OEM & Lieferant Ausgabe 2/2019 - OEM & Supplier 2/2019 by VEK Publishing

139 The followingmeasures are available for this [5] : ›  Scalable assemblymodules linked by flexible automated guided vehicles (AGVs) and elim- ination of permanently installed conveyor ›   Increased use of universal industrial robots in cooperation with production and assem- bly workers ›  Utilisation of the potential offered by dig- italisation and the increasing performance of information technology for automotive production (see Fig. 1) In various publications [6] , management consul- tancy strategy& has demonstrated methods for automakers; one of these – which we will elaborate on below – is that of Flex Champi- ons (Fig. 2): vehicle production according to this business model pursues the approach of maximum adaptability. Various models, drive variants and derivatives with a large spread of work content can be cost-effectively produced if each body takes its own individual path through the assembly modules, which in turn are supplied on time with components from pre-selected shopping baskets by AGVs. This scenario requires permanent localisa- tion and online tracking of body shells, AGVs for their transport, assembly parts and their means of transport. Conveyor technology across several levels such as in today’s au- tomotive plants is then no longer necessary; even track-bound vehicles will be largely eliminated from the factory. Today’s (mostly outsourced) logistics with external supplier warehouses, supermarkets, milk-run trains to supply the assembly line and Kanban racks at the conveyor belt are changing toward picking sets of components for particular in- stallation volumes. Only C-parts will be pro- vided just-in-time in the modules (managed externally). Simulation and operational control using new methods such as reinforcement learning for all autonomous vehicles (see example in Fig. 4) which transport the workpieces and deliver the components is challenging. It has not yet been proven that such a novel production and control system can be at least as efficient but more adaptable as the sophis- ticated and synchronised assembly line pro- duction which has been tried and tested over many years [8] ; nor has it been proven that such a system can autonomously and robustly re- spond to unexpected events. Self-organisation is taking place not only in the factory but also at the level of global supply chains. Many suppliers find it difficult to hand over planning autonomy and confi- dential information to a central supply chain orchestrator. This results in self-organisa- tion and agent-based decentralised planning tasks. Initial attempts, e.g. production of the e.Go vehicle in Aachen with small numbers for an automotive plant, indicate that there is great potential for self-organisation, even though several outstanding questions remain to be answered. strategy& and Fraunhofer have set themselves the goal of answering these outstanding questions and opening up paths to new production systems for their customers. Sources [1] acatech (Pub.): Umsetzungsempfehlungen für das Zu- kunftsprojekt Industrie 4.0 – (Implementation recom- mendations for the Industry 4.0 future project) Final report of the Industry 4.0 work group, April 2013 [2] Sauer, O.; Sutschet, G.: ProductionMonitoring linked to object identification and tracking – a step towards real time manufacturing in automotive plants. In: Teti, R. (Ed.):Proceedingsofthe5thCIRP InternationalSeminar on Intelligent Computation in Manufacturing Enginee- ring, Ischia (Italy): 2006, pp. 321-326 [3] Bussmann, S.; Schild, K.: Self-Organizing Manufactu- ring Control: An Industrial Application of Agent Tech- nology. In Proc. of the 4th Int. Conf. on Multi-agent Systems (ICMAS’2000), Boston, MA, USA, 2000, pp. 87-94. [4] Weyer, M.; Spath, D.: Das Produktionssteuerungs- konzept “Perlenkette”. Herausforderungen und Hand- lungsempfehlungen der Implementierung. (The “pearl chain” production control concept. Challenges and recommended action for implementation.) ZWF Zeit- schrift für wirtschaftlichen Fabrikbetrieb; 2009, No. 12; pp. 1126-1130. [5] Fraunhofer Allianz Automobilproduktion (Pub.): Mo- bilität der Zukunft muss produziert werden. (Future mobility must be produced.) Position paper, Chemnitz: 2019. [6] Weber, H. et al: Transforming vehicle production by 2030 – how shared mobility and automation will re- volutionize the auto industry. strategy& White Paper, 2018. [7] Fraunhofer IOSB: Künstliche Intelligenz für die Produk- tion von morgen. (Artificial intelligence for tomorrow’s production.) White paper, Karlsruhe: 2019. [8] Monden, Y.: Toyota Production System: an integrated approach to Just-in-time. Engineering Management Press, 1997. Fig. 3: Example of a first application of self-organization in automobile production Fig. 4: Self-organisation using the example of swarming insects [7] Business Unit Automation and Digitalization https://www.iosb.fraunhofer.de/ servlet/is/12579/ Autonomous Systems  https://www.iosb.fraunhofer.de/ servlet/is/99090/ Websites