Module A holistic communication enables information exchange and allows data to be gathered and stored. But how can this be achieved? This module aims at giving answers to this question. As participant you will deepen your knowledge in data consolidation and learn to use modern technologies to store and to analyse data. The analysis of data derived from CPS is the main topic of this module. As an introduction to industrial (big) data, architectures for data acquisition, integration and analysis will be presented. In this advanced course you will practice theoretical knowledge on a real production data set. You will learn how to interpret the structure and how to derive insights as part of the analysis. The increasing complexity within the decentral organisation of production plants which are capable of industry 4.0 necessitates assistance systems for humans who fulfill their respective roles within manufacturing. One approach is the integration of intelligent systems which as expert systems or via machine learning analyse production data and thereby automatically derive guidance. As participant you will understand how decision making and expert systems work and how they can be used in productive environments. Furthermore, you will get to know how modern concepts of machine learning can be used to develop intelligent and self-optimising systems. To support humans in CPS and robotic environments, data derived from these systems can be used as decision support. This advanced course covers the modelling of expert systems and introduces machine learning as a way to deal with the rising complexity in CPS and robotic environments. Day 1 Day 4 Day 1 Day 4 Industrial Big Data: Concepts and architectures Data analytics on production data Visual analytics in production Data representation & pre-processing Use Case Implementation: Decision support via machine learning I Appliance of machine learning on real time production data Day 2 Day 5 Day 2 Day 5 Integration of CPS data sources (towards Industrial IoT) Visual analytics in production Transforming data into information: Heuristics & rule-based systems Use Case Implementation: Decision support via machine learning II Human decision support: Modelling of results Day 3 Day 3 Integration of CPS data sources (towards Industrial IoT) Data analytics on production data 18/09-22/09/2017 Prof. Tobias Meisen, Dipl.-Ing. Thomas Thiele Transforming data into information: Machine Learning application design 25/09 29/09/2017 Prof. Tobias Meisen, Dipl.-Ing. Thomas Thiele, Dr.-Ing. Sebastian Reuter, Philipp Ennen M.Sc., Sebastian Schönitz, M.Sc., Christoph Henke

7 Robot Operating System (ROS) for Industrial Robots Course Schedule - Advanced Module In-Factory Logistics Using Mobile Robots Course Schedule - Advanced Module You will be able to implement CPS and intelligent robots based on the concept of ROS. First you get a short review of the communication infrastructure of ROS. Subsequently, you learn how to model and integrate various environments, actuators and sensors into the simulation environment Gazebo. You will be able to implement sensor- and hardware-drivers in simulation and on real robots. In addition, you learn and test fundamental methods for localisation, mapping and motion planning in ROS. You will integrate the key components of a mobile robot (hardware, sensory as well as localisation, mapping and Motion Planning Algorithms) in ROS. This advanced course introduces ROS middleware and its tools for developing modern robot systems. It covers the general structure of ROS and the usage of its publish-subscribe, service and action-server concepts. It offers a short introduction to the robot simulation Gazebo. You will understand the potentials of a flexible material flow and how to build adaptive production systems using mobile robots. You will learn methods for planning transport orders, coordinating a fleet of mobile robots and planning collision-free and efficient paths. Finally, you will implement and test the methods using a fleet of mobile robots. The latest procedures of planning tasks and pathways for intralogistical robots will be presented. A special focus lies on dependency and safety, as well as the implementation in the industrial realm. As a flexible flow of material is a prerequisite for adaptive production systems, in this advanced course you will learn how to make intralogistics more flexible via mobile robots. Day 1 Day 4 Day 1 Day 4 ROS basics I: Basic structure of ROS programmes (Publish<->subscribe and services) Using ROS to make a robot move I: writing sensor- and hardware-drivers Introduction to mobile robots for in-factory logistics Trajectory generation and reactive collision avoidance for mobile robots Day 2 Day 5 Day 2 Day 5 ROS basics II: How to create action services and how to debug programmes Using ROS to make a robot move II: localisation, mapping and motion planning Task planning of transport-orders Definition of basic robot skill for monitoring task and path execution and material handling Day 3 Day 3 GAZEBO basics: simulating the world Planning global paths for a fleet of mobile robots 16/10-20/10/2017 Dr.-Ing. Sebastian Reuter, Philipp Ennen M.Sc., Christoph Henke 23/10 27/10/2017 Dr.-Ing. Sebastian Reuter, Philipp Ennen M.Sc., Sebastian Schönitz, M.Sc, Christoph Henke

