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Using an interdisciplinary demonstration platform for teaching Industry 4.0
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Procedia Manufacturing 00 (2019) 000–000 Procedia Manufacturing (2019) 000–000 Procedia Manufacturing 31 00 (2019) 302–308 Procedia Manufacturing 00 (2017) 000–000
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9th Conference on Learning Factories 2019 9th Conference on Learning Factories 2019
Using an interdisciplinary demonstration platform for teaching Using an interdisciplinary demonstration platform for teaching Industry 4.0 Industry Conference 4.0 Manufacturing Engineering Society International 2017, MESIC 2017, 28-30 June
a,b 2017,Walter Vigo (Pontevedra), Spain Jeffrey Wermanna,b,∗ , Armando Colomboa,b a,b , Agnes Pechmanna,b , Maximilian a Jeffrey Wermanna,b,∗, Armando Walter Colombo , Agnes Pechmann , Maximilian Zartea Zarte a Costing models for capacity optimization in Industry 4.0: Trade-off University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26721 Emden, Germany a University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26721 Emden, Germany f¨ur Informatik, Automatisierungstechnik und Robotik (I2 AR), Constantiaplatz 4, 26721 Emden, Germany f¨ur Informatik, Automatisierungstechnik und Robotik (I2 AR), Constantiaplatz 4, 26721 Emden, Germany
between used capacity and operational efficiency
b Institut b Institut
A. Santanaa, P. Afonsoa,*, A. Zaninb, R. Wernkeb Abstract Abstract a of Minho, 4800-058 Guimarães, Portugal Industry 4.0 is based on a set of concepts, University technologies and organizational processes affects various areas in engineering education b Unochapecó, 89809-000 Chapecó, SC, Brazil Industry 4.0 is based on a set of concepts, technologies and organizational processes affects various engineering education and beyond. It includes internet-based networking of digitalized mechatronics components on theareas shopinfloor with management and beyond. It includesby internet-based networking of digitalized mechatronics the shop floor with management and business platforms applying technologies from the IT sector. Even socialcomponents aspects are on targeted, as the human being is also and businesstoplatforms fromSystem the IT sector. aspects targeted, institutions as the human also considered be a partby of applying Industrialtechnologies Cyber-Physical (ICPS).Even The social challenge for are educational is being to dealis with considered to be a part of Industrial The challenge for educational institutions is toeach deal other with this broad spectrum. Departments andCyber-Physical institution withSystem different(ICPS). specialization are required to work more closely with Abstract this Departments and institution different specialization required of to the work more closely with each other to bebroad able spectrum. to teach the topic of Industry 4.0 in allwith its dimensions. One of the are approaches University of Applied Sciences to be able to isteach the topic of Industry in all departments its dimensions. thecollaborate approachesand of use the itUniversity of various Appliedaspects Sciences Emden/Leer to build a platform, where 4.0 different canOne workofon, to teach the of Under concept of "Industry production processes be pushed to use be which interconnected, Emden/Leer to build a platform, different departments can work collaborate and itincreasingly to teach the various of Industrythe 4.0. is This platform is calledwhere the4.0", “Automated Class Room” and iswill a on, physical demonstrator, consists of manyaspects different Industry 4.0. This platform is called the “Automated Class Room” and is a physical demonstrator, which consists of many different information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization modules from different departments, such as mechatronic machines, simulation tools, management tools, logistics systems which modules from into different departments, as mechatronic machines, simulationalso tools, tools,profitability logistics systems which goes beyond the traditional aim ofsuch capacity contributing formanagement organization’s and value. are integrated an Industry 4.0 compliant ICTmaximization, (information-communication technologies) architecture. This paper provides an are integrated an Industry compliant ICT (information-communication technologies) architecture. Thistarget paperaudiences. provides an overview aboutinto the platform and4.0 discusses in depth how it is currently used for teaching Industry 4.0 to different It Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of overview the platform and discusses in depth how is currently used teaching Industry tocan different target audiences. It describes about in which parts the individual departments and itspecific courses setfor their and how 4.0 they demonstrate thedeserves benefits maximization. The study of capacity optimization and costing models isfocus an important research topic that describes in 4.0 which parts the individual departments and specific courses set their focus and how they can demonstrate the benefits of Industry for students but also for visitors of the university and enterprises. Furthermore, the “Automated Class Room” is contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical of Industry 4.0 for test students but also for visitors different of the university and can enterprises. Furthermore, the “Automated Class is used as for a practical bed, where students departments learn together how to implement Industry 4.0Room” concepts model capacity based from on different costing models (ABC and TDABC). A generic model has been used as a practical testmanagement bed, where students from different can learn together how in to the implement and technologies. The paper also gives an overview about departments how the platform is going to evolve future. Industry 4.0 concepts developed and it The waspaper used also to analyze capacity and to design strategies towards theinmaximization of organization’s and technologies. gives anidle overview about how the platform is going to evolve the future. value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity c 2019 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. © optimization might operational inefficiency. c 2019 The under Authors. Published by Elsevier B.V. committee of the 9th Conference on Learning Factories. Peer review thehide responsibility of the scientific Peer review under thePublished responsibility of the scientific committee of the 9th Conference on Learning Factories. © 2017 The under Authors. by Elsevier B.V. committee Peer review the responsibility of the scientific of the 9th Conference on Learning Factories. Keywords: Industry 4.0; Learning Platform; Industrialcommittee Cyber-Physical Systems Peer-review under responsibility of the scientific of the Manufacturing Engineering Society International Conference Keywords: Industry 4.0; Learning Platform; Industrial Cyber-Physical Systems 2017. Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency
1. Introduction 1.1.Introduction Introduction The effective information-driven interaction among ICPS on the shop floor and enterprise information systems, effective information-driven interaction amonglife ICPS on the shop and enterprise information systems, The cost capacity is a fundamental forcycles, companies andfloor their management extreme and importance extending toofallidle business processes along theinformation different is viewed as vital to modernofindustries constiextending to all business processes along the life cycles, is viewed as vital to modern constiin modern production systems. In general, it is different defined as unused capacity or production potentialindustries and can beand measured in several ways: tons of production, available hours of manufacturing, etc. The management of the idle capacity Corresponding author. Tel.: +49(0)4921/807-1948. *∗ Paulo Afonso. Tel.: +351 253 510 761; fax: +351 253 604 741 ∗ Corresponding author. Tel.: +49(0)4921/807-1948. [email protected] E-mail address: [email protected] E-mail address: [email protected] c 2017 2351-9789 © 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. 2351-9789 c 2019the 2351-9789 The Authors. Published by Elsevier B.V. of the 9th Conference on Learning Factories. Peer review responsibility of the scientific committee Peer-review under under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017. Peer review under the responsibility of the scientific committee of the 9th Conference on Learning Factories. 2351-9789 © 2019 The Authors. Published by Elsevier B.V. Peer review under the responsibility of the scientific committee of the 9th Conference on Learning Factories. 10.1016/j.promfg.2019.03.048
