Abstract
The emergence of IoT (Internet of Things) fuels an incipient generation of modern applications and enhancing effectiveness. Smart manufacturing is the significant aspect to meet the innovation and competitiveness in the production environment. The application of IoT avails to increment the overall understanding in the factory through connected smart objects. This paper proposes an integrated solution of sensor affixed machines, data acquisition model and data analytics. The proposed system design and implementation is pertaining to a manufacturing company to monitor the efficiency of processes in each stage in the production environment. The focus is on monitoring and inferring insights on the efficiency of machines and operators in a cloud environment. Experimental evaluation shows a drastic amendment in the shop floor visibility area by integrating sensors for data acquisition and providing insights through the analytic tool.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kortuem, G., Kawsar, F., Fitton, D., Sundramoorthy, V.: Smart objects as building blocks for the Internet of Things. IEEE Internet Comput. 14(1), 44–51 (2010). Smart Manufacturing Through Cloud-Based Smart Objects and SWE 127
Schreiber, D., Luyten, K., Mühlhäuser, M., Brdiczka, O., Hartman, M.: Introduction to the special issue on interaction with smart objects. Trans. Interact. Intell. Syst. 3(2), 6 (2013)
Fortino, G., Guerrieri, A., Russo, W.: Agent-oriented smart objects development. In: Proceedings of IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 907–912 (2012)
Fortino, G., Guerrieri, A., Lacopo, M., Lucia, M., Russo, W.: An agent-based middleware for cooperating smart objects. In: Corchado, J.M., et al. (eds.) Highlights on Practical Applications of Agents and Multi- Agent Systems. Communications in Computer and Information Science (CCIS), vol. 365, pp. 387–398. Springer, Heidelberg (2013)
Fortino, G., Guerrieri, A., Russo, W., Savaglio, C.: Middlewares for smart objects and smart environments: overview and comparison. In: Fortino, G., Trunfio, P. (eds.) Internet of Things Based on Smart Objects: Technology, Middleware and Applications. Series on the Internet of Things, pp. 1–27. Springer, Cham (2014)
Hartmann, M., Schreiber, D., Mühlhäuser, M.: Workshop on interacting with smart objects. In: Proceedings of the 16th International Conference on Intelligent User Interfaces (IUI 2011), New York, pp. 481–482 (2011)
McFarlane, D., Sarma, S., Chirn, J.L., Wong, C.Y., Ashton, K.: The intelligent product in manufacturing control and management. In: 15th Triennial World Congress IFAC, Barcelona, Spain (2002)
Bajic, E.: Ambient services modeling framework for intelligent products. In: Workshop on Smart Object Systems, UbiComp 2005, Tokyo, September 2005
Tarazona, G.M., Espada, J.P., Nunez-Valdez, E.R.: Using collaborative virtual objects based on services to communicate smart objects. In: Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), pp. 456–461 (2013)
O’Donovan, P., Leahy, K., Bruton, K., O’Sullivan, D.T.J.: An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities. J. Big Data 2, 25 (2015). A SpringerOpen Journal. doi:10.1186/s40537-015-0034-z
Liao, L., et al.: A self-aware machine platform in manufacturing shop floor utilizing MTConnect data. In: Annual Conference of the Prognostics and Health Management Society (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Balaji, V., Venkumar, P., Sabitha, M.S., Vijayalakshmi, S., Rathikaa Sre, R.M. (2018). Smart Manufacturing Through Sensor Based Efficiency Monitoring System (SBEMS) . In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-60618-7_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60617-0
Online ISBN: 978-3-319-60618-7
eBook Packages: EngineeringEngineering (R0)