Abstract
Smart factories are one of the biggest trends in modern manufacturing, also known as Industry 4.0. They reach a new level of process automation and make heavy use of sensors in manufactoring equipment, which brings new challenges to monitoring and diagnostics at smart factories. We propose to address the challenges with a novel rule-based monitoring and diagnostics language that relies on ontologies and reasoning and allows one to write diagnostic tasks at a high level of abstraction. We show that our approach speeds up the diagnostic routine of engineers at Siemens: they can formulate and deploy diagnostic tasks in factories faster than with existing Siemens data-driven solutions. Moreover we show that our diagnostic language, despite the built-in reasoning, allows for efficient execution of diagnostic tasks over large volumes of industrial data. Finally, we implemented our ideas in a prototypical diagnostic system for smart factories.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Arenas, M., Grau, B.C., Kharlamov, E., Marciuska, S., Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data. In: CIKM, pp. 939–948 (2014)
Arenas, M., Grau, B.C., Kharlamov, E., Marciuska, S., Zheleznyakov, D.: Faceted search over RDF-based knowledge graphs. J. Web Semant. 37–38, 55–74 (2016)
Artale, A., Kontchakov, R., Ryzhikov, V., Zakharyaschev, M.: The complexity of clausal fragments of LTL. In: McMillan, K., Middeldorp, A., Voronkov, A. (eds.) LPAR 2013. LNCS, vol. 8312, pp. 35–52. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-45221-5_3
Artale, A., Kontchakov, R., Wolter, F., Zakharyaschev, M.: Temporal description logic for ontology-based data access. In: IJCAI 2013, pp. 711–717 (2013)
Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, New York (2003)
Barbieri, D.F., Braga, D., Ceri, S., Valle, E.D., Grossniklaus, M.: C-SPARQL: a continuous query language for RDF data streams. Int. J. Semant. Comput. 4(1), 3–25 (2010)
Brandt, S., Kalaycı, E.G., Kontchakov, R., Ryzhikov, V., Xiao, G., Zakharyaschev, M.: Ontology-based data access with a Horn fragment of metric temporal logic. In: AAAI (2017)
Calvanese, D., et al.: Ontop: answering SPARQL queries over relational databases. Semant. Web 8(3), 471–487 (2017)
Calvanese, D., et al.: The MASTRO system for ontology-based data access. Semant. Web 2(1), 43–53 (2011)
Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Tractable reasoning and efficient query answering in description logics: the DL-Lite family. JAR 39(3), 385–429 (2007)
Charron, B., Hirate, Y., Purcell, D., Rezk, M.: Extracting semantic information for e-commerce. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9982, pp. 273–290. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46547-0_27
Corcho, O., Calbimonte, J.P., Jeung, H., Aberer, K.: Enabling query technologies for the semantic sensor web. Int. J. Semant. Web Inf. Syst. 8(1), 43–63 (2012)
Horrocks, I., Giese, M., Kharlamov, E., Waaler, A.: Using semantic technology to tame the data variety challenge. IEEE Internet Comput. 20(6), 62–66 (2016)
Jiménez-Ruiz, E., et al.: BootOX: practical mapping of RDBs to OWL 2. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9367, pp. 113–132. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25010-6_7
Kharlamov, E., et al.: Enabling semantic access to static and streaming distributed data with optique: demo. In: DEBS, pp. 350–353 (2016)
Kharlamov, E., et al.: Ontology-based integration of streaming and static relational data with optique. In: SIGMOD, pp. 2109–2112 (2016)
Kharlamov, E., Giacomelli, L., Sherkhonov, E., Grau, B.C., Kostylev, E.V., Horrocks, I.: Ranking, aggregation, and reachability in faceted search with semfacet. In: ISWC Posters & Demonstrations (2017)