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tutes the core of the 4th Industrial Revolution [3]. Specifically in Germany, this industrial revolution has a concrete scientific, technical and particular industrial background founded on the fussion of industrial norms and standards, and formally grounded on a new DIN (Deutsche Industrie Norm) specification: the Reference Architecture Model for Industrie 4.0 (RAMI4.0) [6]. Note: The amalgamation of concepts, technologies, engineering methodologies behind Industrie 4.0 is recognized world-wide under the English denomination ”Industry 4.0”. Though the concepts behind, the engineering methods and tools and technologies for Industry 4.0 and ICPS get more defined, elaborated and mature, the challenges for learning, applying and working with them, i.e. living in an Industry 4.0 environment, are hard to grasp, for experts, industrialist and practitioners, but even more for students [4]. Teaching concepts and methods to prepare students for learning Industry 4.0, i.e. about digitalized and virtualized industrial building blocks, things (Industrial Internet of Things - IIoT), assets (RAMI4.0 [6]), which work interconnected through several communication and information networks including the Internet, collaborating and providing citizens and businesses with a wide range of innovative applications along the product and production process life-cycle, based on digitalized data, information and services (e.g. computing, simulating, analyzing, making decisions, communicating, etc.) [3], have successfully been applied at the University of Applied Sciences Emden/Leer, Germany since 2010 [8]. These methods are basically based on experiences and a set of considerable lessons learned by teaching “digitalization of industrial production systems applying the service-oriented architecture (SoA) paradigm” [2]. Basically, a combination of different Teaching/Learning methods have been developed further and applied [1]. This includes the creation of a new international Master Engineering Degree program on Industrial Informatics with specialization on Industrial Cyber-Physical Systems. The learning methods are focusing particularly on 4 major steps: (i) linking theory related to the Industry 4.0 paradigm learned in the classroom with the analysis of published research results, the screening of industrial patent applications complemented with acquisition and analysis of requirements of the industry, done by the students, (ii) transferring this acquired knowledge to prototype innovations and implementations in a digital factory model of the university performed by teams of 2-3 students each, (iii) transferring some of those prototype and the acquired foreground know-how to the industry, and (iv) disseminating the research and innovation results performed by those students of the Master Industrial Informatics, in an international context (see e.g. [13], [9], [11], [12]). With the aim of extending and improving the results of the experiences addressed above, in this paper and following this introduction section, major challenges for teaching concepts and methods to prepare students for learning Industry 4.0 in a multidisciplinary context are introduced in section 2. In section 3 follows the description of the major specifications of a multidisciplinary demonstration platform called ”Automated Class Room” that is being developed and implemented at the University of Applied Sciences Emden/Leer, Germany. Section 4 describes different applications of that platform followed by a summary of current state of those applications and of first achieved results in section 5. Finally, section 6 rounds up the paper with the conclusion and outlook.
2. Challenges for learning to work with Industry 4.0 2.1. Summary of main challenging features of Industry 4.0-compliant solutions Industry 4.0 and Industrial Cyber-Physical Systems (ICPS) forge the core of real-world networked industrial infrastructures having a cyber representation through the digitalization of data and information and the exposition and/or consume of services horizontally and vertically across the enterprise, along the product, production order and process engineering life cycles, and from supplier to customers along the collaborative supply chain network. As such, the quality and the competitive performance of an Industry 4.0-compliant solution depends, among others, on the ability: i. to effectively generate digitalized data and information, in real-time, from different and often heterogeneous networked physical and cyber sources, having in mind that those physical systems are mainly mechanical, hydraulic, pneumatic, electrical, but also documentation, technical design draws, production and maintenance orders, etc. ii. to collect, analyze and use large-scale digitalized data and information for supporting functionalities in the different phases of the named life cycles and within the enterprise ICT architecture
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iii. to sustainably and efficiently manage, supervise and operate the cyber and the physical components and systems in the industrial environment, having in mind that those systems are mainly geographically distributed, are structurally evolvable and present emergent behaviors from functional point of view (i.e. application of the CyberPhysical-Systems-of-Systems paradigm [5]) iv. to facilitate the vertical OT/IT (Operational Technology/Information Technology) as well as horizontal OT/OT and IT/IT connectivity among components and systems v. to guarantee the interoperability of components and systems by using a consistent data model and data transport technology along the life cycles vi. to combine the application of sometimes disjoints industry norms and standards in order to make the solution. vii. to effectively integrate the human actors along the value chain, so that they are able to interact and possibly collaborate with the rest of the networked Industrial Cyber-Physical Systems. 2.2. Major requirements for teaching Industry 4.0 to students As explained before, Industry 4.0 means mainly the confluence of mechatronics, information, communication, computer networks and data and information processing and the penetration and co-existence of all these hardware and software technologies into the industrial environment. Looking to this multi-disciplinary domain and taking into account the traditional engineering study programs, on the one side, the main challenges for a mechanical engineering or industrial engineering student is to cover its non-familiarity of the concrete background about ICT infrastructures, i.e., enterprise control and management architectures, communication and information technologies, computer networks, digitalization and modelling of data and information, specifying and implementing cyber aspects of a production system, etc. Concretely, learning and understanding the informatization, digitalization and networking of the industrial ecosystem. The main challenge for a lecturer/professor is teaching mechanical and industrial engineering graduates for working with the cyber-part, mainly software, information and communication within an Industry 4.0 environment. On the other side, students of the informatics and in general computer sciences and sometimes also of the electronics and electrotechnic need to be instructed how to deal in respect to the physical aspects of Industrial Cyber-Physical Systems behind Industry 4.0. How far are they familiar with the value creation processes in the production systems and collaborative networks? Are they familiar with productivity measures, maintenance aspects and yield aspects? How does the used terminology differ? How do the standards of report writing differ? It is very difficult if not impossible to digitalize and informatize a production system for migrating it into an Industry 4.0-compliant solution if the basic structural and functional specifications of the physical components, mainly hardware and their life cycle specifications, are not well understood. It is very difficult if not impossible to digitalize and to informatize a production system for migrating it into an Industry 4.0-compliant solution if the basic structural and functional specifications of the physical components, mainly HW and their life cycle specifications, i.e., at least the product and factory life cycle as a framework for learning factories [1], are not well understood. At this point the necessity to have a ”Demonstration Platform” where many if not all those specifications of Industry 4.0-compliant solutions can be designed, implemented, tested, optimized, etc, in a multi-disciplinary fashion is clear. Despite of the necessary initial investments in acquiring and installing industrial SW/HW components and systems at the university site [4] [13], at this point is clear that it is unavoidable to have a “Demonstration Platform” for implementing the approach described in this paper. The major advantage, a concrete ROI, is to count on an industrially relevant environment where many if not all the specifications of Industry 4.0-compliant solutions can be designed, implemented, tested, optimized, etc. by all involved actors (teachers, students, etc.) in a multidisciplinary fashion. 3. Demonstration Platform ”Automated Class Room” For several years working on individual aspects of Industry 4.0 have already been covered in laboratories and specific learning platforms within the University of Applied Sciences in Emden. For example, the Institute I2 AR
