Abstract
Cloud manufacturing will play a significant role in future manufacturing, enabling companies to share resources and equipping them with scalable, flexible as well as cost-efficient manufacturing solutions with cheaper maintenance. With the main focus on cloud manufacturing, this paper aims to propose new devices for monitoring of manufacturing processes. The proposed self-powered wireless devices cover two main groups: rotating and non-rotating cutting tools. The most common rotating tool—mill—and non-rotating one—turning tool—are examined. Energy harvesting from the accelerations of the rotating cutting tool is mostly influenced by the speed of the tool and the number of cutting edges, while energy harvesting from the non-rotating tool is affected by the vibration modes of the tool. A significant difference between these two types of excitation frequencies obliges to use cantilever for energy harvesting from the rotating tool and disc-shaped piezoelectric harvesters for the non-rotating tool. The results of theoretical and experimental studies of the dynamics of these harvesters show an effective way for approaching their natural frequencies to the resonant frequencies of the cutting tools. The amplitude-frequency analysis of vibrations of the tool could be useful for the technological process monitoring as well as for the evaluation of machine tool state. Vibration and acoustic signal analysis using fast Fourier transform (FFT) enables to identify the level of tool wear and, moreover, the mode of tool fixture and technical state of the spindle. As the intensity of energy accumulation depends on the state of the cutting tool wear, it indicates and detects the tool condition. The voltage generated from the cutting tool vibrations of the harvester exponentially rises till the capacitor is fully charged and a wireless signal is sent to the receiver. All the proposed technique and methods are inseparable from cloud manufacturing technologies.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Dargie W, Poellabauer C (2010) Fundamentals of wireless sensor networks: theory and practice. Wiley, West Sussex, 330 p
Cuzzocrea A, Fortino G (2013) Managing data and processes in cloud-enabled large-scale sensor networks: state-of-the-art and future research directions. In: 13th IEEE/ACM international symposium on cluster, cloud, and grid computing: 583–588
Govindan R, Hellerstein JM, Hong W, Madden S, Franklin M, Shenker S (2002) The sensor network as a database. University of Southern California: 1–8
Lu B, Habetler TG, Harley RG, Gutierrez JA, Durocher DB (2007) Energy evaluation goes wireless. IEEE Ind Appl Mag 13(2):17–23
Jagannath VMD, Raman B (2007) WiBeaM: wireless bearing monitoring system. In: Communication systems software and middleware, COMSWARE, 2nd international conference: 1–8
Wright P, Dornfeld D, Hillaire R, Ota N (2006) Tool temperature measurement and its integration within a manufacturing system. Trans of NAMRI/SME 34:63–70
Sudararajan V, Redfern A, Schneider M, Wright P (2005) Wireless sensor networks for machinery monitoring. In: ASME International Mechanical Engineering Congress and Exposition
Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. Ann CIRP 44(1):357–362
Ghosh N, Ravi YB, Patra A, Mukhopadhyay S, Paul S, Mohanty AR, Chattopadhyay AB (2007) Estimation of tool wear during CNC milling using neural network-based sensor fusion. Mech Syst Signal Process 21(1):466–479
Jardine AKS, Lin D, Banjevic D (2006) A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech Syst Signal Process 20(7):1483–1510
Ramamurthy H, Prabhu BS, Gadh R, Madni AM (2007) Wireless industrial monitoring and control using a smart sensor platform. IEEE Sensors J 7(5–6):611–618
Koumpis K, Hanna L, Andersson M, Johansson M (2005) Wireless industrial control and monitoring beyond cable replacement. In: Profibus international conference. Coombe Abbey, Warwickshire, UK
Korber HJ, Wattar H, Scholl G (2007) Modular wireless real-time sensor/actuator network for factory automation applications. IEEE Trans Indust Inform 3(2):111–119
Johnstone I, Nicholson J, Shehzad B, Slipp J (2007) Experiences from a wireless sensor network deployment in a petroleum environment. In: Proceedings of international conference on wireless communications and mobile computing, Honolulu
Krishnamurthy L, Adler R, Buonadonna P, Chhabra J, Flanigan M, Kushalnagar N, Nachman L, Yarvis M (2005) Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the North Sea. In: ACM SenSys
Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manufac 28(1):75–86
Pallis G (2010) Cloud computing: the new frontier of internet computing. IEEE Internet Comput 2010:70–73
Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360 degree compared. In: Grid computing environments workshop
Kunio T (2010) NEC cloud computing system. I: NEC Tech J 5(2):10–15
Dikaiakos MD, Katsaros D, Mehra P, Pallis G, Vakali A (2009) Cloud computing: distributed internet computing for IT and scientific research. IEEE Internet Comput 13(5):10–11
Ryan MD (2011) Viewpoint cloud computing privacy concerns on our doorstep. Commun ACM 54(1):36–38
Ostasevicius V, Gaidys R, Rimkeviciene J, Dauksevicius R (2010) An approach based on tool mode control for surface roughness reduction in high-frequency vibration cutting. J Sound Vibrat 329(23):4866–4879
Ostasevicius V, Milasauskaite I, Dauksevicius R, Baltrusaitis V, Grigaliunas V, Prosycevas I (2010) Experimental characterization of material structure of piezoelectric PVDF polymer. Mechanika 6:78–82
Rao SS (2007) Vibration of continuous systems. Wiley, New York, 720 p
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Ostasevicius, V., Jurenas, V., Markevicius, V. et al. Self-powering wireless devices for cloud manufacturing applications. Int J Adv Manuf Technol 83, 1937–1950 (2016). https://doi.org/10.1007/s00170-015-7617-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-015-7617-x