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Strong market growth, upcoming global competition and the impact of customer-requirements in aerospace industry demand for more productive, flexible and cost-effective machining systems. Industrial robots have already demonstrated their advantages in smart and efficient production in a wide field of applications and industries. However, their use for machining of structural aircraft components is still obstructed by the disadvantage of low absolute accuracy and adverse reaction to process loads. This publication demonstrates and investigates different methods for performance assessment and optimization of robot-based machining systems. For conventional Cartesian CNC machining systems several methods and guidelines for performance assessment and error identification are available. Due to the attributes of a common 6-axis-robot serial kinematics these methods of decoupled and separated analysis fail, especially concerning optimization of the system.

Simulation of avionics equipment is essential due to the complex nature of its development and integration process. Throughout the development process, executable component models are used to demonstrate the feasibility and the compliance of the system design with respect to its functional requirements. In later development phases, there is the need for system integration tests where a mix of real and simulated equipment is used to verify the overall system behavior. Since Boeing 777 and Airbus A380 programs, IMA1 technology has entered several civil aircraft systems. In recent programs like Boeing 787 and Airbus A350 the number of IMA components has significantly increased. In this paper we present a simulation model for a new IMA component - the common Remote Data Concentrator (CRDC)2, which is developed by Thales-Diehl for the Airbus A350 XWB. Building simulation models of IMA components is in general a challenging task due to their complexity on both software and hardware level.