Identification and Retrieval of Relevant Information for Instantiating Digital Twins during the Construction of Process Plants
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nadège Troussier
Author: Layer, Max (1); Neubert, Sebastian (1); Tiemann, Lea (1); Stelzer, Ralph (2)
Series: ICED
Institution: 1: Siemens Energy Global GmbH & Co.KG; 2: Technische Universität Dresden
Section: Design Methods
Page(s): 2175-2184
DOI number: https://doi.org/10.1017/pds.2023.218
ISBN: -
ISSN: -
Abstract
While volume-driven industries such as automotive are characterized by a high degree of data backflow across all production cycles, there is still a certain residue in the planning and construction of process plants. This is firstly due to the high proportion of customer-specific requirements and secondly to the significant amount of value added on site during construction. To handle recurring project-specific process plants as time- and cost-efficiently as possible, optimal information exchange among contractors of various disciplines and the plant developer is a prerequisite. For this purpose, a holistic digital representation of the plant is created, which consolidates all relevant information in one place serving as a foundation of multiple digital twins. An approach to identify and define relevant information depending on their subsequent use is developed. On this basis, a framework is proposed to enable a multipliable BOM-based automatic definition of information backflow to instantiate digital representations in parallel to the planning and construction process. Furthermore, project-specific contextual information will be captured and referenced in a structured form preventing their loss for subsequent similar projects.
Keywords: Information management, Contextual Information, Instantiation, Digital / Digitised engineering value chains, Knowledge management