Efficient production monitoring on the basis of domain ontologies by utilizing IoT

• Autorzy: Riad Maha , Elgammal Amal , Elzanfaly Doaa

Identyfikatory

DOI

10.15439/2019F228

• Konferencja: Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
• Języki publikacji: EN

Abstrakty

EN

The Internet-of-Things (IoT) technologies and cyber-physical systems has facilitated production monitoring and control. However, researches and applications still lack a standardized framework and an integrated technological solution that can maximize the leverage of real-time monitoring. This can be achieved through enabling data transfer and exchange between all entities/organizations in supply chains and accordingly utilizing the monitored data. This paper introduces a framework for production monitoring that utilizes and integrates ontological model, which implements and integrates Semantic Sensor Network (SSN) ontology with production monitoring services. In addition, Complex Event Processing is integrated in the proposed model to enable event patterns identification and undertake the appropriate (pro-active) action accordingly. The framework is constructed based on ISA-95 and SCOR standards. The utility, applicability and efficacy of the proposed framework is validated by its application on a real-life large-scale case study in the domain of laser cutting machines.

Słowa kluczowe

EN

Internet of things; IoT; real-time monitoring; production monitoring

PL

Internet przedmiotów; IoT; monitorowanie w czasie rzeczywistym; monitorowanie produkcji

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2019
• Tom: Vol. 20
• Strony: 93--100
• Opis fizyczny: Bibliogr. 25 poz., tab., il.

Twórcy

autor

Riad Maha

• Faculty of Informatics and Computer Science, The British University in Egypt, Cairo, Egypt

autor

Elgammal Amal

• Faculty of Computers and Information, Cairo University, Cairo, Egypt

autor

Elzanfaly Doaa

• Faculty of Informatics and Computer Science, The British University in Egypt, Helwan University, Cairo, Egypt

