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

138 IT and Automotive Self-organisation as a control principle in modular automotive production By Dr.-Ing. Olaf Sauer, Automation business unit/Deputy Institute Director Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe One application of Industry 4.0 is “self-organising production”. Even the first documents relating to Industry 4.0 contain the vision that “by their ad-hoc networking capability as well as the inclusion of a digital product description, intelligent products are able to autonomously control their paths through the production process” [1] . Initial appli- cations can already be seen in several factories, for example where automated guided vehicles (AGVs) transport workpieces to the next free assembly station. This idea of self-controlled production was already pertinent by the turn of the millen- nium, triggered by the then software agent technology [2,3] . However, this production con- trol technology has not become established for various reasons. Computer performance has been insufficient and there has been too little confidence in self-organising units in factories. In body production, painting and final assem- bly, the automotive industry has long utilised the pearl chain control principle [4] , right up to the so-called just-in-sequence (JIS) delivery of components, which are assigned to a par- ticular “pearl”, i.e. a specific vehicle. However, this principle is reaching its limits due to the increasing variety of vehicle types, versions and derivatives. The space available for the provision of components on the assembly line, synchronisation of average cycle times, the fluctuating work content of specific cycles and the need for a high level of adaptability demand new control principles. In any case, the linear path and strict adherence to the pearl chain between body shell production and assembly is usually interrupted in the paint shop, where color groups are formed. The sequence must then be restored in a body storage that allows selectable access after painting. The 2008/09 financial crisis in particular made it clear that the production technol- ogy installed and control principles used by automakers can result in problems in cover- ing fixed costs when sales fluctuate. This is primarily due to the legacy equipment cur- rently in use, which is designed for specific production series, engine versions or as- semblies and is too inflexible to be used for other purposes in extreme cases, i.e. when capacity is underutilised. Automotive pro- duction will have to meet this challenge in the coming years. For future automotive production, automated systems will therefore have to become more flexible, e.g. through equipment which can be used more universally and/or modular produc- tion lines that allow scalable, universal equip- ment to be quickly assembled and configured for new production and assembly tasks with- out great engineering effort. • Quality, e.g. ppm requirements • Delivery time, throughput time • Manufacturing cost, TCO for shipped vehicle • Other KPIs, such as OEE, OPEX, CAPEX, etc. • Optimization in terms of searching for a global optimum • Competitiveness based on manufacturing excellence and data based services; ‘the winner takes it all’-paradigm • Customer orientation • Sustainability • Resilience and agility • Uncertainty and reactiveness • Network, coopetion • Economies of scale • Good static ‘white box’ models for entire vehicle manufacturing down to single processes • Automation technology • Skilled workforce, their experience, knowledge about causalities • Clear manufacturing strategy • Computing power: Cyber Physical Systems, Edge, Cloud, Quantum computing, real-time communication and machine learning • Augmented people and assisting systems • Partners, market places, e.g. for technology data or capacities Drivers of the past Future drivers Enablers of the past Future enablers Fig. 1: Digitalisation of value creation: drivers and enabling technologies for future automotive manufacturing Dr. Olaf Sauer Bilder/Grafiken: © IOSB Fig. 2: Possible business models for future automotive man- ufacturing (perspective for 2030) [6] low Individualization high low value creation high „Integration- champion“ „Flex Champion“ „Plug & play- champion“ „Efficiency- champion“