Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel

Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel

This research presents the parametric effect of machining control variables while turning EN31 alloy steel with a Chemical Vapor deposited (CVD) Ti(C,N) + Al<sub>2</sub>O<sub>3</sub> + TiN coated carbide tool insert. Three machining parameters with four levels considered in t...

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Main Authors: Ishwer Shivakoti, Lewlyn L.R. Rodrigues, Robert Cep, Premendra Mani Pradhan, Ashis Sharma, Akash Kumar Bhoi
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Materials
Subjects:
alloy steel
feed
ANFIS
RPM
turning
Online Access:https://www.mdpi.com/1996-1944/13/14/3137
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record_format Article
spelling doaj-f471b116761e4d038e15637a9ac0ded32020-11-25T02:35:57ZengMDPI AGMaterials1996-19442020-07-01133137313710.3390/ma13143137Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy SteelIshwer Shivakoti0Lewlyn L.R. Rodrigues1Robert Cep2Premendra Mani Pradhan3Ashis Sharma4Akash Kumar Bhoi5Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar 737136, IndiaDepartment of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higher Education, Mangalore 576104, IndiaVSB-TU Ostrava, Faculty of Mechanical Engineering, 17. listopadu 2172/15, 708 00 Ostrava, Czech RepublicDepartment of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar 737136, IndiaDepartment of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar 737136, IndiaDepartment of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar 737136, IndiaThis research presents the parametric effect of machining control variables while turning EN31 alloy steel with a Chemical Vapor deposited (CVD) Ti(C,N) + Al<sub>2</sub>O<sub>3</sub> + TiN coated carbide tool insert. Three machining parameters with four levels considered in this research are feed, revolutions per minute (RPM), and depth of cut (a<sub>p</sub>). The influences of those three factors on material removal rate (MRR), surface roughness (Ra), and cutting force (Fc) were of specific interest in this research. The results showed that turning control variables has a substantial influence on the process responses. Furthermore, the paper demonstrates an adaptive neuro fuzzy inference system (ANFIS) model to predict the process response at various parametric combinations. It was observed that the ANFIS model used for prediction was accurate in predicting the process response at varying parametric combinations. The proposed model presents correlation coefficients of 0.99, 0.98, and 0.964 for MRR, Ra, and Fc, respectively.https://www.mdpi.com/1996-1944/13/14/3137alloy steelfeedANFISRPMturning
collection DOAJ
language English
format Article
sources DOAJ
author Ishwer Shivakoti
Lewlyn L.R. Rodrigues
Robert Cep
Premendra Mani Pradhan
Ashis Sharma
Akash Kumar Bhoi
spellingShingle Ishwer Shivakoti
Lewlyn L.R. Rodrigues
Robert Cep
Premendra Mani Pradhan
Ashis Sharma
Akash Kumar Bhoi
Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
Materials
alloy steel
feed
ANFIS
RPM
turning
author_facet Ishwer Shivakoti
Lewlyn L.R. Rodrigues
Robert Cep
Premendra Mani Pradhan
Ashis Sharma
Akash Kumar Bhoi
author_sort Ishwer Shivakoti
title Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
title_short Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
title_full Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
title_fullStr Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
title_full_unstemmed Experimental Investigation and ANFIS-Based Modelling During Machining of EN31 Alloy Steel
title_sort experimental investigation and anfis-based modelling during machining of en31 alloy steel
publisher MDPI AG
series Materials
issn 1996-1944
publishDate 2020-07-01
description This research presents the parametric effect of machining control variables while turning EN31 alloy steel with a Chemical Vapor deposited (CVD) Ti(C,N) + Al<sub>2</sub>O<sub>3</sub> + TiN coated carbide tool insert. Three machining parameters with four levels considered in this research are feed, revolutions per minute (RPM), and depth of cut (a<sub>p</sub>). The influences of those three factors on material removal rate (MRR), surface roughness (Ra), and cutting force (Fc) were of specific interest in this research. The results showed that turning control variables has a substantial influence on the process responses. Furthermore, the paper demonstrates an adaptive neuro fuzzy inference system (ANFIS) model to predict the process response at various parametric combinations. It was observed that the ANFIS model used for prediction was accurate in predicting the process response at varying parametric combinations. The proposed model presents correlation coefficients of 0.99, 0.98, and 0.964 for MRR, Ra, and Fc, respectively.
topic alloy steel
feed
ANFIS
RPM
turning
url https://www.mdpi.com/1996-1944/13/14/3137
work_keys_str_mv AT ishwershivakoti experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
AT lewlynlrrodrigues experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
AT robertcep experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
AT premendramanipradhan experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
AT ashissharma experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
AT akashkumarbhoi experimentalinvestigationandanfisbasedmodellingduringmachiningofen31alloysteel
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