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has built a fully automated production system, which allowed the collaboration of different industrial automation devices (e.g. robots, conveyor belt systems, storage systems) to produce individualized products based on the concept of Service-oriented Architecture [13]. The focus of this platform lies on important aspects such as digitalization of automation systems, communication and integration technologies for vertical and horizontal integration and migration approaches [12] [15] [7]. Other aspects like applying the digitalization benefits in production and logistics are more strongly focused in the laboratory of production planning (PPS-Lab). The PPS-Lab has strong history in using Enterprise Resource Planning (ERP) systems and serious games to teach interdisciplinary challenges in production systems [14]. Based on the existing expertise, the Institute I2Ar and the PPS-Lab initiated building an additional platform, which combines the different lessons learned in the Industry 4.0-related fields of knowledge in one system. This system will then act as a common platform for all involved stakeholders to teach, practice and demonstrate the specific aspects of Industry 4.0 which they are covering. 3.1. General Idea The first step to build this platform was to identify the collaborators within the university, which are related to the topic of production systems and which cover specific aspects of an Industry 4.0 system. Based on the knowledge and experience of these collaborators (see [10]), necessary modules were identified, (i) necessary aspects which have to be covered by the platform as well as the concepts for the implementation of the installation were defined and (ii) the integration of already existing modules with new hardware/software and technologies were considered. The underlying Industry 4.0-related concept for this platform is the modularity. Each functional module can be used to focus on specific aspects and can be operated independently from the rest of the system, if necessary. In addition, also the combined operation of all modules is required. This approach should both work in a decentralized way, where the individual systems are located in their respective laboratories, but also in a centralized setup, where all modules are placed together. This allows the use of the system as a demonstration platform for exhibitions and other events. The system is also required to be open for future changes and addition of new components. The selected name for the platform is the ”Automated Class Room” to show the target of being applied as a learning platform, but also showing the relation to automation and digitalization. To build a basic setup for the ”Automated Class Room”, oriented to learn and work in an Industry 4.0-compliant environment, a first set of collaborators from the following areas and departments has been selected: (i) Industrial Informatics, (ii) Industrial Automation, (iii) Industrial Communication Technologies, (iv) Production Management and Control, (v) Supply Chain and Logistics, (vi) Laser Technology, (vii) Material Sciences and Mechanical Design, etc. The inclusion of the areas of Material Science and Mechanical Design covers all aspects related to the products which are being handled through the platform, as well as the necessary machinery to produce these products. Specifically, the requirement was to include laser engraving and 3D printing processes, since they allow an easy application of customer-specific individualization of the product. Stakeholders from the fields of Industrial Automation, Industrial Informatics and Industrial Communication Technologies are involved to digitalize these machines and the products. This includes applying concepts to integrate hardware and software systems, which are not already Industry 4.0 compliant, as well as defining an information and communication architecture. The information generated by the digitalized machinery and products can then be used by additional production management and control systems, such as Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES) to handle customized orders and controlling the production process. Additionally, virtualized and simulated representations of the platform are using the information to calculate valuable key performance indicators. The whole setup is then also considered from a supply chain management and logistics perspective. 3.2. Hardware Setup and Digitalization Approach Within the first setup, the aforementioned domains have been considered to build a system consisting of the modules illustrated in Figure 1(a). The setup consists of two machines, a laser engraving machine and a 3D printer,
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Fig. 1. (a) Overview of Hardware setup of the Automated Class Room; (b) Adapters for REST implementation.
but is supposed to be extended with additional equipment over time (e.g. storage and packaging stations, additional processing machines, etc.). Each machine builds its own module to be integrated and digitalized for the platform. If put together, a collaborative robot (cobot) is used to handle the products and transfer them between the different modules. The whole system is connected to an ERP/MES server, which handles the production planning and execution of the production. A Web Shop is acting as the interface to the customer. Since the goal for the platform is to integrate all modules of the system into an Industry 4.0 environment, each of the modules – which themselves (many of them) are not typically ready for Industry 4.0 by default – needs to be digitalized. The strategy for digitalizing each module is based on applying the Service-oriented Architecture (SoA) concept [2] [13]. The application of the SoA approach allows that each module gets networked through the internet, being able (1) to offer its functionalities and/or (2) consume functions from other modules of the networks as “services” (i.e. applying Internet-of-Services (IoS) technologies). Related to the application of the SoA approach, many established ICT exist, such as SOAP, REST or the Industry 4.0 related OPC-UA [9]. The technology of choice for the first implementation is REST, since it is easy to develop while still providing the necessary behaviour. To allow the individual modules to be SoA-based networked using REST technology, additional adapter solutions need to be developed. These adapters will take the machine or software specific interfaces and set up a REST interface on top of them. For example, the ERP/MES system used within the platform doesn’t provide a REST interface on its own and just stores its data inside a database. This data is picked up by an adapter using SQL queries and translated in corresponding REST resources. In another example, the 3D printing machine also needs to be attached with a REST adapter, which, among other functions, allows the 3D printer to pull production orders from the ERP and executes these orders on the 3D printer. Figure 1(b) provides an overview about the adapters. 3.3. Envisioned processes There are currently two processes envisioned to be covered by the platform. In both cases, a user is able to enter individualized orders for a product into a Web Shop, which is connected to the ERP/MES and is able to trigger the creation of a new order within the system. The first product a pen, which is processed by the laser engraving machine and which allows the customer to engrave a text of his choice on the pen. The second product is a 3D printed business card, where the customer can select a logo to be printed and the contact details which the business card should have. 4. Using the ”Automated Class Room”. Exemplary Use Cases The main application for the Automated Class Room platform are teaching purposes within the university. Teaching Platform for individual aspects: The individual modules of the system can be used on their own without the interaction with other systems. This way, parts of the system can be used to target specialized aspects
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of the system. For this use, the platform does not need to be assembled in one spot as a whole. For example, the ERP/MES module is used within courses related to production planning and industrial engineering students in practical exercises or projects can specifically focus on the ERP/MES system itself, while still having a clearly defined implementation goals (e.g. configuring the system to allow the order of business cards and pens). Another example is the digitalization part, where students from the Master on Industrial Informatics need to investigate information/communication technologies as well as to develop solutions to migrate specific modules, digitalizing them for working in a SoA-based manner. Teaching Platform to integrate the whole system: The requirement for this use case is that basic functionality within the modules is already setup. If this is done, the platform can be used as a learning platform for bringing interdisciplinary groups together to solve a problem. To get to whole system running, students from various backgrounds need to collaborate. This kind of integration work needs a high amount of communication and specification to be able to link up the individual parts. The data and the SoA-based interfaces to transport the data need to be aligned as well as the service-oriented functionality developed within each module. Exemplary demonstration platform: With all modules implemented and working together, the whole platform during its operational state can also be used as a full running example for students to see a system designed with Industry 4.0 characteristics running. This way, the students but also teachers and other actors as e.g. participants of exhibitions both in class as well as fairs, can see in a live demonstration, where the benefits for Industry 4.0 are (e.g., vertical and horizontal SoA-based connectivity, structural and functional reconfigurability, virtualization of modules/simulation-in-the-control and –management-loops, etc.) and how such a system can look like.
