http://www.diva-portal.org Preprint This is the submitted version of a paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11 13, 2018, University of Skövde, Sweden. Citation for the original published paper: Syberfeldt, A., Ayani, M., Holm, M. (2018) A holistic solution for integrating a simulated twin of an automation system during the system s entire life-cycle In: Peter Thorvald, Keith Case (ed.), Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11 13, 2018, University of Skövde, Sweden (pp. 405-410). Amsterdam: IOS Press Advances in Transdisciplinary Engineering https://doi.org/10.3233/978-1-61499-902-7-405 N.B. When citing this work, cite the original published paper. The final publication is available at IOS Press through http:// dx.doi.org/10.3233/978-1-61499-902-7-405 Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16374
A holistic solution for integrating a simulated twin of an automation system during the system s entire life-cycle Anna SYBERFELDT a,1, Mikel AYANI a and Magnus HOLM a a University of Skövde, Department of Engineering Science, Högskolevägen, Skövde 541 28, Sweden. Abstract. This paper describes a project that attempts to develop a holistic solution for integrating a simulated twin of an automation system during the system s entire life-cycle. With such holistic solution, virtual commission could be undertaken in all steps of the life-cycle which facilitates companies in realizing flexible and intelligent automation systems. Based on the simulated twin, the companies could easily and cost-efficiently evaluate modifications, make improvements, and train operators when changes in the production setup occurs due mass-customization or new products being introduced. This aids the companies in staying competitive on a global and rapidly changing market and meet the challenges coming with the forth industrial revolution, such as masscustomization and short product life-cycles. Keywords. Simulated twin, Virtual commissioning, Automation system. 1. Introduction With Industry 4.0 comes a ground-breaking technological evolution towards cyberphysical systems and a paradigm shift from centralized to decentralized production enabled through the concept of the Internet-of-Things [1]. This paradigm shift will significantly change the way production is undertaken [2]. Short product life-cycles and extreme customization will require companies to be equipped with efficient automation systems (including robots, machines, AGV:s etc.) that can easily and dynamically be adjusted to changing circumstances [3]. Realizing such systems is, however, non-trivial and is raised by the partner companies involved in the project (as well as other industrial partners to the university) as a problem of uttermost importance to tackle. The problem also involves multidimensional scientific challenges which makes it highly interesting also from an academic perspective. The aim of this project is to approach the problem by using virtual simulation and based on this technique develop solutions that facilitate the design, implementation and operation of flexible and intelligent automation systems. The idea is to create a virtual copy of the automation system that acts a digital twin to the real system. Simulation is a powerful technique for minimizing development, test and validation time and cost when developing new automated system projects. It also provides a 1 Corresponding Author. anna.syberfeldt@his.se
perfect platform to develop new products and algorithms reducing prototype fabrication costs and development time. Besides that, once a simulation model is created and used in the development and validation steps of a project, other potential uses emerge. Integrating the simulation model with the entire life cycle of an automated system (Figure 1) could improve the quality and reduce costs in many different ways. Simulation can be used to make improvements in a working system, test modifications, debug system failures, train maintenance staff and educate operators. This can be done without disturbing the production system. In addition, simulation could help, for example, to reduce production stop times, reduce failing risk when implementing system modifications or increase staff knowledge and their confidence. Figure 1: The life-cycle of an automated system. The project described in this paper aims to develop a holistic solution for integrating a simulated twin of an automation system during the system s entire lifecycle. With such holistic solution, virtual commission could be undertaken in all steps of the life-cycle which facilitates companies in realizing flexible and intelligent automation systems. Amongst others, the following benefits are expected from the solution developed: Increased productivity and quality of automation solutions throughout the entire life cycle (for example by reduce production stop times, reduce failing risk when implementing system modifications and by increasing staff knowledge). Minimal costs and lead times in conceptual and development phases. Enabling the concept of "batch size one" (mass customization/high product mix) in practice through supporting minimal costs and minimal lead times when changing the production set-up. Easy to make improvements in a working system, test modifications, debug system failures etc. without disturbing the production system. Efficient training of maintenance staff and operators.
