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IDENTIFICATION AND RETRIEVAL OF RELEVANT INFORMATION FOR INSTANTIATING DIGITAL TWINS DURING THE CONSTRUCTION OF PROCESS PLANTS

Published online by Cambridge University Press:  19 June 2023

Max Layer*
Affiliation:
Siemens Energy Global GmbH & Co.KG;
Sebastian Neubert
Affiliation:
Siemens Energy Global GmbH & Co.KG;
Lea Tiemann
Affiliation:
Siemens Energy Global GmbH & Co.KG;
Ralph Stelzer
Affiliation:
Technische Universität Dresden
*
Layer, Max, Siemens Energy Global GmbH & Co.KG, Germany, [email protected]

Abstract

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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.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

2014/68/EU. Pressure Equipment Directive, 2014. (accessed 2/15/2023).Google Scholar
Ackoff, Russell L. (1989). From data to wisdom. Journal of applied systems analysis 16 (1), 39.Google Scholar
Ballesteros, John R. (Ed.) (2004). Meta-model instantiation for geoscientific data collection. ITC.Google Scholar
Bosché, Frédéric/Ahmed, Mahmoud/Turkan, Yelda/Haas, Carl T./Haas, Ralph (2015). The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components. Automation in Construction 49, 201213. https://doi.org/10.1016/j.autcon.2014.05.014.CrossRefGoogle Scholar
Braaksma, A.J.J./Klingenberg, W./ van Exel, P.W.H.M. (2011). A review of the use of asset information standards for collaboration in the process industry. Computers in industry 62 (3), 337350. https://doi.org/10.1016/j.compind.2010.10.003.CrossRefGoogle Scholar
Brundage, Michael P./Sexton, Thurston/Hodkiewicz, Melinda/Dima, Alden/Lukens, Sarah (2021). Technical language processing: Unlocking maintenance knowledge. Manufacturing Letters 27, 4246. https://doi.org/10.1016/j.mfglet.2020.11.001.CrossRefGoogle Scholar
Eigner, Martin/Stelzer, Ralph (2009). Product lifecycle management: Ein Leitfaden für product development und life cycle management. Springer Science & Business Media.CrossRefGoogle Scholar
Elfving, Jan Alarik (2003). Exploration of opportunities to reduce lead times for engineered-to-order products. Berkeley, University of California.Google Scholar
Esfahani, Mansour Esnaashary/Rausch, Christopher/Sharif, Mohammad Mahdi/Chen, Qian/Haas, Carl/Adey, Bryan T. (2021). Quantitative investigation on the accuracy and precision of Scan-to-BIM under different modelling scenarios. Automation in Construction 126, 103686. https://doi.org/10.1016/j.autcon.2021.103686.CrossRefGoogle Scholar
Ge, Zhiqiang/Song, Zhihuan/Ding, Steven X./Huang, Biao (2017). Data Mining and Analytics in the Process Industry: The Role of Machine Learning. IEEE Access 5, 2059020616. https://doi.org/10.1109/ACCESS.2017.2756872.CrossRefGoogle Scholar
Gepp, M./Vollmar, J./Schaeffler, T. (2014). Standardization programs in the industrial plant business: Best practices and lessons learned. In: 2014 IEEE International Conference on Industrial Engineering and Engineering Management, 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Selangor Darul Ehsan, Malaysia, 09.12.2014 - 12.12.2014. IEEE, 122126.CrossRefGoogle Scholar
Gorecky, Dominic/Weyer, Stephan/Hennecke, André/Zühlke, Detlef (2016). Design and Instantiation of a Modular System Architecture for Smart Factories. IFAC-PapersOnLine 49 (31), 7984. https://doi.org/10.1016/j.ifacol.2016.12.165.CrossRefGoogle Scholar