5. Current State and first results The aforementioned results have started to being implemented and are used in practice. Since the whole idea consists of multiple modules and is open to changes and additions, the platform is not finished yet. In fact, the goal is to continuously improve and enhance the system, which implies that there is no clearly defined ”final” state. The first activities were focusing on implementing a basic setup including the laser engraving machine, the 3D printer and the ERP/MES system. This way, both horizontal (machine to machine) and vertical (machine to MES/ERP) connectivity can be demonstrated and a whole production process can be demonstrated. The process includes the generation of a production order within the ERP. This order includes customized information regarding the desired product. Depending on the selected product (either a business card or a pen), the related machine is capable to fetch the new order via ”services” from the ERP/MES and adapt its program to the selected custom parameters. The communication is done using a REST-based communication architecture, where the ERP/MES provides order-specific information as REST resource. This setup has been successfully implemented through various student projects. So far, students from the fields of Computer Science (Bachelor), Mechanical Engineering (Bachelor and Master) and Industrial Informatics (Master) have been active in the development. The result is a first demonstration setup, which is used for showcasing the platform internally as well as externally, based on the use cases described in Chapters 4 to 4.
6. Conclusion This paper has described an interdisciplinary approach and the development of a first setup of an Industrial CyberPhysical Systems Platform, called “Automated Class Room”. After describing the current use of the platform for learning Industry 4.0-related concepts at the University of Applied Sciences Emden/Leer, Germany, the manuscript highlights the impact of such a learning platform for use case demonstrations as well as for the realization of student projects. Future works will include not only the realization of new student projects to continue developing the work on the platform, but also the use of the learning approach and platform in different bachelor- and master-engineering curricula within the university.
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References [1] Abele, E., Chryssolouris, G., Sihn, W., Metternich, J., ElMaraghy, H., Seliger, G., Sivard, G., ElMaraghy, W., Hummel, V., Tisch, M., Seifermann, S., 2017. Learning factories for future oriented research and education in manufacturing. CIRP Annals 66, 803 – 826. URL: http:// www.sciencedirect.com/science/article/pii/S0007850617301440, doi:https://doi.org/10.1016/j.cirp.2017.05.005. [2] Colombo, A., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., Harrison, R., Jammes, F., Lastra, J.L., 2014. Industrial Cloud-Based Cyber-Physical Systems: The IMC-AESOP Approach. Springer Publishing Company, Incorporated. [3] Colombo, A.W., Karnouskos, S., Kaynak, O., Shi, Y., Yin, S., 2017. Industrial cyberphysical systems: A backbone of the fourth industrial revolution. IEEE Industrial Electronics Magazine 11, 6–16. doi:10.1109/MIE.2017.2648857. [4] Colombo, A.W., Schleuter, D., Kircher, M., 2015. An approach to qualify human resources supporting the migration of smes into an industrie4.0-compliant company infrastructure, pp. 003761–003766. doi:10.1109/IECON.2015.7392687. [5] CPSoS, . Cpsos - definitions used throughout the project. URL: http://www.cpsos.eu/project/ what-are-cyber-physical-systems-of-systems/. [6] DIN Deutsches Institut f¨ur Normung e.V., 2016. DIN SPEC 91345:2016-04: Referenzarchitekturmodell Industrie 4.0 (RAMI4.0). [7] Gosewehr, F., Wermann, J., Colombo, A.W., 2016. Assessment of industrial middleware technologies for the perform project , 5699– 5704doi:10.1109/IECON.2016.7793611. [8] G¨otting, M., Gosewehr, F., M¨uller, M., Wermann, J., Zarte, M., Colombo, A.W., Pechmann, A., Wings, E., 2017. Methodology and case study for investigating curricula of study programs in regard to teaching industry 4.0, pp. 533–538. doi:10.1109/INDIN.2017.8104828. [9] Haskamp, H., Meyer, M., Mollmann, R., Orth, F., Colombo, A.W., 2017. Benchmarking of existing opc ua implementations for industrie 4.0-compliant digitalization solutions , 589–594doi:10.1109/INDIN.2017.8104838. [10] N.N., . AKZ project page. University of Applied Sciences Emden/Leer. URL: https://www.hs-emden-leer.de/fachbereiche/ technik/labore/produktionsplanung/akz/. [11] Schulte, D., Colombo, A.W., 2017. Rami 4.0 based digitalization of an industrial plate extruder system: Technical and infrastructural challenges, pp. 3506–3511. doi:10.1109/IECON.2017.8216593. [12] Wermann, J., Kliesing, N., Colombo, A.W., Moraes, E.C., 2015a. Impact of new ict trends for the educational curriculum in the area of industrial automation and engineering. doi:10.1109/IECON.2015.7392667. [13] Wermann, J., Moraes, E.C., Colombo, A.W., 2015b. A service-oriented architecture implementation in the digital factory of the university, Springer International Publishing, Cham. doi:10.1007/978-3-319-22867-9_7. [14] Zarte, M., Pechmann, A., 2017. Concept for introducing the vision of industry 4.0 in a simulation game for non-it students, pp. 512–517. doi:10.1109/INDIN.2017.8104825. [15] Zarte, M., Pechmann, A., Wermann, J., Gosewehr, F., Colombo, A.W., 2016. Building an industry 4.0-compliant lab environment to demonstrate connectivity between shop floor and it levels of an enterprise , 6590–6595doi:10.1109/IECON.2016.7792956.
