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The simulation of production processes using a Digital Twin is a promising tool for predictive planning, analysis of existing systems or process-parallel monitoring. In the process industry, the concept of Digital Twin provides significant support for process optimization. The generation of the Digital Twin of an already existing plant is a major challenge – in particular for small and medium-sized enterprises. In this sense, the twinning of the existing physical environment has got a particular importance due to high effort. Shape segmentation from unstructured (e.g. point cloud data) is a core step of the digital twinning process for industrial facilities. This is an inherent issue of Product Lifecycle Management how to acquire data of existing goods. The practice of Digital Twin is described based on object recognition by using methods of Machine Learning. The exploration of the pipeline semantics presents a particular challenge. The highly automated procedure for the generation of Digital Twin is described based on a use case of a biogas plant. Commercial deployment, pitfalls, drawbacks and potential for further developments are further explored.

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Ships are complex, often unique products. They are made of hundreds of thousands to millions of single parts and components which have to be created and placed as part of the design process, managed in bills of materials for part manufacturing or purchasing and assigned to assembly stages for production planning and logistics. In this paper we will present our advances with the practical application of our 2017 analysis results of the differences between dedicated “intent-driven” ship building systems and more general mechanical CAD based systems [1]. Being able to evolve the digital master of the ship along the ship development process from contract design to manufacturing without information flow breaks – and eventually becoming a digital twin during the product’s operational life – is a major digital thread capability. The second important capability is configuration management, enabling involved parties to know which parts are currently valid for design, manufacturing and operation.

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