Knowledge Graphs for Efficient Integration and Access of Manufacturing Data

Achieving interoperability is a crucial factor for realizing the Industry 4.0 (I4.0) vision. In I4.0 different systems exist, and the demand for the creation of an integrated view using the existing data increases. However, interoperability between data sources is hampered due to different representation of similar processes or production parts. In this paper, we present a knowledge graph based approach for semantically integrating data sources in I4.0 scenarios. To tackle the problem of interoperability, we developed the Bosch Industry 4.0 Knowledge Graph (BI40KG). The BI40KG comprises a set of ontologies for describing common concepts and relations that can be reused in the domain. We present a general approach for using the BI40KG to semantically integrate data from different data sources in I4.0. The benefits of such an approach are manifold. Besides achieving interoperability, the semantics encoded in BI40KG allow for creating a common understating across I4.0 applications that are developed. In addition, KG based data integration enables effortless tracebility of product parts for production lines which in general is a tedious task. Two use cases are presented to demonstrate the applicability of the described approach.

[1]  Guangyi Liu,et al.  Enhancement of Power Equipment Management Using Knowledge Graph , 2019, 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia).

[2]  W. Marsden I and J , 2012 .

[3]  Irlán Grangel-González,et al.  Realizing an RDF-Based Information Model for a Manufacturing Company - A Case Study , 2017, SEMWEB.

[4]  Irlán Grangel-González Semantic Data Integration for Industry 4.0 Standards , 2016, EKAW.

[5]  Achim Rettberg,et al.  Using Ontology and Standard Middleware for integrating IoT based in the Industry 4.0 , 2018 .

[6]  Diego Calvanese,et al.  Ontology-Based Data Access: A Survey , 2018, IJCAI.

[7]  G. Tortorella,et al.  Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies , 2018, Int. J. Prod. Res..

[8]  Thomas Olzak,et al.  What is virtualization , 2009 .

[9]  Michelle Cheatham,et al.  Semantic Data Integration , 2017, Handbook of Big Data Technologies.

[10]  Steffen Lamparter,et al.  Use Cases of the Industrial Knowledge Graph at Siemens , 2018, SEMWEB.

[11]  Marek Obitko,et al.  Understanding Data Heterogeneity in the Context of Cyber-Physical Systems Integration , 2017, IEEE Transactions on Industrial Informatics.

[12]  Jens Lehmann,et al.  Distributed Semantic Analytics Using the SANSA Stack , 2017, SEMWEB.

[13]  Peter Clark,et al.  Semantic Integration of Heterogeneous Information Sources Using a Knowledge-Based System , 2000 .

[14]  Anees Mehdi,et al.  Ontologies and Reasoning to Capture Product Complexity in Automation Industry , 2017, International Semantic Web Conference.

[15]  Natasha Noy,et al.  Industry-scale Knowledge Graphs: Lessons and Challenges , 2019, ACM Queue.

[16]  Thorsten Liebig,et al.  Building a Knowledge Graph for Products and Solutions in the Automation Industry , 2019, KGB@ESWC.

[17]  Wenjun Xu,et al.  Open Industrial Knowledge Graph Development for Intelligent Manufacturing Service Matchmaking , 2017, 2017 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII).

[18]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[19]  Diego Calvanese,et al.  Virtual Knowledge Graphs: An Overview of Systems and Use Cases , 2019, Data Intelligence.

[20]  Diego Calvanese,et al.  OBDA with the Ontop Framework , 2015, SEBD.

[21]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[22]  Malte Brettel,et al.  How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective , 2014 .

[23]  Peng Wang,et al.  Manufacturing Ontology Development Based on Industry 4.0 Demonstration Production Line , 2016, 2016 Third International Conference on Trustworthy Systems and their Applications (TSA).