In the research community, previous efforts have been made to develop solutions for the simulation of automation systems (examples include [4-6]). The ideas and findings presented in these studies are both relevant and valuable, but the proposed solutions consider only one specific type of equipment (for example robots) and/or only one or few step(s) in the life-cycle. A careful literature review reveals no generic solutions that consider different kinds of automation equipment and implement a simulated twin throughout the entire life-cycle. Furthermore, the literature review also reveals a gap with respect to supporting PLC emulation (that is, creating a digital twin of the units that are used to control the automation equipment) throughout the life-cycle. These finding have motived this project from a scientific perspective and we believe that the development of a new holistic solution that includes PLC emulation have a great potential not only to advance the research front but even to revolutionize the manufacturing industry. 2. Conceptual design of the holistic solution The conceptual design of the holistic solution intended to be developed in the project is provided in Figure 2 below. Figure 2: Conceptual design of the holistic solution intended to be developed in the project. Basically, the solution consists of four parts: ❶ a simulated automation twin of the physical automation environment, ❷ an IT platform for automated data acquisition,
❸ a simulation-based optimization based on the digital twin, ❹ tools for train the employees and making informed decisions based on the simulations. The process of realizing the solution is divided into five different steps, as described below: Step 1: Design a holistic framework for realizing the simulated automation twin ( a virtual original ) that enable carrying out all steps in an automation system s life-cycle entirely virtually. The framework should describe all parts of a holistic solution in detail, including both conceptual and technical details. Step 2: Design and implement a PLC emulation software that supports all steps in the life-cycle. The software should be easy to couple to other automation simulation software, such as robot simulations and production system s simulations. Step 3: Design and implement tailor-made optimization techniques for automatic multi-criteria optimization based on the simulated automation twin (simulation-based optimization). The optimization techniques should be able to provide solutions both for conceptual systems and for systems being in operation (for the latter, solutions should be provided in real-time). The results of the optimizations should be visualized in a way that efficiently aid decision makers in making informed decisions. Step 4: Design a conceptual design for an IT platform for automated data acquisition in real time that enables the simulated twin and the physical equipment to be maintained identical over time. This ensures that the virtual copy is constantly up-to-date, which enables the real-time study of the physical equipment through its simulated twin and to perform experiments on the physical equipment in a virtual environment. Step 5: Design and implement a training tool for operators and maintenance personnel based on the simulated twin. The training tool should provide an easy and effective training of the operator and preferably be based on state-of-the art technology from the gaming industry such as virtual reality. 3. Industrial gains From the industrial perspective, the main value of the solution is that realizing it will help in maintaining the companies competitiveness and survival in the global market. Industrial companies have a great interest in the development of new solutions that can optimize their automation systems and enhance adaptability and flexibility, which is the very aim of the solution. Amongst others, the industry will gain the following benefits from the solution: Increased productivity and quality of their automation solutions throughout the entire life cycle. This is achieved by, for example, reduced stops in the production, reduced risks of failing when doing modifications of the systems and by increased skills of the operators. Minimal costs and lead times in conceptual and development phases by using simulation instead of physical prototypes.
