Preventive maintenance of taper bearing using Arduino in the application of industry 4.0

  • Subekti Subekti Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
  • Hadi Pranoto Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
  • Beni Rukasah Salmon SMK Negeri 1 Majalaya, JL. H. Idris NO 99 Majalaya Bandung, Jawa Barat, Indonesia
  • Setyo Qomarudin Yusuf Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
  • Suyadiyanto Suyadiyanto Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
  • Ari Slamet Ariyadi Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
  • Abdul Hamid Mechanical Engineering Vibration Laboratory, Universitas Mercu Buana, Indonesia
Keywords: Arduino, Internet of Things, Labview, predictive maintenance, taper bearing

Abstract

The maintenance of industrial tools is very important to support production. Therefore, many companies apply preventive maintenance. A national industrialization agenda discussed that it is crucial especially in the manufacturing industry. The battery-powered IoT sensing device is capable of thorough monitoring of industrial machinery enabling the development of sophisticated predictive maintenance applications under set scenarios. In this paper, we applied the concept of the Internet of Thing (IoT) system using LabVIEW via Arduino. The research method used in this study was similar to Susanto et al. (2019) namely Frequency Response Function (FRF) test to investigate the dynamic characteristics of a mechanic structure to identifying damages on X, Y, and Z axes of tapered bearing using harmonic vibration from handphones. Results of FRF and Labview via Ardunio were then compared to identify the results of measurement using LabView via Arduino. It was found much noise in the measurement occupying Labview Via Ardunio because its system does not use a filter like the one in FFT Analyser. However, in general, LabVIEW via Ardunia can predict damages in taper bearing. It is because, under broken condition, there was a two-time movement of natural frequencies from good condition.

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References

Aslan, A. (2019). Peran Pola Asuh Orangtua di Era Digital. Jurnal Studia Insania, 7(1), 20-34.

Aslan, A. (2019). Pergeseran Nilai Di Masyarakat Perbatasan (Studi tentang Pendidikan dan Perubahan Sosial di Desa Temajuk Kalimantan Barat).

Aslan, A. (2020). Pengembangan bahan ajar berbasis imtaq dan iptek di era revolusi industri 4.0 pada mata pelajaran sains madrasah ibtidaiyah. TaLimuna: Jurnal Pendidikan Islam, 9(1), 1-15. https://doi.org/10.32478/talimuna.v9i1.345

Aslan, A., & Setiawan, A. (2019). Internalization of value education in temajuk-melano malaysia border school. Edukasia: Jurnal Penelitian Pendidikan Islam, 14(2), 419-436.

Biantoro, A. W., Maryanto, H., Hidayanto, A. K., & Hamid, A. The investigation of end mill feeds on cnc router machine using vibration method.

Cao, B., Wang, Y., Wen, D., Liu, W., Wang, Jingli, Fan, G., Ruan, L., Song, B., Cai, Y., Wei, M., Li, X., Xia, J., Chen, N., Xiang, J., Yu, T., Bai, T., Xie, X., Zhang, L., Li, C., Yuan, Y., Chen, H., Li, Huadong, Huang, H., Tu, S., Gong, F., Liu, Y., Wei, Y., Dong, C., Zhou, F., Gu, X., Xu, J., Liu, Z., Zhang, Y., Li, Hui, Shang, L., Wang, K., Li, K., Zhou, X., Dong, X., Qu, Z., Lu, S., Hu, X., Ruan, S., Luo, S., Wu, J., Peng, L., Cheng, F., Pan, L., Zou, J., Jia, C., Wang, Juan, Liu, X., Wang, S., Wu, X., Ge, Q., He, J., Zhan, H., Qiu, F., Guo, L., Huang, C., Jaki, T., Hayden, F.G., Horby, P.W., Zhang, D., Wang, C. (2020). A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19. New England Journal of Medicine 0, 1–13. https://doi.org/10.1056/NEJMoa2001282

Çimen, O., Topbaşoğlu, T., & Saklakoğlu, I. E. (2020). Industry 4.0 applications in wet wipes machines. Industry 4.0, 5(1), 7-9.