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Procedia Manufacturing 00 (2019) 000–000 Procedia Manufacturing (2019) 000–000 Procedia Manufacturing 31 00 (2019) 302–308 Procedia Manufacturing 00 (2017) 000–000
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Using an interdisciplinary demonstration platform for teaching Using an interdisciplinary demonstration platform for teaching Industry 4.0 Industry Conference 4.0 Manufacturing Engineering Society International 2017, MESIC 2017, 28-30 June
a,b 2017,Walter Vigo (Pontevedra), Spain Jeffrey Wermanna,b,∗ , Armando Colomboa,b a,b , Agnes Pechmanna,b , Maximilian a Jeffrey Wermanna,b,∗, Armando Walter Colombo , Agnes Pechmann , Maximilian Zartea Zarte a Costing models for capacity optimization in Industry 4.0: Trade-off University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26721 Emden, Germany a University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26721 Emden, Germany f¨ur Informatik, Automatisierungstechnik und Robotik (I2 AR), Constantiaplatz 4, 26721 Emden, Germany f¨ur Informatik, Automatisierungstechnik und Robotik (I2 AR), Constantiaplatz 4, 26721 Emden, Germany
between used capacity and operational efficiency
b Institut b Institut
A. Santanaa, P. Afonsoa,*, A. Zaninb, R. Wernkeb Abstract Abstract a of Minho, 4800-058 Guimarães, Portugal Industry 4.0 is based on a set of concepts, University technologies and organizational processes affects various areas in engineering education b Unochapecó, 89809-000 Chapecó, SC, Brazil Industry 4.0 is based on a set of concepts, technologies and organizational processes affects various engineering education and beyond. It includes internet-based networking of digitalized mechatronics components on theareas shopinfloor with management and beyond. It includesby internet-based networking of digitalized mechatronics the shop floor with management and business platforms applying technologies from the IT sector. Even socialcomponents aspects are on targeted, as the human being is also and businesstoplatforms fromSystem the IT sector. aspects targeted, institutions as the human also considered be a partby of applying Industrialtechnologies Cyber-Physical (ICPS).Even The social challenge for are educational is being to dealis with considered to be a part of Industrial The challenge for educational institutions is toeach deal other with this broad spectrum. Departments andCyber-Physical institution withSystem different(ICPS). specialization are required to work more closely with Abstract this Departments and institution different specialization required of to the work more closely with each other to bebroad able spectrum. to teach the topic of Industry 4.0 in allwith its dimensions. One of the are approaches University of Applied Sciences to be able to isteach the topic of Industry in all departments its dimensions. thecollaborate approachesand of use the itUniversity of various Appliedaspects Sciences Emden/Leer to build a platform, where 4.0 different canOne workofon, to teach the of Under concept of "Industry production processes be pushed to use be which interconnected, Emden/Leer to build a platform, different departments can work collaborate and itincreasingly to teach the various of Industrythe 4.0. is This platform is calledwhere the4.0", “Automated Class Room” and iswill a on, physical demonstrator, consists of manyaspects different Industry 4.0. This platform is called the “Automated Class Room” and is a physical demonstrator, which consists of many different information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization modules from different departments, such as mechatronic machines, simulation tools, management tools, logistics systems which modules from into different departments, as mechatronic machines, simulationalso tools, tools,profitability logistics systems which goes beyond the traditional aim ofsuch capacity contributing formanagement organization’s and value. are integrated an Industry 4.0 compliant ICTmaximization, (information-communication technologies) architecture. This paper provides an are integrated an Industry compliant ICT (information-communication technologies) architecture. Thistarget paperaudiences. provides an overview aboutinto the platform and4.0 discusses in depth how it is currently used for teaching Industry 4.0 to different It Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of overview the platform and discusses in depth how is currently used teaching Industry tocan different target audiences. It describes about in which parts the individual departments and itspecific courses setfor their and how 4.0 they demonstrate thedeserves benefits maximization. The study of capacity optimization and costing models isfocus an important research topic that describes in 4.0 which parts the individual departments and specific courses set their focus and how they can demonstrate the benefits of Industry for students but also for visitors of the university and enterprises. Furthermore, the “Automated Class Room” is contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical of Industry 4.0 for test students but also for visitors different of the university and can enterprises. Furthermore, the “Automated Class is used as for a practical bed, where students departments learn together how to implement Industry 4.0Room” concepts model capacity based from on different costing models (ABC and TDABC). A generic model has been used as a practical testmanagement bed, where students from different can learn together how in to the implement and technologies. The paper also gives an overview about departments how the platform is going to evolve future. Industry 4.0 concepts developed and it The waspaper used also to analyze capacity and to design strategies towards theinmaximization of organization’s and technologies. gives anidle overview about how the platform is going to evolve the future. value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity c 2019 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. © optimization might operational inefficiency. c 2019 The under Authors. Published by Elsevier B.V. committee of the 9th Conference on Learning Factories. Peer review thehide responsibility of the scientific Peer review under thePublished responsibility of the scientific committee of the 9th Conference on Learning Factories. © 2017 The under Authors. by Elsevier B.V. committee Peer review the responsibility of the scientific of the 9th Conference on Learning Factories. Keywords: Industry 4.0; Learning Platform; Industrialcommittee Cyber-Physical Systems Peer-review under responsibility of the scientific of the Manufacturing Engineering Society International Conference Keywords: Industry 4.0; Learning Platform; Industrial Cyber-Physical Systems 2017. Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency
1. Introduction 1.1.Introduction Introduction The effective information-driven interaction among ICPS on the shop floor and enterprise information systems, effective information-driven interaction amonglife ICPS on the shop and enterprise information systems, The cost capacity is a fundamental forcycles, companies andfloor their management extreme and importance extending toofallidle business processes along theinformation different is viewed as vital to modernofindustries constiextending to all business processes along the life cycles, is viewed as vital to modern constiin modern production systems. In general, it is different defined as unused capacity or production potentialindustries and can beand measured in several ways: tons of production, available hours of manufacturing, etc. The management of the idle capacity Corresponding author. Tel.: +49(0)4921/807-1948. *∗ Paulo Afonso. Tel.: +351 253 510 761; fax: +351 253 604 741 ∗ Corresponding author. Tel.: +49(0)4921/807-1948. [email protected] E-mail address: [email protected] E-mail address: [email protected] c 2017 2351-9789 © 2019 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. 2351-9789 c 2019the 2351-9789 The Authors. Published by Elsevier B.V. of the 9th Conference on Learning Factories. Peer review responsibility of the scientific committee Peer-review under under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017. Peer review under the responsibility of the scientific committee of the 9th Conference on Learning Factories. 2351-9789 © 2019 The Authors. Published by Elsevier B.V. Peer review under the responsibility of the scientific committee of the 9th Conference on Learning Factories. 10.1016/j.promfg.2019.03.048