Possibility to frequently change the production set-up and implement the concept of "batch size one" with minimal costs and minimal lead times. Possibility to make improvements of a system in operation, test modifications, debug system failures etc. without disturbing the production system. Efficient training of maintenance staff and operators. Increased knowledge about simulation and virtual commissioning and how these techniques can be used to realize a flexible and efficient automation system. 4. Operator support system As previously described, one part of the solution is tailor-made optimization techniques for automatic multi-criteria optimization based on the simulated automation twin. These optimization techniques are intended to provide solutions in real-time for the systems being in operation (the physical twin). In order to realize these optimized set-ups in practice, decision-support systems for the shop-floor operators are needed. The operators commonly face complex tasks related how to handle occurring problems and best operating the equipment. The complexity, in combination with the pressure of completing the task within a minimum time frame and without error, makes it hard for the operators to act optimally. To aid the operators and support them to carry out the tasks in the most efficient way, enhanced visual guidance through smart glasses using augmented reality will be developed as part of the project. With augmented reality, it is possible to give operators access to information that their ordinary senses could not have gathered from reality, and to give this information in the context of where it is needed [7]. The basic concept behind augmented reality is to overlay digital information about the environment and its objects on the real world, and thereby enhance the perception of reality [8], see Figure 2. Figure 2. Augmented reality in smart glasses. Over the last few years, the technology enabling augmented reality has advanced rapidly and a number of real-world applications of augmented reality can be seen today; mainly within areas such as gaming, sports and tourism. Within the context of industrial applications, augmented reality has been discussed for over 20 years. There
exist plenty of studies on the topic (see for example [9-13]), and also some industrial applications. As far as the authors are aware, there are however currently no industrial applications of augmented reality targeting automation twins. 5. Summary This paper describes a project that attempts to develop a holistic solution for integrating a simulated twin of an automation system during the system s entire lifecycle. With such holistic solution, virtual commission could be undertaken in all steps of the life-cycle which facilitates companies in realizing flexible and intelligent automation systems. Based on the simulated twin, the companies could easily and costefficiently evaluate modifications, make improvements, and train operators when changes in the production setup occurs due mass-customization or new products being introduced. This aids the companies in staying competitive on a global and rapidly changing market and meet the challenges coming with the forth industrial revolution, such as mass-customization and short product life-cycles. References [1] Zuehlke, D. (2010). SmartFactory Towards a factory-of-things. Annual Reviews in Control, 34(1), 129-138. [2] C. Brecher, C. Ecker, W. Herfs, M. Obdenbusch, S. Jeschke, M. Hoffmann and T. Meisen, The Need of Dynamic and Adaptive Data Models for Cyber-Physical Production Systems, in Cyber-Physical Systems: Foundations, Principles and Applications, pp. 321-338, ImpressumWaltham, Elsevier, 2017. ISBN978-0-12-803801-7 [3] Veza, I., Mladineo, M., & Gjeldum, N. (2015). Managing Innovative Production Network of Smart Factories. IFAC-PapersOnLine, 48(3), 555-560. [4] Lee, C.G. and Park, S.C. (2014) Survey on the virtual commissioning of manufacturing systems. Journal of Computational Design and Engineering, 1(3), 213 222. [5] Pehrsson, L., Ng, A. H. C. & Stockton, D. (2013) Industrial cost modelling and multi-objective optimisation for decision support in production systems development. Computers and Industrial Engineering, 66, 1036-1048. [6] Hoffmann, P., Schumann, R., Maksoud, T. M., & Premier, G. C. (2010) Virtual Commissioning Of Manufacturing Systems A Review And New Approaches For Simplification. In ECMS 2010, pp. 175-181. [7] Barfield, W. (2015) Fundamentals of Wearable Computers and Augmented Reality, 2nd ed. Florida: CRC Press. ISBN 9781482243505 [8] Kipper, G. and Rampolla, J. (2013) Augmented Reality: An Emerging Technologies Guide to AR. Boston, MA: Syngress/Elsevier. [9] Zauner, J., Haller, M., Brandl, A. and Hartman, W. (2003) Authoring of a mixed reality assembly instructor for hierarchical structures. 2nd IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2003. Institute of Electrical and Electronics Engineers Inc., 237-246. [10] Nilsson, S. and Johansson, B. (2007) Fun and usable: Augmented Reality instructions in a hospital setting. Australasian Computer-Human Interaction Conference, OZCHI'07, Adelaide, SA. 123-130. [11] Sääski, J., Salonen, T., Hakkarainen, M., Siltanen, S., Woodward, C. and Lempiäinen, J. (2008) Integration of design and assembly using augmented reality. In: RATCHEV, S. (ed.) IFIP International Federation for Information Processing. [12] Henderson, S. and Feiner, S. (2011) Exploring the benefits of augmented reality documentation for maintenance and repair. IEEE Transactions on Visualization and Computer Graphics, 17, 1355-1368. [13] Paelke, V. (2015) Augmented reality in the smart factory: Supporting workers in an industry 4.0 environment, in Proc. of the 2014 IEEE Emerging Technology and Factory Automation, pp. 1-4.