Data management of process plants as complex systems: systematic literature review and identification of challenges and opportunities

Research output: Contribution to journalReview articleContributedpeer-review

Contributors

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

Original languageEnglish
Pages (from-to)329-349
Number of pages21
JournalReviews in Chemical Engineering
Volume40
Issue number3
Early online dateJul 2023
Publication statusPublished - 14 Jul 2023
Peer-reviewedYes

External IDs

Scopus 85165333945
WOS 001030390400001
Mendeley 87724156-9b63-3bbc-927d-a25ca7f201c7
ORCID /0000-0003-3957-9489/work/142256079

Keywords

ASJC Scopus subject areas

Keywords

  • 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