8 Cyber-Physical Systems and Intelligent Robotics Examplary Curriculum Pick & Mix - your choice, your career, your future! Please note that all of the modules below need to be attended in the indicated order for the purpose of completing either the Advanced Course or the Expert Training. Nevertheless, they can also be selected separately as individual courses, each lasting 5 days and finishing with the RWTH Executive Certificate. Short Intensive Certificate Foundation Module Communication in Modern Production Systems Overview on the basic communication technologies in modern production facilities, offering a survey on common theoretical concepts as well as corresponding technologies that implement the concepts like OPC UA, DDS and RabbitMQ. Quick Facts each separate module lasts 5 days on-campus attendance (RWTH Aachen, Germany) 2 ECTS qualification: RWTH Executive Certificate Expert Training Advanced Certificate Course Advanced Modules Expert Module Integrating, Mining and Analysing Data for Production Systems Case Study and Field Project Including Decision Making Using Expert-Systems and Machine Learning Robot Operating System (ROS) for Industrial Robots In-factory Logistics Using Mobile Robots Fundamentals to Smart Engineering for Smart Factory One of the advanced modules serves as a basis for the individual case studies. Whilst attending your chosen modules, you conduct your own hands-on example of implementing its theoretical aspects, finishing the study back in your companies. The examination task can be individually chosen (e.g. daily-work related) or assigned. You will have to document how you solved the task and present and defend your solution. Quick Facts Foundation Module plus 3 advanced modules of 5 days each on-campus attendance (RWTH Aachen, Germany) 8 ECTS qualification: RWTH Academic Certificate Quick Facts Foundation Module plus 3 advanced modules of 5 days each necessary to attend this level on-campus attendance (RWTH Aachen, Germany) & blended learning 15 ECTS qualification: RWTH Expert Certificate

9 Your Lecturers Prof. Dr.-Ing. Tobias Meisen Junior Professor and Head of Institute of Information Management in Mechanical Engineering (IMA) of RWTH Aachen University Expert topics: data integration and analytics in production, heterogeneous ICT, industrial big data Dr.-Ing. Sebastian Reuter Research Group Leader Technical Cybernetics Expert topics: control and navigation of mobile robots, inter-robot cooperation Dipl.-Ing. Thomas Thiele Research Group Leader Production Technology Expert topics: data analytics in production, knowledge management Dipl.-Ing. Max Hoffmann MBA Research Group Leader Big Data Analytics Expert topics: Industry 4.0 ready communication and information technologies (OPC UA, DDS, ) Philipp Ennen M.Sc. Researcher at IMA (Institute of Information Management in Mechanical Engineering) Expert topics: learning motion skills, human-robot cooperation Christoph Henke M.Sc. Researcher at IMA (Institute of Information Management in Mechanical Engineering) Expert topics: mobile robotics in intralogistics, path planning, motion generation Why choose us? Sebastian Schönitz M.Sc. Researcher at IMA (Institute of Information Management in Mechanical Engineering) Expert topics: expert system, inter-agent cooperation, automated planning We provide thoroughly English-taught continuing education at the RWTH Aachen University in Germany, with the scientific leadership of highly qualified university professors and scientists. Your trainers are technology experts of the RWTH Aachen University with a scientific and didactic background as well as a broad experience from industrial projects. Course contents are directly applicable to the challenges in your companies, enabling you to develop and employ your own 4.0 strategies. A strong focus lies on networking and communication amongst participants and lecturers. You will receive an official RWTH Aachen University certificate which shows both course contents and course aims. Prof. Dr. Ing. Christian Brecher Professor and head of Institute of Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University Expert topics: transmission technology Dipl.-Ing. Markus Obdenbusch Chief Engineer at Institute of Laboratory for Machine Tools and Production Engineering (WZL) Expert topics: automisation and control engineering Industry 4.0 Experience Demonstration Factory and Innovation Labs as Real-Life Experimental Framework The Demonstration Factory and the innovation lab of our smart logistics cluster serve as a real-life experimental environment for Industry 4.0. Participants can test the governance of the actual employment of machines and personnel in real-time to implement lean production processes. The innovation labs test new technologies like sensors or the intercommunication between different IT-system environments. Thilo Vogel Scan for visual information on our Smart Automation Lab

10 Organisation and Application Cyber-Physical Systems and Intelligent Robotics (CPS-IR) and Fundamentals of Smart Engineering for Smart Factory Venue and Scope Both certificate courses are conducted at RWTH Aachen University (Germany) with a scope of 5 days. The Advanced and Expert Training variants of CPS-IR exceed this scope. For further information refer to pages 14 and 15 of this booklet. Number of Participants To ensure individual learning success and lively discussions between participants and lecturers, the maximum number of attendees does not exceed 15 people. Didactics and Language The courses combine different teaching methods such as lectures, group works, blended learning and practical examples. Course language is English, therefore both the comprehensive course documents as well as presentations will be provided in English. Test Performance and Certificate Upon successful completion of the chosen course, both of which conclude with a written exam, participants will receive an official RWTH University certificate. Course Fees The certificate course Fundamentals to Smart Engineering for Smart Factory costs. The certificate course Cyber-Physical Systems and Intelligent Robotics (CPS-IR) ranges from to 18,000, depending on the chosen degree. Course papers, catering and framework programme are included, whereas lodging and travel expenses will be at participant s own costs. Application You can apply via the online application form on weiterbildung.rwth-aachen.de/en/technology-production or via to further-education@academy.rwth-aachen.de We will be happy to answer any of your queries, so please do not hesitate to contact us: Sonja Kaufmann Programme Coordinator Engineering & Natural Sciences RWTH International Academy Tel: +49 (0) S.Kaufmann@academy.rwth-aachen.de For further information and to access the application form please visit our website: If you wish to download this broschure as pdfdocument:

11 Imprint editor: RWTH International Academy ggmbh Campus-Boulevard Aachen I Germany Telefon: further-education@academy.rwth-aachen.de pictures: RWTH International Academy ggmbh, Thilo Vogel, fotolia published: January 2017, first edition

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