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Using artificial intelligence to find design errors in the engineering drawings
Electrical, Instrumentation, Control & Safety Systems McDermott The Hague The Netherlands.ORCID-id: 0000-0003-3411-4084
Instrumentation, Control & Safety Systems McDermott The Hague The Netherlands.
Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden.
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-7700-1816
2023 (Engelska)Ingår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 35, nr 12Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Artificial intelligence is increasingly becoming important to businesses because many companies have realized the benefits of applying machine learning (ML) and deep learning (DL) in their operations. ML and DL have become attractive technologies for organizations looking to automate repetitive tasks to reduce manual work and free up resources for innovation. Unlike rule-based automation, typically used for standardized and predictable processes, machine learning, especially deep learning, can handle more complex tasks and learn over time, leading to greater accuracy and efficiency improvements. One of such promising applications is to use AI to reduce manual engineering work. This paper discusses a particular case within McDermott where the research team developed a DL model to do a quality check of complex blueprints. We describe the development and the final product of this case—AI-based software for the engineering, procurement, and construction (EPC) industry that helps to find the design mistakes buried inside very complex engineering drawings called piping and instrumentation diagrams (P&IDs). We also present a cost-benefit analysis and potential scale-up of the developed software. Our goal is to share the successful experience of AI-based product development that can substantially reduce the engineering hours and, therefore, reduce the project's overall costs. The developed solution can also be potentially applied to other EPC companies doing a similar design for complex installations with high safety standards like oil and gas or petrochemical plants because the design errors it captures are common within this industry. It also could motivate practitioners and researchers to create similar products for the various fields within engineering industry. 

Ort, förlag, år, upplaga, sidor
John Wiley & Sons, 2023. Vol. 35, nr 12
Nationell ämneskategori
Programvaruteknik
Identifikatorer
URN: urn:nbn:se:mau:diva-64286DOI: 10.1002/smr.2543ISI: 000930985800001Scopus ID: 2-s2.0-85148338919OAI: oai:DiVA.org:mau-64286DiVA, id: diva2:1818862
Tillgänglig från: 2023-12-12 Skapad: 2023-12-12 Senast uppdaterad: 2024-01-04Bibliografiskt granskad

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Olsson, Helena Holmström

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