Data management of process plants as complex systems: systematic literature review and identification of challenges and opportunities
Publikation: Beitrag in Fachzeitschrift › Übersichtsartikel (Review) › Beigetragen › Begutachtung
Beitragende
Abstract
Led by the manufacturing industry, virtual replicas of production systems also known as digital twins (DTs) are gradually moving into all areas of industry. Their advantages are characterized by the possibility of product optimization, simulations, improved monitoring and prediction of downtimes and optimized maintenance, to name just a few. The engineering, procurement and construction (EPC) of process plants as mechatronic systems is characterized by a high degree of project-specific modifications and interdisciplinary engineering effort with low reusability, in contrast to unit-production-driven areas such as automotive. This results in a high cost-benefit ratio for the creation of DTs over the life cycle of process plants, especially when suppliers are integrated into the value chain. The objective of this paper is to analyze the state of plant lifecycle management, data exchange and the possibilities of optimized supplier integration during the planning and EPC of process plants regarding DT creation and usage. Three research questions (RQs) were used to narrow down a total of 356 identified publications to 54, which were then examined. The papers covered a variety of topics, including combining discipline-specific models, plant management approaches and the combination of both.
Details
Originalsprache | Englisch |
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Seiten (von - bis) | 329-349 |
Seitenumfang | 21 |
Fachzeitschrift | Reviews in Chemical Engineering |
Jahrgang | 40 |
Ausgabenummer | 3 |
Frühes Online-Datum | Juli 2023 |
Publikationsstatus | Veröffentlicht - 14 Juli 2023 |
Peer-Review-Status | Ja |
Externe IDs
Scopus | 85165333945 |
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WOS | 001030390400001 |
Mendeley | 87724156-9b63-3bbc-927d-a25ca7f201c7 |
ORCID | /0000-0003-3957-9489/work/142256079 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Data interoperability, Digital representation, Digital twin, Instantiation, Plant lifecycle management, Process plant, Data interoperability, Digital representation, Digital twin, Instantiation, Plant lifecycle management, Process plant, process plant, digital representation, plant lifecycle management, data interoperability, digital twin, instantiation