Automated repair processes and adaptive machining strategies constitute an important task in today’s aero-engine and industrial gas turbine maintenance, repair and overhaul (MRO) industry (figure 1). Currently, the repair of blisks is a central issue whenever consideration is given to replacing bladed stages with blisks; the feasibility of such a step hinges on the available capabilities for automated repair. The standard repairs are also influenced by these innovative approaches. Today, most of the processes for the MRO of engine components are carried out manually. In many cases, however, manual operations are not satisfactory from the point of view of costs and reliability. The MRO steps which are especially time consuming and require a high degree of accuracy are inspection, welding, milling and polishing. Adaptive machining methods can compensate for part-to-part variation as well as inaccurate clamping positions and keep the tolerances for the actual parts within a minimal range. The geometrical adaptation of the NC paths to the actual part geometry is performed automatically using in-process measuring techniques, mathematical best-fit strategies and adaptation methods. With the present state-of-the-art, it is possible to automate MRO work steps currently performed manually and to reduce costs and throughput times while boosting quality and precision. A further important aspect for the automation of component repair is the data management which should constitute the core of automated overhaul systems. As part of an innovative data management solution, the single repair process modules are integrated to build an automated repair cell for aero engine components. Furthermore, it is possible to establish “virtual” MRO workshops. The data management system generates a data set for each individual component and handles the logistics of the components and the accompanying data sets. As result, different MRO processes can be carried out at different facilities without loss of information, efficiency or quality. In addition, the approach described supports efficient life cycle monitoring.

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