Todays’ heterogeneous manufacturing environments and isolated manufacturing elements hinder the realization of a complete and data consistent digital twin. Against this background, an increased connectivity based on the Industrial Internet of Things (IIoT) might be the future key enabler for the digital twin. However, it requires each domain to transfer, rearrange and rethink their individual data solutions in a framework that is IIoT-ready. This paper presents an IIoT-based implementation of a digital twin framework for machining, enabling the creation of a complete and data consistent digital twin throughout process planning, manufacturing and quality assurance. Different use cases are introduced based on the example of a blade integrated disk for modern turbofan engines.

In this publication, the application of an implemented Digital Twin (DT) framework is presented by orchestration of CAM-integrated and containerized technology models carrying out FEM-coupled simulations for the finishing process of a simplified blade integrated disk (blisk) demonstrator. As a case study, the continuous acquisition, processing and usage of virtual process planning and simulation data as well as real machine and sensor data along the value chain is presented. The use case demonstrates the successful application of the underlying DT framework implementation for the prediction of the continuously changing dynamic behavior of the workpiece and according stable spindle speeds in the process planning phase as well as their validation in the actual manufacturing phase.

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