Most recent issue published online in the International Journal of Materials and Product Technology.
International Journal of Materials and Product Technology
http://www.inderscience.com/browse/index.php?journalID=20&year=2024&vol=68&issue=1/2
Inderscience Publishers Ltd
en-uk
support@inderscience.com
International Journal of Materials and Product Technology
0268-1900
1741-5209
© 2024 Inderscience Enterprises Ltd.
© 2024 Inderscience Publishers Ltd
editor@inderscience.com
International Journal of Materials and Product Technology
https://www.inderscience.com/images/files/coverImgs/ijmpt_scoverijmpt.jpg
http://www.inderscience.com/browse/index.php?journalID=20&year=2024&vol=68&issue=1/2
-
Calculation method for ultimate bearing capacity of reinforced concrete beams based on unified strength theory
http://www.inderscience.com/link.php?id=136843
In order to improve the accuracy and reliability of the calculation results of the ultimate bearing capacity of reinforced concrete beams, this paper proposes a calculation method for the ultimate bearing capacity of reinforced concrete beams based on the unified strength theory. Firstly, we analyse the mechanical properties of reinforced concrete materials and conduct principal stress analysis of reinforced concrete beams. Then, the plastic damage model (CDP model) is used to simulate the mechanical properties of concrete components under reciprocating loads. Based on the unified strength theory assumption, concrete and steel bars are considered as equivalent materials, and the shear deformation method is used to calculate the ultimate bearing capacity. The results show that the accuracy of the proposed method can reach up to 99.2%, indicating that the proposed method can effectively improve the accuracy of calculating the ultimate bearing capacity of reinforced concrete beams.
Calculation method for ultimate bearing capacity of reinforced concrete beams based on unified strength theory
Pu Miao; Yanmin Chen; Zhanzhan Zheng
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 1 - 17
In order to improve the accuracy and reliability of the calculation results of the ultimate bearing capacity of reinforced concrete beams, this paper proposes a calculation method for the ultimate bearing capacity of reinforced concrete beams based on the unified strength theory. Firstly, we analyse the mechanical properties of reinforced concrete materials and conduct principal stress analysis of reinforced concrete beams. Then, the plastic damage model (CDP model) is used to simulate the mechanical properties of concrete components under reciprocating loads. Based on the unified strength theory assumption, concrete and steel bars are considered as equivalent materials, and the shear deformation method is used to calculate the ultimate bearing capacity. The results show that the accuracy of the proposed method can reach up to 99.2%, indicating that the proposed method can effectively improve the accuracy of calculating the ultimate bearing capacity of reinforced concrete beams.]]>
10.1504/IJMPT.2024.136843
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 1 - 17
Pu Miao
Yanmin Chen
Zhanzhan Zheng
School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu, 476000, China ' School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu, 476000, China ' School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu, 476000, China
force model
reinforced concrete beams
shear deformation method
stress distribution
yield strength
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
1
17
2024-02-22T23:20:50-05:00
-
Study on detection of dent defects of polariser based on deep convolutional generative adversarial network
http://www.inderscience.com/link.php?id=136845
The existing techniques of polariser detection only concern whether the polarisers have defects or not and do not classify them as specialised. In addition, lightweight CNN architectures proposed for defect classification of polarisers are based on limited samples. In order to attack the aforementioned issues, a novel grating imaging mechanism based on an adsorption transport platform is designed for a certain defect, dent. Multi-scale negative samples with dent defects and positive samples with other defects or not are expanded by a deep convolutional generative adversarial network (DCGAN). O sets, <i>64_10000</i> sets and <i>128_10000</i> sets (referred to as the original data, 64*64 generated data and 128*128 generated data) are trained on multiple convolutional neural networks (AlexNet, VGGNet, GoogLeNet, ResNet, SqueezeNet, MoblieNet, ShuffleNet) respectively, the obtained models are then validated on two new samples. Empirically show that ResNet obtained by <i>64G+128G</i> perform better than others, classification accuracy rate of the new model is up to 94.94%.
