Permanently updated 3D‑model of actual geometries of research environments

This report describes the approach to create permanently updated 3D models of research aircraft and laboratory facilities. Therefore, optical metrology scans the research environment in its raw or as-delivered condition. The result is a virtual model of the actual geometry and, in comparison to reference data (e.g. CAD-data), the smallest inaccuracies can be identi- fied and analyzed. The exact position of non-rigid components, like riser ducts, electronics or isolation, can be determined in the models. Further changes to the layout of these facilities are permanently digitized and added to the virtual model of the environment. This can be a new recording of the entire facility or of individual areas that are affected by the changes. The individual, newly recorded models are then integrated into the existing model. This creates an always up-to-date 3D model of the research environment, which is added to its digital twin and can be observed there. In combination with CAD data, future conversion and installation measures are planned in advance and analyzed virtually in relation to the up-to-date geometry and installation space data. In addition, the virtual models of the aircraft cabins can be used to support the lengthy approval and certification process at an early stage

Optimized robot usage for minimizing the power utilization in automated cabin assembly process

Commercial aircraft transport is facing turbulence due to corona lockdown and the impact of such lockdowns are short-term felt, could range for next two-three years. On retaining to normality, the aircraft industry would regain its wings to operate, which continues the impact on environment. The effect of climate change is a long-term issue over next 30-40 years. Due to the rapid growth of commercial aviation, consumption of fuel is directly increased. Phenomenal growth of air trafficking by national and international airliners results in progressive depletion of total carbon space along with alarming increase in emissions level. The term Green Transport stresses on building sustainable economic development without sacrificing the local and global environment. With the mission on zero emissions of carbon and other harmful pollutants, DLR is involved in different research areas such as electric flights, alternate fuels etc. In order to achieve the goal of zero emissions and to make aircraft production sustainable, it is necessary to go green in airplane manufacturing. This work is focusing on green assembly, where we focus ourselves on describing an approach that offers adaptable, automated and customizable process flow along with reliable assembling methodology that provides faster cycle time in conjunction with safety to human workers

Aircraft cabin assembly based on decision tree algorithm

Aircraft manufactures offer to their customers a possibility to customize and differentiate their aircraft. Upmost impact to future passengers leaves the painting of the aircraft with company logo, colors, and cabin interior. Worldwide there a lot of airlines with different requirements therefore, there is not a possibility for fixed final assembly line for each aircraft model. Moreover, the specific cabin options are often ordered later than required by the order fulfilment process of the OEM (Original Equipment Manufacturer). Delays in the supply chain disturb are also a serious complication [1]. Therefore, it is of significant importance to digitalize the aircraft cabin production in order to agile and flexible reschedule and simulate the cabin assembly. Even more digitalization minimizes the industrial waste and contributes to more sustainable aircraft production. In this paper is presented a decision tree algorithm for scheduling the assembly of customizable aircraft cabin. This approach contributes to reduce the time and effort for optimal rescheduling such a complex assembly as aircraft cabin

Integration eines Prozessplanungsalgorithmus in die Modellbasierte Produktionsarchitektur am Beispiel der Crown-Modul Vormontage

Die Konfiguration und die Ausstattung einer Flugzeugkabine hat einen erheblichen Einfluss auf das Flugerlebnis der Passagiere. Um den Bedürfnissen der Passagiere gerecht zu werden und insbesondere das Flugerlebnis bei der eigenen Airline zu verbessern, fordern Fluggesellschaften immer wieder individuelle Anpassungen an das Kabinendesign. Die Umsetzung dieser Änderungen erfordert eine hohe Flexibilität in der Produktion und kann zu Schwierigkeiten bei der Einrichtung einer festen Endmontagelinie führen. Zudem erfordern unvorhergesehene Ereignisse und Änderungen in der Lieferkette der OEMs eine schnelle Reaktion in der Flugzeugproduktion, um termingerecht liefern zu können. Die Digitalisierung und Automatisierung in der Produktionsplanung ermöglicht es, diese Herausforderungen zu bewältigen und leistet einen wichtigen Beitrag zur Flexibilität, Zeit- und Kosteneffizienz. In dieser Arbeit wird ein digitaler Ansatz zur Modellierung und flexiblen Planung von Produktionsprozessen vorgestellt. Dazu werden Flugzeugentwurfsdaten automatisch mit den Produktionsmodellen verknüpft, um schnell auf Designänderungen im Montageprozess zu reagieren. Ein Planungsalgorithmus nutzt daraufhin die Produktionsarchitekturparameter, um die Montageprozesse, z.B. zeitlich, zu optimieren. Demonstriert wird der vorgestellte Ansatz am Beispiel der Umplanung der Vormontageprozesse des "Crown-Moduls". Letzteres beinhaltet alle strukturellen und funktionalen Komponenten oberhalb der Fensterpanele, wie Gepäckablagen, Elektrik und Belüftung. Der in dieser Arbeit vorgestellte agile Ansatz ermöglicht zudem die Simulation von innovativen Änderungen im Flugzeug- und Kabinenentwurf oder in der Produktionsanlage und Ressourcen. Damit können Änderungen in einer virtuellen Umgebung getestet und validiert werden, bevor sie in die reale Produktion übertragen werden. Die virtuelle Montageprozesssimulation ermöglicht es, Fehler wie Kollisionen zu erkennen sowie verschiedene Leistungsindikatoren wie Prozessdauer, Energieverbrauch oder Materialfluss zu ermitteln und diese zum Benchmarking der Produktionsarchitekturvarianten zu verwenden. Somit tragen diese Vorteile sowohl zur Zeit und Kostenoptimierung der Flugzeugproduktion bei, als auch zur Nachhaltigkeit des Produktes. Die vorliegende Arbeit liefert damit einen wertvollen Beitrag zur Weiterentwicklung von digitalen Lösungen in der Flugzeugproduktio

IMPLEMENTING SYSTEM ARCHITECTURE MODEL FOR SUSTAINABLE AUTOMATED AIRCRAFT CABIN ASSEMBLY PROCESS

A knowledge based engineering in the area of aeronautics for sustainable and automated cabin assembl

Digital Shadow Model for automated Cabin assembly process

Digital transformation of the shop floor focuses not only to automate the process, but also to collect and transform the process data, with which effective data analytics is feasible. Due to the advanced communication technologies and decreasing cost for data storage, the amount of data generated on shop-floors is increasing rapidly on a daily basis. Using the metadata from the shop-floor, process-improvement based on the feedback is possible with modern data analytics. Real time information from the physical system is collected and stored, from which record-and-replay of the stored information on cabin assembly process is realized. With this motivation of record-replay of events along with remote monitoring of live data, the purpose of this paper is to introduce a digital shadow model for automated cabin assembly process

Autonomous control of an Industrial robot based on formalized process description for cabin assembly

Envisioning advance assembly concepts in Aircraft manufacturing are essential for sustaining the competition and acquiring customers. In this paper we focus ourselves on describing an approach that offers adaptable process flow, reliable assembling methodology that provides faster cycle time along with safety to human workers. Further we also introduce the methodologies to program robot control from different sources which could be of interest to the Aerospace manufacturers. The process planning associated with deployment of robots and communication between the robots using external sensors are described here. Based on existing assembly model for cabin, the initial assembly instructions are written with Ontology. Time consuming activities during such assembly work are identified and interactions are reframed such that the overall assembly time is optimized. This is achieved by collecting and storing the meta-data of the robot motion which may describe the different process times, and associated robot motions. Feasibility on preempting the failure through live visualization of robot data (such as joint current, joint temperature) is studied along with analyzing and improving process by visualizing robot motions in Blender