Investigations of Machining Characteristics in the Upgraded MQL-Assisted Turning of Pure Titanium Alloys Using Evolutionary Algorithms

Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its...

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Bibliographic Details
Published in:Materials Vol. 12; no. 6; p. 999
Main Authors: Singh, Gurraj, Pruncu, Catalin Iulian, Gupta, Munish Kumar, Mia, Mozammel, Khan, Aqib Mashood, Jamil, Muhammad, Pimenov, Danil Yurievich, Sen, Binayak, Sharma, Vishal S.
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 26.03.2019
MDPI
Subjects:
03 Chemical Sciences
09 Engineering
Aerodynamics
Compressed air
Cooling
Cooling effects
CUTTING FLUIDS
Environmental protection
evolutionary algorithm
Evolutionary algorithms
Genetic algorithms
Grain size
Inlet nozzles
Lubricants & lubrication
Lubrication
MACHINABILITY
Materials Science
Materials Science, Multidisciplinary
Mechanical engineering
MQL
MQL; RHVT; optimization; turning; titanium; evolutionary algorithm
Multidisciplinary
NANO-FLUID
optimization
Optimization algorithms
PARAMETER OPTIMIZATION
Particle swarm optimization
Process engineering
Process parameters
QUANTITY LUBRICATION
R&D
Research & development
RESPONSE-SURFACE
RHVT
Science & Technology
Surface properties
SURFACE-ROUGHNESS
Technology
TEMPERATURE
titanium
Titanium alloys
Titanium base alloys
TOOL WEAR
turning
Turning (machining)
Variance analysis
Vortex chambers
VORTEX-TUBE
Vortices
United Kingdom > UK
India
MQL
RHVT
optimization
titanium
turning
evolutionary algorithm
ISSN:1996-1944, 1996-1944
Online Access:Get full text
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Abstract Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque–Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.
AbstractList Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque–Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.
Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque⁻Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque⁻Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.
Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque⁻Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.
Author Muhammad Jamil
Vishal S. Sharma
Aqib Mashood Khan
Gurraj Singh
Munish Kumar Gupta
Mozammel Mia
Danil Yurievich Pimenov
Catalin Iulian Pruncu
Binayak Sen
AuthorAffiliation 1 School of Mechanical Engineering, Lovely Professional University, Phagwara 144411, India; singh_gurraj@yahoo.co.in
2 Mechanical Engineering, Imperial College London, Exhibition Rd., London SW7 2AZ, UK
7 Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, Chelyabinsk 454080, Russia; danil_u@rambler.ru
5 Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh; mozammelmiaipe@gmail.com
3 Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, UK
6 College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; dr.aqib@nuaa.edu.cn (A.M.K.); engr.jamil@nuaa.edu.cn (M.J.)
9 I & P Engg. Department, Dr. B.R. Ambedkar N.I.T, Jalandhar 144001, India; sharmavs@nitj.ac.in
8 Department of Production Engineering, National Institute of Technology, Agartala 799046, India; binayaksen3@gmail.com
4 University Center fo
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– name: 7 Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, Chelyabinsk 454080, Russia; danil_u@rambler.ru
– name: 8 Department of Production Engineering, National Institute of Technology, Agartala 799046, India; binayaksen3@gmail.com
– name: 9 I & P Engg. Department, Dr. B.R. Ambedkar N.I.T, Jalandhar 144001, India; sharmavs@nitj.ac.in
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– name: 2 Mechanical Engineering, Imperial College London, Exhibition Rd., London SW7 2AZ, UK
– name: 6 College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; dr.aqib@nuaa.edu.cn (A.M.K.); engr.jamil@nuaa.edu.cn (M.J.)
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  fullname: Pruncu, Catalin Iulian
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  orcidid: 0000-0002-8351-1871
  surname: Mia
  fullname: Mia, Mozammel
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  givenname: Aqib Mashood
  orcidid: 0000-0002-4446-4478
  surname: Khan
  fullname: Khan, Aqib Mashood
– sequence: 6
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  surname: Jamil
  fullname: Jamil, Muhammad
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  fullname: Sharma, Vishal S.
BackLink https://cir.nii.ac.jp/crid/1873116917809402624$$DView record in CiNii
https://www.ncbi.nlm.nih.gov/pubmed/30917617$$D View this record in MEDLINE/PubMed
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2019 by the authors. 2019
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Issue 6
Keywords MQL
RHVT
optimization
titanium
turning
evolutionary algorithm
Language English
License Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Snippet Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum...
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StartPage 999
SubjectTerms 03 Chemical Sciences
09 Engineering
Aerodynamics
Compressed air
Cooling
Cooling effects
CUTTING FLUIDS
Environmental protection
evolutionary algorithm
Evolutionary algorithms
Genetic algorithms
Grain size
Inlet nozzles
Lubricants & lubrication
Lubrication
MACHINABILITY
Materials Science
Materials Science, Multidisciplinary
Mechanical engineering
MQL
MQL; RHVT; optimization; turning; titanium; evolutionary algorithm
Multidisciplinary
NANO-FLUID
optimization
Optimization algorithms
PARAMETER OPTIMIZATION
Particle swarm optimization
Process engineering
Process parameters
QUANTITY LUBRICATION
R&D
Research & development
RESPONSE-SURFACE
RHVT
Science & Technology
Surface properties
SURFACE-ROUGHNESS
Technology
TEMPERATURE
titanium
Titanium alloys
Titanium base alloys
TOOL WEAR
turning
Turning (machining)
Variance analysis
Vortex chambers
VORTEX-TUBE
Vortices
Title Investigations of Machining Characteristics in the Upgraded MQL-Assisted Turning of Pure Titanium Alloys Using Evolutionary Algorithms
URI https://cir.nii.ac.jp/crid/1873116917809402624
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