Abstract
This paper presents solutions that leverage Semantic Web Technologies (SWT) to allow pragmatic traceability in supply-chains, especially for the textile industry. Objectives are the identification of the supply-chain, order management, tracking and problem reporting (such as dangerous substance detection). It is intended to be a generic platform supporting potentially any kind of industrial supply-chain, to be usable in harsh environments (mobile appliances) without any kind of communications possibility and to be fully usable to non-IT people, including for the modelling of the production processes. The developed solutions also allow the consumer to benefit from the traceability through information pages available by scanning the QR codes available on the finished products (clothes, clocks, etc.). This paper presents: (i) the methodology applied to achieve those functionalities, (ii) the design and implementation choices, and (iii) the test results. The main value of this paper is the usage of the Semantic Web in real-world industrial traceability solutions, which were tested in real supply-chains in Switzerland and India. The commercialization of the developed solutions has started.
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Notes
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REACH - Registration, Evaluation, Authorization and Restriction of Chemical Substances - http://ec.europa.eu/environment/chemicals/reach/reach_intro.htm.
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BPMN - Business Process Modeling and Notation - http://www.bpmn.org.
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PSL - Process Specification Language - http://www.mel.nist.gov/psl/.
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BPMO - BPMN Ontology - https://dkm.fbk.eu/index.php/BPMN_Ontology.
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Acknowledgements
We especially thank the Swiss Commission for Technology and Innovation (http://www.kti-cti.ch) who financed a big part of this project under contract number PFES-ES No. 11141.1, and the company Ontotext who supported us with a research license for OWLim SE.
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Alves, B. et al. (2014). Fairtrace: Applying Semantic Web Tools and Techniques to the Textile Traceability. In: Hammoudi, S., Cordeiro, J., Maciaszek, L., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2013. Lecture Notes in Business Information Processing, vol 190. Springer, Cham. https://doi.org/10.1007/978-3-319-09492-2_5
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