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tutes the core of the 4th Industrial Revolution [3]. Specifically in Germany, this industrial revolution has a concrete scientific, technical and particular industrial background founded on the fussion of industrial norms and standards, and formally grounded on a new DIN (Deutsche Industrie Norm) specification: the Reference Architecture Model for Industrie 4.0 (RAMI4.0) [6]. Note: The amalgamation of concepts, technologies, engineering methodologies behind Industrie 4.0 is recognized world-wide under the English denomination ”Industry 4.0”. Though the concepts behind, the engineering methods and tools and technologies for Industry 4.0 and ICPS get more defined, elaborated and mature, the challenges for learning, applying and working with them, i.e. living in an Industry 4.0 environment, are hard to grasp, for experts, industrialist and practitioners, but even more for students [4]. Teaching concepts and methods to prepare students for learning Industry 4.0, i.e. about digitalized and virtualized industrial building blocks, things (Industrial Internet of Things - IIoT), assets (RAMI4.0 [6]), which work interconnected through several communication and information networks including the Internet, collaborating and providing citizens and businesses with a wide range of innovative applications along the product and production process life-cycle, based on digitalized data, information and services (e.g. computing, simulating, analyzing, making decisions, communicating, etc.) [3], have successfully been applied at the University of Applied Sciences Emden/Leer, Germany since 2010 [8]. These methods are basically based on experiences and a set of considerable lessons learned by teaching “digitalization of industrial production systems applying the service-oriented architecture (SoA) paradigm” [2]. Basically, a combination of different Teaching/Learning methods have been developed further and applied [1]. This includes the creation of a new international Master Engineering Degree program on Industrial Informatics with specialization on Industrial Cyber-Physical Systems. The learning methods are focusing particularly on 4 major steps: (i) linking theory related to the Industry 4.0 paradigm learned in the classroom with the analysis of published research results, the screening of industrial patent applications complemented with acquisition and analysis of requirements of the industry, done by the students, (ii) transferring this acquired knowledge to prototype innovations and implementations in a digital factory model of the university performed by teams of 2-3 students each, (iii) transferring some of those prototype and the acquired foreground know-how to the industry, and (iv) disseminating the research and innovation results performed by those students of the Master Industrial Informatics, in an international context (see e.g. [13], [9], [11], [12]). With the aim of extending and improving the results of the experiences addressed above, in this paper and following this introduction section, major challenges for teaching concepts and methods to prepare students for learning Industry 4.0 in a multidisciplinary context are introduced in section 2. In section 3 follows the description of the major specifications of a multidisciplinary demonstration platform called ”Automated Class Room” that is being developed and implemented at the University of Applied Sciences Emden/Leer, Germany. Section 4 describes different applications of that platform followed by a summary of current state of those applications and of first achieved results in section 5. Finally, section 6 rounds up the paper with the conclusion and outlook.
2. Challenges for learning to work with Industry 4.0 2.1. Summary of main challenging features of Industry 4.0-compliant solutions Industry 4.0 and Industrial Cyber-Physical Systems (ICPS) forge the core of real-world networked industrial infrastructures having a cyber representation through the digitalization of data and information and the exposition and/or consume of services horizontally and vertically across the enterprise, along the product, production order and process engineering life cycles, and from supplier to customers along the collaborative supply chain network. As such, the quality and the competitive performance of an Industry 4.0-compliant solution depends, among others, on the ability: i. to effectively generate digitalized data and information, in real-time, from different and often heterogeneous networked physical and cyber sources, having in mind that those physical systems are mainly mechanical, hydraulic, pneumatic, electrical, but also documentation, technical design draws, production and maintenance orders, etc. ii. to collect, analyze and use large-scale digitalized data and information for supporting functionalities in the different phases of the named life cycles and within the enterprise ICT architecture
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iii. to sustainably and efficiently manage, supervise and operate the cyber and the physical components and systems in the industrial environment, having in mind that those systems are mainly geographically distributed, are structurally evolvable and present emergent behaviors from functional point of view (i.e. application of the CyberPhysical-Systems-of-Systems paradigm [5]) iv. to facilitate the vertical OT/IT (Operational Technology/Information Technology) as well as horizontal OT/OT and IT/IT connectivity among components and systems v. to guarantee the interoperability of components and systems by using a consistent data model and data transport technology along the life cycles vi. to combine the application of sometimes disjoints industry norms and standards in order to make the solution. vii. to effectively integrate the human actors along the value chain, so that they are able to interact and possibly collaborate with the rest of the networked Industrial Cyber-Physical Systems. 2.2. Major requirements for teaching Industry 4.0 to students As explained before, Industry 4.0 means mainly the confluence of mechatronics, information, communication, computer networks and data and information processing and the penetration and co-existence of all these hardware and software technologies into the industrial environment. Looking to this multi-disciplinary domain and taking into account the traditional engineering study programs, on the one side, the main challenges for a mechanical engineering or industrial engineering student is to cover its non-familiarity of the concrete background about ICT infrastructures, i.e., enterprise control and management architectures, communication and information technologies, computer networks, digitalization and modelling of data and information, specifying and implementing cyber aspects of a production system, etc. Concretely, learning and understanding the informatization, digitalization and networking of the industrial ecosystem. The main challenge for a lecturer/professor is teaching mechanical and industrial engineering graduates for working with the cyber-part, mainly software, information and communication within an Industry 4.0 environment. On the other side, students of the informatics and in general computer sciences and sometimes also of the electronics and electrotechnic need to be instructed how to deal in respect to the physical aspects of Industrial Cyber-Physical Systems behind Industry 4.0. How far are they familiar with the value creation processes in the production systems and collaborative networks? Are they familiar with productivity measures, maintenance aspects and yield aspects? How does the used terminology differ? How do the standards of report writing differ? It is very difficult if not impossible to digitalize and informatize a production system for migrating it into an Industry 4.0-compliant solution if the basic structural and functional specifications of the physical components, mainly hardware and their life cycle specifications, are not well understood. It is very difficult if not impossible to digitalize and to informatize a production system for migrating it into an Industry 4.0-compliant solution if the basic structural and functional specifications of the physical components, mainly HW and their life cycle specifications, i.e., at least the product and factory life cycle as a framework for learning factories [1], are not well understood. At this point the necessity to have a ”Demonstration Platform” where many if not all those specifications of Industry 4.0-compliant solutions can be designed, implemented, tested, optimized, etc, in a multi-disciplinary fashion is clear. Despite of the necessary initial investments in acquiring and installing industrial SW/HW components and systems at the university site [4] [13], at this point is clear that it is unavoidable to have a “Demonstration Platform” for implementing the approach described in this paper. The major advantage, a concrete ROI, is to count on an industrially relevant environment where many if not all the specifications of Industry 4.0-compliant solutions can be designed, implemented, tested, optimized, etc. by all involved actors (teachers, students, etc.) in a multidisciplinary fashion. 3. Demonstration Platform ”Automated Class Room” For several years working on individual aspects of Industry 4.0 have already been covered in laboratories and specific learning platforms within the University of Applied Sciences in Emden. For example, the Institute I2 AR