Civerchia, F., Bocchino, S., Salvadori, C., Rossi, E., Maggiani, L., & Petracca, M. (2017). Industrial Internet of Things monitoring solution for advanced predictive maintenance applications. Journal of Industrial Information Integration, 7, 4-12. https://doi.org/10.1016/j.jii.2017.02.003

Firouzi, F., Farahani, B., Weinberger, M., DePace, G., & Aliee, F. S. (2020). IoT Fundamentals: Definitions, Architectures, Challenges, and Promises. In Intelligent Internet of Things (pp. 3-50). Springer, Cham. https://doi.org/10.1007/978-3-030-30367-9_1

Hamid, A. (2011). The Investigation of the Effect of Heaving and Pitching on Wave-Induced Vertical Hull Vibration of a Container Ship in Regular Waves. Journal of Mechanics Engineering and Automation, 1(6), 491-496.

Hammid, A., & Biantoro, A. W. (2018, November). Identifying the Nonlinearity of Structures Dynamics by Wavelet Packet Decomposition. In IOP Conference Series: Materials Science and Engineering (Vol. 453, No. 1, p. 012003). IOP Publishing. https://doi.org/10.1088/1757-899X/453/1/012003

Jena, M. C., Mishra, S. K., & Moharana, H. S. (2020). Application of Industry 4.0 to enhance sustainable manufacturing. Environmental Progress & Sustainable Energy, 39(1), 13360. https://doi.org/10.1002/ep.13360

Jung, D., Zhang, Z., & Winslett, M. (2017, April). Vibration analysis for iot enabled predictive maintenance. In 2017 IEEE 33rd International Conference on Data Engineering (ICDE) (pp. 1271-1282). IEEE. https://doi.org/10.1109/ICDE.2017.170

Martinov, G. M., Kovalev, I. A., & Chervonnova, N. Y. (2020, January). Development of a platform for collecting information on the operation of technological equipment with the use of Industrial Internet of Things. In IOP Conference Series: Materials Science and Engineering (Vol. 709, No. 4, p. 044063). IOP Publishing. https://doi.org/10.1088/1757-899X/709/4/044063

Parpala, R. C., & Iacob, R. (2017). Application of IoT concept on predictive maintenance of industrial equipment. In MATEC Web of Conferences (Vol. 121, p. 02008). EDP Sciences. https://doi.org/10.1051/matecconf/201712102008

Putra, P., Mizani, H., Basir, A., Muflihin, A., Aslan (2020). The Relevancy on Education Release Revolution 4.0 in Islamic Basic Education Perspective in Indonesia: TEST Engineering & Management 83, 10256–10263.

Sahal, R., Breslin, J. G., & Ali, M. I. (2020). Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case. Journal of Manufacturing Systems, 54, 138-151. https://doi.org/10.1016/j.jmsy.2019.11.004

Sang, G. M., Xu, L., de Vrieze, P. T., Bai, Y., & Pan, F. (2020). Predictive maintenance in Industry 4.0.

Sang, G. M., Xu, L., de Vrieze, P., & Bai, Y. (2020, June). Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE. In International Conference on Advanced Information Systems Engineering (pp. 17-28). Springer, Cham. https://doi.org/10.1007/978-3-030-49165-9_2

Sang, G. M., Xu, L., de Vrieze, P., & Bai, Y. (2020, June). Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE. In International Conference on Advanced Information Systems Engineering (pp. 17-28). Springer, Cham.

Susanto, Y. K., Pirzada, K., & Adrianne, S. (2019). Is tax aggressiveness an indicator of earnings management?. Polish Journal of Management Studies, 20.

Yamato, Y., Fukumoto, Y., & Kumazaki, H. (2017). Predictive maintenance platform with sound stream analysis in edges. Journal of Information processing, 25, 317-320. https://doi.org/10.2197/ipsjjip.25.317

Published
2020-07-08
How to Cite
Subekti, S., Pranoto, H., Salmon, B. R., Yusuf, S. Q., Suyadiyanto, S., Ariyadi, A. S., & Hamid, A. (2020). Preventive maintenance of taper bearing using Arduino in the application of industry 4.0. International Research Journal of Engineering, IT & Scientific Research, 6(4), 1-14. https://doi.org/10.21744/irjeis.v6n4.953
Section
Articles