Causal AI-powered Digital Product Passports for enabling a circular and sustainable manufacturing ecosystem

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dc.contributor.authorOmpusunggua, Agusmian P.
dc.contributor.authorTjahjowidodo, Tegoeh
dc.contributor.authorWicaksano, H
dc.coverage.spatialCranfield, Bedfordshire
dc.date.accessioned2024-07-18T08:11:49Z
dc.date.available2024-07-18T08:11:49Z
dc.date.issued2024-06-06
dc.description.abstractDigital product passport (DPP) has been recently introduced by policymakers (e.g., the European Commission) to advance sustainable business practices towards a circular economy (CE). As a newly introduced concept, DPP is still relatively high-level and vague. Therefore, its definition, information flow architecture, what relevant information needs to be stored, and how to use such information in the context of a circular and sustainable manufacturing ecosystem, etc., are still open research questions. This paper addresses these research questions by proposing a novel conceptual framework for DPP, facilitating seamless information exchanges among CE stakeholders, and providing a transparent and trustworthy basis for decision-making. Causal AI utilisation is proposed to extract causal relationships among sustainability/circularity KPIs comprehensively, encompassing raw material supply chain, circularity-compliant product design, manufacturing optimisation on the shop floor, and after-sale product usage optimisation. Seamless information exchange will be achieved through semantic interoperability and a comprehensive model of the whole supply chain by employing an ontology model. The causal AI approach is proposed to identify causalities among KPIs and other factors to predict environmental impacts. This way, a causal model integrating domain expert knowledge and causality discovered from measured data will increase the transparency/explainability of prediction/decision made by machine learning algorithms.
dc.description.conferencename12th International Conference on Through-life Engineering Services 2024en
dc.description.sponsorshipDMG-MORI
dc.identifier.citationOmpusunggua A P, Tjahjowidodo T, Wicaksano H, (2024), Causal AI-powered Digital Product Passports for enabling a circular and sustainable manufacturing ecosystem, 12th International Conference on Through-life Engineering Services – TESConf2024, 6-7 June 2024, Cranfield UK
dc.identifier.doi10.57996/cran.ceres-2579
dc.identifier.urihttps://doi.org/10.57996/cran.ceres-2579
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22621
dc.language.isoen
dc.publisherCranfield University
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSustainability
dc.subjectCircularity
dc.subjectManufacturing
dc.subjectDigital Product Passport
dc.subjectCausal AI
dc.subjectDigital Twin (DT)
dc.subjectOntologies
dc.titleCausal AI-powered Digital Product Passports for enabling a circular and sustainable manufacturing ecosystem
dc.typeConference paper
dcterms.dateAccepted2024-03-18
dcterms.temporal.endDate07-Jun-2024
dcterms.temporal.startDate06-Jun-2024

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12th International Conference on Through-life Engineering Services 2024