Kharlamov, E., Giacomelli, L., Sherkhonov, E., Grau, B.C., Kostylev, E.V., Horrocks, I.: SemFacet: making hard faceted search easier. In: CIKM, pp. 2475–2478 (2017)
Kharlamov, E., et al.: Ontology based access to exploration data at statoil. In: ISWC, pp. 93–112 (2015)
Kharlamov, E., et al.: Ontology based data access in statoil. J. Web Semant. 44, 3–36 (2017)
Kharlamov, E., et al.: Optique: towards OBDA systems for industry. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds.) ESWC 2013. LNCS, vol. 7955, pp. 125–140. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41242-4_11
Kharlamov, E., et al.: Semantic access to streaming and static data at Siemens. J. Web Semant. 44, 54–74 (2017)
Kharlamov, E., et al.: A semantic approach to polystores. In: IEEE BigData, pp. 2565–2573 (2016)
Kharlamov, E., et al.: Diagnostics of trains with semantic diagnostics rules. In: Riguzzi, F., Bellodi, E., Zese, R. (eds.) ILP 2018. LNCS (LNAI), vol. 11105, pp. 54–71. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99960-9_4
Kharlamov, E., et al.: Semantic rules for machine diagnostics: execution and management. In: CIKM, pp. 2131–2134 (2017)
Kharlamov, E., et al.: How semantic technologies can enhance data access at siemens energy. ISWC 2014. LNCS, vol. 8796, pp. 601–619. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_38
Koymans, R.: Specifying real-time properties with metric temporal logic. Real-Time Syst. 2(4), 255–299 (1990)
Mehdi, G., et al.: Semantic rule-based equipment diagnostics. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10588, pp. 314–333. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68204-4_29
Mehdi, G., et al.: SemDia: semantic rule-based equipment diagnostics tool. In: CIKM, pp. 2507–2510 (2017)
Pinkel, C., et al.: RODI: benchmarking relational-to-ontology mapping generation quality. Semant. Web 9(1), 25–52 (2018)
Pinkel, C., et al.: IncMap: a journey towards ontology-based data integration. In: BTW, DBIS, pp. 145–164 (2017)
Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R.: Linking data to ontologies. J. Data Semant. 10, 133–173 (2008)
Savkovic, O., et al.: Theoretical characterization of signal diagnostic processing language. In: Description Logic Workshop (DL 2018), pp. 1–11 (2018)
Sherkhonov, E., Cuenca Grau, B., Kharlamov, E., Kostylev, E.V.: Semantic faceted search with aggregation and recursion. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 594–610. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68288-4_35
Soylu, A., Giese, M., Jiménez-Ruiz, E., Kharlamov, E., Zheleznyakov, D., Horrocks, I.: Ontology-based end-user visual query formulation: why, what, who, how, and which? Univers. Access Inf. Soc. 16(2), 435–467 (2017)
Soylu, A., et al.: Querying industrial stream-temporal data: an ontology-based visual approach. JAISE 9(1), 77–95 (2017)
Soylu, A., et al.: OptiqueVQS: a visual query system over ontologies for industry. Semant. Web 9(5), 627–660 (2018)
Vachtsevanos, G., Lewis, F.L., Roemer, M., Hess, A., Wu, B.: Intelligent Fault Diagnosis and Prognosis for Engineering Systems. Wiley, Hoboken (2006)
Acknowledgments
This research is supported by the EPSRC projects MaSI\(^3\), DBOnto, ED\(^3\), and by the SIRIUS Centre, Norwegian Research Council project number 237898. Also it is partially supported by the Free University of Bozen-Bolzano projects QUEST, ROBAST and QUADRO.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Savković, O. et al. (2018). Semantic Diagnostics of Smart Factories. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds) Semantic Technology. JIST 2018. Lecture Notes in Computer Science(), vol 11341. Springer, Cham. https://doi.org/10.1007/978-3-030-04284-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-04284-4_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-04283-7
Online ISBN: 978-3-030-04284-4
eBook Packages: Computer ScienceComputer Science (R0)