Study on detection of dent defects of polariser based on deep convolutional generative adversarial network
Pengfei Shi
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 18 - 28
The existing techniques of polariser detection only concern whether the polarisers have defects or not and do not classify them as specialised. In addition, lightweight CNN architectures proposed for defect classification of polarisers are based on limited samples. In order to attack the aforementioned issues, a novel grating imaging mechanism based on an adsorption transport platform is designed for a certain defect, dent. Multi-scale negative samples with dent defects and positive samples with other defects or not are expanded by a deep convolutional generative adversarial network (DCGAN). O sets, <i>64_10000</i> sets and <i>128_10000</i> sets (referred to as the original data, 64*64 generated data and 128*128 generated data) are trained on multiple convolutional neural networks (AlexNet, VGGNet, GoogLeNet, ResNet, SqueezeNet, MoblieNet, ShuffleNet) respectively, the obtained models are then validated on two new samples. Empirically show that ResNet obtained by <i>64G+128G</i> perform better than others, classification accuracy rate of the new model is up to 94.94%.]]>
10.1504/IJMPT.2024.136845
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 18 - 28
Pu Miao
Yanmin Chen
Zhanzhan Zheng
CETC Fenghua Information-Equipment Co., Ltd., Taiyuan, 030024, Shanxi, China
deep learning
polariser defect detection
convolutional neural network
CNN
generative adversarial net
GAN
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
18
28
2024-02-22T23:20:50-05:00
-
Image recognition method of surface defects of prefabricated concrete members in prefabricated building
http://www.inderscience.com/link.php?id=136849
In view of the cracks, holes and other defects on the surface of prefabricated concrete components in prefabricated building, an Image recognition method of surface defects of prefabricated concrete members in prefabricated building is proposed. This method first performs denoising and enhancement processing on the obtained component defect images to improve the clarity of the images. Based on this, the image is segmented, and the defect features of the component surface defect image are extracted based on the segmentation results. Finally, support vector machines are used to classify the extracted features, achieving accurate recognition of surface defects in prefabricated concrete components. The experimental results show that the recognition effect and accuracy of using this method for component defect image recognition are good.
Image recognition method of surface defects of prefabricated concrete members in prefabricated building
Zhiyuan Li
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 29 - 49
In view of the cracks, holes and other defects on the surface of prefabricated concrete components in prefabricated building, an Image recognition method of surface defects of prefabricated concrete members in prefabricated building is proposed. This method first performs denoising and enhancement processing on the obtained component defect images to improve the clarity of the images. Based on this, the image is segmented, and the defect features of the component surface defect image are extracted based on the segmentation results. Finally, support vector machines are used to classify the extracted features, achieving accurate recognition of surface defects in prefabricated concrete components. The experimental results show that the recognition effect and accuracy of using this method for component defect image recognition are good.]]>
10.1504/IJMPT.2024.136849
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 29 - 49
Pu Miao
Yanmin Chen
Zhanzhan Zheng
School of Construction Engineering, Chongqing Water Resources and Electric Engineering College, Yongchuan, Chongqing, 402160, China
prefabricated building
prefabricated concrete members
defect
images recognition
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
29
49
2024-02-22T23:20:50-05:00
-
Stiffness analysis of automobile aluminium alloy frame based on finite element model
http://www.inderscience.com/link.php?id=136846
Existing frame stiffness analysis methods lack accuracy. Therefore, a finite element model-based stiffness analysis method for automobile aluminium alloy frames is proposed. The finite element model considers only the main structural components and simplifies their structures to improve calculation efficiency while meeting accuracy requirements. Various parts and components are modelled and assembled into the complete frame model, including the suspension system in the analysis. The model grid is divided, and additional mass and assembly mass are simplified as concentrated loads applied to supporting points, while the frame's own mass is simplified as uniformly distributed loads applied to nodes and elements. Bending stiffness and torsional stiffness are analysed to determine the stiffness characteristics of the aluminium alloy frame. Test results demonstrate that this design method enables accurate bending and torsional stiffness analysis of the aluminium alloy frame, with minimal errors, as low as 2e+0.01 Nm<SUP align="right">2</SUP> and 22 N·m/°.