Bibliografia

• 1. P. Foster, “Manufacturing Quality Control: The Difference Between Product and Process Audits,” Beacon Quality, 2018. [Online]. Available: https://www.beaconquality.com/blog/manufacturing-quality-control-the-difference-between-product-and-process-audits. [Accessed: 23-Apr-2019].
• 2. M. Ardolino et al., “The role of digital technologies for the service transformation of industrial companies,” Int. J. Prod. Res., vol. 7543, no. May, 2017. DOI: https://doi.org/10.1080/00207543.2017.1324224
• 3. V. Chaudhary, I. R. Dave, and K. P. Upla, “Automatic visual inspection of printed circuit board for defect detection and classification Automatic Visual Inspection of Printed Circuit Board for Defect Detection and Classification,” in 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2017. http://dx.doi.org/https://doi.org/10.1109/WiSPNET.2017.8299858
• 4. M. Riad, A. Elgammal, and D. ElZanfaly, “Efficient Management of Perishable Inventory by Utilizing IoT,” in 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 2018. http://dx.doi.org/https://doi.org/10.1109/ICE.2018.8436267
• 5. A. Bera, “80 Mind-Blowing IoT Statistics (Infographic),” 2019. [Online]. Available: https://safeatlast.co/blog/iot-statistics/. [Accessed: 25-May-2019].
• 6. Capgemini D. T. Institute, “Unlocking the business value of IoT in operations,” 2018.
• 7. S. Dupont, A. Achour, L. Deru, and N. Matskanis, “Bringing Dynamics to IoT Services with Cloud and Semantic Technologies An Innovative Approach for Enhancing IoT based Services,” in IoTBD 2016 - International Conference on Internet of Things and Big Data, 2016, pp. 185–190. DOI: https://doi.org/10.5220/0005933001850190
• 8. I. Szilagyi and P. Wira, “Ontologies and Semantic Web for the Internet of Things – A Survey,” in 42nd IEEE Industrial Electronics Conference, 2016. DOI: https://doi.org/10.1109/IECON.2016.7793744
• 9. M. Ganzha, M. Paprzycki, W. Pawłowski, P. Szmeja, and K. Wasielewska, “Semantic technologies for the IoT – an Inter-IoT perspective,” in 2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI), 2016. http://dx.doi.org/https://doi.org/10.1109/IoTDI.2015.22
• 10. T. Rohrmann, “Introducing Complex Event Processing (CEP) with Apache Flink.” 2016.
• 11. W3C, “Semantic Sensor Network Ontology.” Spatial Data on the Web Working Group, 2017.
• 12. K. Ding, P. Jiang, and S. Su, “RFID-enabled social manufacturing system for inter-enterprise monitoring and dispatching of integrated production and transportation tasks,” Robot. Comput. Manuf., vol. 49, no. 2018, pp. 120–133, 2017. DOI: https://doi.org/10.1016/j.rcim.2017.06.009
• 13. W. Li and S. Kara, “Methodology for Monitoring Manufacturing Environment by Using Wireless Sensor Networks ( WSN ) and the Internet of Things ( IoT ),” in The 24th CIRP Conference on Life Cycle Engineering Methodology, 2017, vol. 61, pp. 323–328. DOI: http://dx.doi.org/10.1016/j.procir.2016.11.182
• 14. Kai Ding and P. Jiang, “RFID-based Production Data Analysis in an IoT-enabled Smart Job-shop,” IEEE/CAA J. Autom. Sin., vol. 5, no. 1, pp. 1–11, 2018. http://dx.doi.org/https://doi.org/10.1109/JAS.2017.7510418
• 15. J. Lee, S. Do Noh, H. Kim, and Y. Kang, “Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control,” Sensors, vol. 18, no. 1428, 2018. DOI: 10.3390/s18051428
• 16. S. Ahmad, A. Badwelan, A. M. Ghaleb, A. Qamhan, and M. Sharaf, “Analyzing Critical Failures in a Production Process : Is Industrial IoT the Solution ?,” Wirel. Commun. Mob. Comput., vol. 2018, 2018. http://dx.doi.org/https://doi.org/10.1155/2018/6951318
• 17. Q. Cao, C. Reich, and P. Afonso, “Towards a Core Ontology for Condition Monitoring,” in Procedia Manufacturing, 2019, vol. 28, pp. 177–182. http://dx.doi.org/https://doi.org/10.1016/j.promfg.2018.12.029
• 18. N. F. Noy and Deborah L. McGuinness, “Ontology Development 101: A Guide to Creating Your First Ontology.” [Online]. Available: https://protege.stanford.edu/publications/ontology_development/ontology101-noy-mcguinness.html. [Accessed: 25-Apr-2019].
• 19. E. Maleki et al., “Ontology-based framework enabling smart Product-Service Systems : Application of sensing systems for machine health monitoring,” IEEE Internet Things J., vol. 2327, no. 4662, 2018. http://dx.doi.org/https://doi.org/10.1109/JIOT.2018.2831279
• 20. Q. Cao, F. Giustozzi, C. Zanni-merk, F. D. B. De, and C. Reich, “Smart Condition Monitoring for Industry 4 . 0 Manufacturing Processes : An Ontology-Based Approach,” Cybern. Syst. an Int. J., 2019. http://dx.doi.org/https://doi.org/10.1080/01969722.2019.1565118
• 21. D. Bogataj, M. Bogataj, and D. Hudoklin, “Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model,” Int. J. Prod. Econ., vol. 193, no. April 2016, pp. 51–62, 2017. http://dx.doi.org/https://doi.org/10.1016/j.ijpe.2017.06.028
• 22. M. P. Papazoglou and A. Elgammal, “The Manufacturing Blueprint Environment : Bringing Intelligence into Manufacturing,” in 23rd ICE/IEEE International Technology Management Conference, 2017, pp. 772–781. http://dx.doi.org/10.1109/ICE.2017.8279960
• 23. M. P. Papazoglou, A. Elgammal, and B. J. Krämer, “Collaborative on-demand Product-Service Systems customization,” CIRP J. Manuf. Sci. Technol., 2018. https://doi.org/10.1016/j.cirpj.2018.08.003
• 24. BMIR, “Protégé.” [Online]. Available: https://protege.stanford.edu/.
• 25. ISA, “ISA–95.00.01–CDV3 Enterprise-Control,” pp. 1–165, 2008.

Uwagi

1. Track 4: Information Systems and Technologies

2. Technical Session: 17th Conference on Advanced Information Technologies for Management

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).