Hicks, B. J./Culley, S. J./Allen, R. D./Mullineux, G. (2002). A framework for the requirements of capturing, storing and reusing information and knowledge in engineering design. International Journal of Information Management 22 (4), 263280. https://doi.org/10.1016/S0268-4012(02)00012-9.CrossRefGoogle Scholar
IEC 62337:2012. Commissioning of electrical, instrumentation and control systems in the process industry, 2012. Geneva, Switzerland. (accessed 11/7/2022).Google Scholar
IEC 62381:2012. Automation systems in the process industry, 2012. Geneva, Switzerland. (accessed 11/2/2022).Google Scholar
Ismail, Ali/Strug, Barbara/Ślusarczyk, Grażyna (2018). Building Knowledge Extraction from BIM/IFC Data for Analysis in Graph Databases. In: Leszek Rutkowski/Rafał Scherer/Marcin Korytkowski et al. (Eds.). Artificial Intelligence and Soft Computing. Cham, Springer International Publishing, 652664.CrossRefGoogle Scholar
ISO 2382-1:1993. Information technology - Vocabulary - Part 1: Fundamental Terms, 1993. Switzerland. (accessed 11/21/2022).Google Scholar
ISO 23952:2020. Automation systems and integration — Quality information framework (QIF), 2020. Switzerland. (accessed 10/31/2022).Google Scholar
Jiang, Shuo/Hu, Jie/Magee, Christopher L./Luo, Jianxi (2022). Deep Learning for Technical Document Classification. IEEE Transactions on Engineering Management, 117. https://doi.org/10.1109/TEM.2022.3152216.CrossRefGoogle Scholar
Kim, Byung Chul/Kim, Bongcheol/Park, Sangjin/Teijgeler, Hans/Mun, Duhwan (2020). ISO 15926–based integration of process plant life-cycle information including maintenance activity. Concurrent Engineering 28 (1), 5871. https://doi.org/10.1177/1063293X19894041.CrossRefGoogle Scholar
Lechler, Armin/Riedel, Oliver/Coupek, Daniel (2017). VIRTUAL REPRESENTATION OF PHYSICAL OBJECTS FOR SOFTWARE DEFINED MANUFACTURING.CrossRefGoogle Scholar
Lettenmeier, Philipp (2020). Efficiency – Electrolysis. White Paper. Available online at https://assets.siemens-energy.com/siemens/assets/api/uuid:a33a8c39-b694-4d91-a0b5-4d8c9464e96c/efficiency-white-paper.pdf.Google Scholar
Li, Zhanjun/Raskin, Victor/Ramani, Karthik (2008). Developing Engineering Ontology for Information Retrieval. Journal of Computing and Information Science in Engineering 8 (1). https://doi.org/10.1115/1.2830851.CrossRefGoogle Scholar
Liew, Anthony (2007). Understanding data, information, knowledge and their inter-relationships. Journal of knowledge management practice 8 (2), 116.Google Scholar
Luttmer, Janosch/Ehring, Dominik/Pluhnau, Robin/Nagarajah, Arun (2021). REPRESENTATION AND APPLICATION OF DIGITAL STANDARDS USING KNOWLEDGE GRAPHS. Proceedings of the Design Society 1, 25512560. https://doi.org/10.1017/pds.2021.516.CrossRefGoogle Scholar
Mallier, Lise/Hétreux, Gilles/Thery-Hétreux, Raphaele/Baudet, Philippe (2021). A modelling framework for energy system planning: Application to CHP plants participating in the electricity market. Energy 214, 118976.CrossRefGoogle Scholar
Martinez, Gerardo Santillan/Sierla, Seppo/Karhela, Tommi/Vyatkin, Valeriy (2018). Automatic Generation of a Simulation-Based Digital Twin of an Industrial Process Plant. In: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, Washington, DC, 21.10.2018 - 23.10.2018. IEEE, 30843089.CrossRefGoogle Scholar
May, Marvin Carl/Overbeck, Leonard/Wurster, Marco/Kuhnle, Andreas/Lanza, Gisela (2021). Foresighted digital twin for situational agent selection in production control. Procedia CIRP 99, 2732. https://doi.org/10.1016/j.procir.2021.03.005.CrossRefGoogle Scholar