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has built a fully automated production system, which allowed the collaboration of different industrial automation devices (e.g. robots, conveyor belt systems, storage systems) to produce individualized products based on the concept of Service-oriented Architecture [13]. The focus of this platform lies on important aspects such as digitalization of automation systems, communication and integration technologies for vertical and horizontal integration and migration approaches [12] [15] [7]. Other aspects like applying the digitalization benefits in production and logistics are more strongly focused in the laboratory of production planning (PPS-Lab). The PPS-Lab has strong history in using Enterprise Resource Planning (ERP) systems and serious games to teach interdisciplinary challenges in production systems [14]. Based on the existing expertise, the Institute I2Ar and the PPS-Lab initiated building an additional platform, which combines the different lessons learned in the Industry 4.0-related fields of knowledge in one system. This system will then act as a common platform for all involved stakeholders to teach, practice and demonstrate the specific aspects of Industry 4.0 which they are covering. 3.1. General Idea The first step to build this platform was to identify the collaborators within the university, which are related to the topic of production systems and which cover specific aspects of an Industry 4.0 system. Based on the knowledge and experience of these collaborators (see [10]), necessary modules were identified, (i) necessary aspects which have to be covered by the platform as well as the concepts for the implementation of the installation were defined and (ii) the integration of already existing modules with new hardware/software and technologies were considered. The underlying Industry 4.0-related concept for this platform is the modularity. Each functional module can be used to focus on specific aspects and can be operated independently from the rest of the system, if necessary. In addition, also the combined operation of all modules is required. This approach should both work in a decentralized way, where the individual systems are located in their respective laboratories, but also in a centralized setup, where all modules are placed together. This allows the use of the system as a demonstration platform for exhibitions and other events. The system is also required to be open for future changes and addition of new components. The selected name for the platform is the ”Automated Class Room” to show the target of being applied as a learning platform, but also showing the relation to automation and digitalization. To build a basic setup for the ”Automated Class Room”, oriented to learn and work in an Industry 4.0-compliant environment, a first set of collaborators from the following areas and departments has been selected: (i) Industrial Informatics, (ii) Industrial Automation, (iii) Industrial Communication Technologies, (iv) Production Management and Control, (v) Supply Chain and Logistics, (vi) Laser Technology, (vii) Material Sciences and Mechanical Design, etc. The inclusion of the areas of Material Science and Mechanical Design covers all aspects related to the products which are being handled through the platform, as well as the necessary machinery to produce these products. Specifically, the requirement was to include laser engraving and 3D printing processes, since they allow an easy application of customer-specific individualization of the product. Stakeholders from the fields of Industrial Automation, Industrial Informatics and Industrial Communication Technologies are involved to digitalize these machines and the products. This includes applying concepts to integrate hardware and software systems, which are not already Industry 4.0 compliant, as well as defining an information and communication architecture. The information generated by the digitalized machinery and products can then be used by additional production management and control systems, such as Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES) to handle customized orders and controlling the production process. Additionally, virtualized and simulated representations of the platform are using the information to calculate valuable key performance indicators. The whole setup is then also considered from a supply chain management and logistics perspective. 3.2. Hardware Setup and Digitalization Approach Within the first setup, the aforementioned domains have been considered to build a system consisting of the modules illustrated in Figure 1(a). The setup consists of two machines, a laser engraving machine and a 3D printer,
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Fig. 1. (a) Overview of Hardware setup of the Automated Class Room; (b) Adapters for REST implementation.
but is supposed to be extended with additional equipment over time (e.g. storage and packaging stations, additional processing machines, etc.). Each machine builds its own module to be integrated and digitalized for the platform. If put together, a collaborative robot (cobot) is used to handle the products and transfer them between the different modules. The whole system is connected to an ERP/MES server, which handles the production planning and execution of the production. A Web Shop is acting as the interface to the customer. Since the goal for the platform is to integrate all modules of the system into an Industry 4.0 environment, each of the modules – which themselves (many of them) are not typically ready for Industry 4.0 by default – needs to be digitalized. The strategy for digitalizing each module is based on applying the Service-oriented Architecture (SoA) concept [2] [13]. The application of the SoA approach allows that each module gets networked through the internet, being able (1) to offer its functionalities and/or (2) consume functions from other modules of the networks as “services” (i.e. applying Internet-of-Services (IoS) technologies). Related to the application of the SoA approach, many established ICT exist, such as SOAP, REST or the Industry 4.0 related OPC-UA [9]. The technology of choice for the first implementation is REST, since it is easy to develop while still providing the necessary behaviour. To allow the individual modules to be SoA-based networked using REST technology, additional adapter solutions need to be developed. These adapters will take the machine or software specific interfaces and set up a REST interface on top of them. For example, the ERP/MES system used within the platform doesn’t provide a REST interface on its own and just stores its data inside a database. This data is picked up by an adapter using SQL queries and translated in corresponding REST resources. In another example, the 3D printing machine also needs to be attached with a REST adapter, which, among other functions, allows the 3D printer to pull production orders from the ERP and executes these orders on the 3D printer. Figure 1(b) provides an overview about the adapters. 3.3. Envisioned processes There are currently two processes envisioned to be covered by the platform. In both cases, a user is able to enter individualized orders for a product into a Web Shop, which is connected to the ERP/MES and is able to trigger the creation of a new order within the system. The first product a pen, which is processed by the laser engraving machine and which allows the customer to engrave a text of his choice on the pen. The second product is a 3D printed business card, where the customer can select a logo to be printed and the contact details which the business card should have. 4. Using the ”Automated Class Room”. Exemplary Use Cases The main application for the Automated Class Room platform are teaching purposes within the university. Teaching Platform for individual aspects: The individual modules of the system can be used on their own without the interaction with other systems. This way, parts of the system can be used to target specialized aspects
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of the system. For this use, the platform does not need to be assembled in one spot as a whole. For example, the ERP/MES module is used within courses related to production planning and industrial engineering students in practical exercises or projects can specifically focus on the ERP/MES system itself, while still having a clearly defined implementation goals (e.g. configuring the system to allow the order of business cards and pens). Another example is the digitalization part, where students from the Master on Industrial Informatics need to investigate information/communication technologies as well as to develop solutions to migrate specific modules, digitalizing them for working in a SoA-based manner. Teaching Platform to integrate the whole system: The requirement for this use case is that basic functionality within the modules is already setup. If this is done, the platform can be used as a learning platform for bringing interdisciplinary groups together to solve a problem. To get to whole system running, students from various backgrounds need to collaborate. This kind of integration work needs a high amount of communication and specification to be able to link up the individual parts. The data and the SoA-based interfaces to transport the data need to be aligned as well as the service-oriented functionality developed within each module. Exemplary demonstration platform: With all modules implemented and working together, the whole platform during its operational state can also be used as a full running example for students to see a system designed with Industry 4.0 characteristics running. This way, the students but also teachers and other actors as e.g. participants of exhibitions both in class as well as fairs, can see in a live demonstration, where the benefits for Industry 4.0 are (e.g., vertical and horizontal SoA-based connectivity, structural and functional reconfigurability, virtualization of modules/simulation-in-the-control and –management-loops, etc.) and how such a system can look like.
