Novel method enhances repair processes in turbine blades, suggesting significant automation in manufacturing.
Remanufacturing and repair processes are key to circularity in manufacturing. However, process set-up is highly challenging due to the strong individuality of wear and damage of the used turbine blades. A novel method is presented that combines the cyber-physical production system with a digital twin to optimize planning in the process chain of automatic turbine blade repair. The contribution focuses on the capability of the digital twin to react to uncertainties given by the varying geometry of degenerated turbine blades as well as process variances during additive manufacturing. Therefore, a Dexel-based NC simulation of the additive and subtractive processes is realized by using real machine kinematics and axis data. Physical models were developed and integrated to realize a technological simulation that predicts the geometry, hardness, and porosity of the deposited material during the process. Based on this, the influence of the additive process on the subtractive process is investigated by considering uncertainties. The presented method contributes to the automated process set-up in the cyber-physical production system for individual parts to ensure qualified and efficient processes. The manual effort is reduced due to a high degree of automation.
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Denkena et al. (2025) studied this question.
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