McAllester, David/Zabih, Ramin (1986). Boolean classes. In: Conference proceedings on Object-oriented programming systems, languages and applications, 417423.CrossRefGoogle Scholar
Nouri, Mahdi/Lucke, Eberhard (2022). Life cycle of a process plant. Amsterdam, Netherlands, Elsevier.Google Scholar
Pinquié, Romain/Véron, Philippe/Segonds, Frédéric/Zynda, Thomas (2019). A Property Graph Data Model for a Context-Aware Design Assistant. In: Clement Fortin/Louis Rivest/Alain Bernard et al. (Eds.). Product Lifecycle Management in the Digital Twin Era. Cham, Springer International Publishing, 181190.CrossRefGoogle Scholar
Ramírez, José/Molina, Arturo (2021). Improving Manufacturing System Design by Instantiation of the Integrated Product, Process and Manufacturing System Development Reference Framework. In: Alexandre Dolgui/Alain Bernard/David Lemoine et al. (Eds.). Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. Cham, Springer International Publishing, 99107.CrossRefGoogle Scholar
Saske, Bernhard/Schwoch, Sebastian/Paetzold, Kristin/Layer, Max/Neubert, Sebastian/Leidich, Jonathan/Robl, Peter (2022). Digitale Abbilder als Basis Digitaler Zwillinge im Anlagenbau: Besonderheiten, Herausforderungen und Lösungsansätze. Industrie 4.0 Management 2022 (5), 2124. https://doi.org/10.30844/IM_22-5_21-24.CrossRefGoogle Scholar
Shafiee, Sara/Kristjansdottir, Katrin/Hvam, Lars (2017). Automatic Identification of Similarities across Products to Improve the Configuration Process in ETO Companies. International Journal of Industrial Engineering and Management 8, 167176.CrossRefGoogle Scholar
Son, Hyojoo/Bosché, Frédéric/Kim, Changwan (2015). As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure: A survey. Advanced Engineering Informatics 29 (2), 172183. https://doi.org/10.1016/j.aei.2015.01.009.CrossRefGoogle Scholar
Stark, Rainer/Kind, Simon/Neumeyer, Sebastian (2017). Innovations in digital modelling for next generation manufacturing system design. CIRP Annals 66 (1), 169172. https://doi.org/10.1016/j.cirp.2017.04.045.CrossRefGoogle Scholar
Tang, D./Clarke, J. A. (1993). Application of the object oriented programming paradigm to building plant system modelling. In: Proceedings of the Building Simulation, 317323.Google Scholar
Consulting Group, THEMA (2021). Hydrogen deployment accelerates, but a lot remains to reach 40 GW EU target by 2030. Available online at https://thema.no/en/nyheter/store-steg-naermere-men-langt-igjen-til-40-gw-elektrolyse-i-eu-i-2030/ (accessed 11/7/2022).Google Scholar
Udeaja, Chika E./Kamara, John M./Carrillo, Patricia M./Anumba, Chimay J./Bouchlaghem, Nasreddine/Tan, Hai Chen (2008). A web-based prototype for live capture and reuse of construction project knowledge. Automation in Construction 17 (7), 839851. https://doi.org/10.1016/j.autcon.2008.02.009.CrossRefGoogle Scholar
Watermeyer, Peter (2002). Handbook for process plant project engineers. John Wiley & Sons.Google Scholar
Wheeler, Robert/Rosenblum, Bruce/West, Lesley (Eds.) (2016). NISO STS Project Overview and Update. National Center for Biotechnology Information (US).Google Scholar
Zhao, Huaxuan/Pan, Yueling/Yang, Feng (2020). Research on Information Extraction of Technical Documents and Construction of Domain Knowledge Graph. IEEE Access 8, 168087–168098. https://doi.org/10.1109/ACCESS.2020.3024070.CrossRefGoogle Scholar