Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 1
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

This research study intends to develop an online tool condition monitoring system and to examine scientifically the effect of machining parameters on quality measures during machining SAE 1015 steel. It is accomplished by adopting a novel microflown sound sensor which is capable of acquiring sound signals. The dry turning experiments were performed by employing uncoated, TiAlN, TiAlN/WC-C coated inserts. The optimal cutting conditions and their influence on flank wear were determined and predicted value has been validated through confirmation experiment. During machining, sound signals were acquired using NI DAQ card and statistical analysis of raw data has been performed. Kurtosis and I-Kaz coefficient was determined systematically. The correlation between flank wear and I-Kaz coefficient was established, which fits into power-law curve. The neural network model was trained and developed with least error (3.7603e-5). It reveals that the developed neural network can be effectively utilized with minimal error for online monitoring.
Go to article

Bibliography

[1] M. Noordin, V. Venkatesh, S. Sharif, J. Mater. Process. Tech. 185 (1-3), 83-90 (2007). DOI: https://doi.org/10.1016/j.jmatprotec.2006.03.137
[2] C. Moganapriya, M. Vigneshwaran, G. Abbas, A. Ragavendran, V.C. Harissh Ragavendra, R. Rajasekar, Mater. Today, Proceeding (2020).
[3] A.M. Ravi, S.M. Murigendrappa, P.G. Mukunda, T. Indian I. Metals 67 (4), 485-502 (2014). DOI: https://doi.org/10.1007/s12666-013-0369-0
[4] A.P. Kulkarni, V.G. Sargade, Mater. Manuf. Process 30 (6), 748- 755 (2015). DOI: https://doi.org/10.1080/10426914.2014.984217
[5] C. Moganapriya, R. Rajasekar, K. Ponappa, R. Venkatesh, S. Jerome, Mater. Today. Proceeding 5 (2), 8532-8538 (2018). DOI: https://doi.org/10.1016/j.matpr.2017.11.550
[6] G .C. Rosa, A.J. Souza, E.V. Possamai, H.J. Amorim, P.D. Neis, Wear 376, 172-177 (2017). DOI: https://doi.org/10.1016/j.wear.2017.01.088
[7] A. Alok, M. Das, Measurement 133, 288-302 (2019). DOI: https://doi.org/10.1016/j.measurement.2018.10.009
[8] R . Yigit, E. Celik, F. Findik, S. Koksal, Int. J. Refract. Hard. Met. 26 (6), 514-524 (2008). DOI: https://doi.org/10.1016/j.ijrmhm.2007.12.003
[9] R . Horváth, Á. Drégelyi-Kiss, G. Mátyási, Acta Polytech. Hung. 11 (2), 137-147 (2014).
[10] R . Kumar, P.S. Bilga, S. Singh, J. Clean Prod. 164, 45-57 (2017). DOI: https://doi.org/10.1016/j.jclepro.2017.06.077
[11] M.K. Gupta, P. Sood, V.S. Sharma, J. Clean Prod. 135, 1276-1288 (2016). DOI: https://doi.org/10.1016/j.jclepro.2016.06.184
[12] S . Pai, T. Nagabhushana, Handbook of Research on Emerging Trends and Applications of Machine Learning, 2020 IGI Global.
[13] A.K. Jain, B.K. Lad, J. Intell. Manuf. 30 (3), 1423-1436 (2019). DOI: https://doi.org/10.1007/s10845-017-1334-2
[14] R . Teti, K. Jemielniak, G. O’Donnell, D. Dornfeld, CIRP Ann. 59 (2), 717-739 (2010). DOI: https://doi.org/10.1016/j.cirp.2010.05.010
[15] C. Moganapriya, R. Rajasekar, K. Ponappa, R. Venkatesh, R. Karthick, Arch. Metall. Mater. 62 (3), 1827-1832 (2017). DOI: https://doi.org/10.1515/amm-2017-0276
[16] H .B. Ulas,T. Indian I. Metals 67 (6), 869-879 (2014). DOI: https://doi.org/10.1007/s12666-014-0410-y
[17] S . Thangarasu, S. Shankar, T. Mohanraj, K. Devendran, P. I. Mech. Eng. C.-J. Mec. 234 (1), 329-342 (2019).
[18] J .A. Ghani, M. Rizal, M.Z. Nuawi, C.H. Che Haron, M.J. Ghazali, M.N.A. Rahman. Trans. Tech. Publ. 2010.
[19] S . Oraby, D. Hayhurst, Int. J. Mach. Tools Manuf. 44 (12-13), 1261-1269 (2004). DOI: https://doi.org/10.1016/j.ijmachtools.2004.04.018
Go to article

Authors and Affiliations

Moganapriya Chinnasamy
1
ORCID: ORCID
Rajasekar Rathanasamy
1
ORCID: ORCID
Gobinath Velu Kaliyannan
2
ORCID: ORCID
Prabhakaran Paramasivam
1
ORCID: ORCID
Saravana Kumar Jaganathan
3 4 5
ORCID: ORCID

  1. Kongu Engineering College, Department of Mechanical Engineering, Perundurai – 638060, Tamil Nadu State, India
  2. Kongu Engineering College, Department of Mechatronics Engineering, Perundurai – 638060, Tamil Nadu State, India
  3. Bionanotechnology Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
  4. Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
  5. Department of Engineering, Faculty of Science and Engineering, University of Hull, HU6 7RX, United Kingdom

This page uses 'cookies'. Learn more