5. Current State and first results The aforementioned results have started to being implemented and are used in practice. Since the whole idea consists of multiple modules and is open to changes and additions, the platform is not finished yet. In fact, the goal is to continuously improve and enhance the system, which implies that there is no clearly defined ”final” state. The first activities were focusing on implementing a basic setup including the laser engraving machine, the 3D printer and the ERP/MES system. This way, both horizontal (machine to machine) and vertical (machine to MES/ERP) connectivity can be demonstrated and a whole production process can be demonstrated. The process includes the generation of a production order within the ERP. This order includes customized information regarding the desired product. Depending on the selected product (either a business card or a pen), the related machine is capable to fetch the new order via ”services” from the ERP/MES and adapt its program to the selected custom parameters. The communication is done using a REST-based communication architecture, where the ERP/MES provides order-specific information as REST resource. This setup has been successfully implemented through various student projects. So far, students from the fields of Computer Science (Bachelor), Mechanical Engineering (Bachelor and Master) and Industrial Informatics (Master) have been active in the development. The result is a first demonstration setup, which is used for showcasing the platform internally as well as externally, based on the use cases described in Chapters 4 to 4.
6. Conclusion This paper has described an interdisciplinary approach and the development of a first setup of an Industrial CyberPhysical Systems Platform, called “Automated Class Room”. After describing the current use of the platform for learning Industry 4.0-related concepts at the University of Applied Sciences Emden/Leer, Germany, the manuscript highlights the impact of such a learning platform for use case demonstrations as well as for the realization of student projects. Future works will include not only the realization of new student projects to continue developing the work on the platform, but also the use of the learning approach and platform in different bachelor- and master-engineering curricula within the university.
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References [1] Abele, E., Chryssolouris, G., Sihn, W., Metternich, J., ElMaraghy, H., Seliger, G., Sivard, G., ElMaraghy, W., Hummel, V., Tisch, M., Seifermann, S., 2017. Learning factories for future oriented research and education in manufacturing. CIRP Annals 66, 803 – 826. URL: http:// www.sciencedirect.com/science/article/pii/S0007850617301440, doi:https://doi.org/10.1016/j.cirp.2017.05.005. [2] Colombo, A., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., Harrison, R., Jammes, F., Lastra, J.L., 2014. Industrial Cloud-Based Cyber-Physical Systems: The IMC-AESOP Approach. Springer Publishing Company, Incorporated. [3] Colombo, A.W., Karnouskos, S., Kaynak, O., Shi, Y., Yin, S., 2017. Industrial cyberphysical systems: A backbone of the fourth industrial revolution. IEEE Industrial Electronics Magazine 11, 6–16. doi:10.1109/MIE.2017.2648857. [4] Colombo, A.W., Schleuter, D., Kircher, M., 2015. An approach to qualify human resources supporting the migration of smes into an industrie4.0-compliant company infrastructure, pp. 003761–003766. doi:10.1109/IECON.2015.7392687. [5] CPSoS, . Cpsos - definitions used throughout the project. URL: http://www.cpsos.eu/project/ what-are-cyber-physical-systems-of-systems/. [6] DIN Deutsches Institut f¨ur Normung e.V., 2016. DIN SPEC 91345:2016-04: Referenzarchitekturmodell Industrie 4.0 (RAMI4.0). [7] Gosewehr, F., Wermann, J., Colombo, A.W., 2016. Assessment of industrial middleware technologies for the perform project , 5699– 5704doi:10.1109/IECON.2016.7793611. [8] G¨otting, M., Gosewehr, F., M¨uller, M., Wermann, J., Zarte, M., Colombo, A.W., Pechmann, A., Wings, E., 2017. Methodology and case study for investigating curricula of study programs in regard to teaching industry 4.0, pp. 533–538. doi:10.1109/INDIN.2017.8104828. [9] Haskamp, H., Meyer, M., Mollmann, R., Orth, F., Colombo, A.W., 2017. Benchmarking of existing opc ua implementations for industrie 4.0-compliant digitalization solutions , 589–594doi:10.1109/INDIN.2017.8104838. [10] N.N., . AKZ project page. University of Applied Sciences Emden/Leer. URL: https://www.hs-emden-leer.de/fachbereiche/ technik/labore/produktionsplanung/akz/. [11] Schulte, D., Colombo, A.W., 2017. Rami 4.0 based digitalization of an industrial plate extruder system: Technical and infrastructural challenges, pp. 3506–3511. doi:10.1109/IECON.2017.8216593. [12] Wermann, J., Kliesing, N., Colombo, A.W., Moraes, E.C., 2015a. Impact of new ict trends for the educational curriculum in the area of industrial automation and engineering. doi:10.1109/IECON.2015.7392667. [13] Wermann, J., Moraes, E.C., Colombo, A.W., 2015b. A service-oriented architecture implementation in the digital factory of the university, Springer International Publishing, Cham. doi:10.1007/978-3-319-22867-9_7. [14] Zarte, M., Pechmann, A., 2017. Concept for introducing the vision of industry 4.0 in a simulation game for non-it students, pp. 512–517. doi:10.1109/INDIN.2017.8104825. [15] Zarte, M., Pechmann, A., Wermann, J., Gosewehr, F., Colombo, A.W., 2016. Building an industry 4.0-compliant lab environment to demonstrate connectivity between shop floor and it levels of an enterprise , 6590–6595doi:10.1109/IECON.2016.7792956.