Stiffness analysis of automobile aluminium alloy frame based on finite element model
Bing Chen; Junfeng Wu; Lei Wang
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 50 - 70
Existing frame stiffness analysis methods lack accuracy. Therefore, a finite element model-based stiffness analysis method for automobile aluminium alloy frames is proposed. The finite element model considers only the main structural components and simplifies their structures to improve calculation efficiency while meeting accuracy requirements. Various parts and components are modelled and assembled into the complete frame model, including the suspension system in the analysis. The model grid is divided, and additional mass and assembly mass are simplified as concentrated loads applied to supporting points, while the frame's own mass is simplified as uniformly distributed loads applied to nodes and elements. Bending stiffness and torsional stiffness are analysed to determine the stiffness characteristics of the aluminium alloy frame. Test results demonstrate that this design method enables accurate bending and torsional stiffness analysis of the aluminium alloy frame, with minimal errors, as low as 2e+0.01 Nm<SUP align="right">2</SUP> and 22 N·m/°.]]>
10.1504/IJMPT.2024.136846
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 50 - 70
Bing Chen
Junfeng Wu
Lei Wang
Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China ' Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China ' Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China
finite element model
automobile aluminium alloy frame
stiffness analysis
bending stiffness
torsional stiffness
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
50
70
2024-02-22T23:20:50-05:00
-
Structural optimisation method of six degrees of freedom manipulator based on finite element analysis
http://www.inderscience.com/link.php?id=136844
In order to improve the optimisation effect of the robotic arm structure from multiple aspects, this paper designs a six degree of freedom robotic arm structure optimisation method based on finite element analysis. Firstly, the relative motion relationship between the rotating joint and the connecting rod was established based on the D-H theory. Then, we divide the mesh elements of the robotic arm structure in ANSYS software and analyse the parameter optimisation redundancy of the robotic arm. Finally, an optimisation equation set was established, and feasible structural optimisation parameters were obtained through solving and finite element verification. The experimental results show that under different load conditions, the maximum load of the robotic arm is increased to 14 kg, the mass of the robotic arm is reduced by about 11%, and the maximum stress is reduced to 13.54 MPa. At the same time, the reachable distance of the robotic arm in three-dimensional space is significantly increased.
Structural optimisation method of six degrees of freedom manipulator based on finite element analysis
Shudong He
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 71 - 85
In order to improve the optimisation effect of the robotic arm structure from multiple aspects, this paper designs a six degree of freedom robotic arm structure optimisation method based on finite element analysis. Firstly, the relative motion relationship between the rotating joint and the connecting rod was established based on the D-H theory. Then, we divide the mesh elements of the robotic arm structure in ANSYS software and analyse the parameter optimisation redundancy of the robotic arm. Finally, an optimisation equation set was established, and feasible structural optimisation parameters were obtained through solving and finite element verification. The experimental results show that under different load conditions, the maximum load of the robotic arm is increased to 14 kg, the mass of the robotic arm is reduced by about 11%, and the maximum stress is reduced to 13.54 MPa. At the same time, the reachable distance of the robotic arm in three-dimensional space is significantly increased.]]>
10.1504/IJMPT.2024.136844
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 71 - 85
Bing Chen
Junfeng Wu
Lei Wang
Intelligent Manufacturing and Mechanical Engineering, Hunan Institute of Technology, Hengyang, 421002, China
six degrees of freedom mechanical arm
mechanical arm structure
D-H theory
kinematics model
ANSYS software
optimisation margin
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
71
85
2024-02-22T23:20:50-05:00
-
Fatigue life estimation of metal materials based on finite element analysis
http://www.inderscience.com/link.php?id=136847
The fatigue life of metal materials determines the application performance of metal materials. A fatigue life estimation method of metal materials based on finite element analysis is proposed. The finite element model of metal materials is constructed through the steps of material property setting, mesh generation, etc. The influence mechanism of stress concentration degree, metal material size, and other factors is analysed; the fatigue damage evolution process of metal materials is simulated using a finite element model; the cyclic stress-strain characteristics of metal materials are extracted; the current fatigue damage accumulation state of metal materials is identified; and the estimation results of fatigue life of metal materials are obtained from two aspects of crack formation life and crack growth life. The experimental results show that the estimation error of this method is reduced by about 9.17 h, and the running speed is significantly improved.
Fatigue life estimation of metal materials based on finite element analysis
Junfeng Wu; Lei Wang; Bing Chen
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 86 - 106
The fatigue life of metal materials determines the application performance of metal materials. A fatigue life estimation method of metal materials based on finite element analysis is proposed. The finite element model of metal materials is constructed through the steps of material property setting, mesh generation, etc. The influence mechanism of stress concentration degree, metal material size, and other factors is analysed; the fatigue damage evolution process of metal materials is simulated using a finite element model; the cyclic stress-strain characteristics of metal materials are extracted; the current fatigue damage accumulation state of metal materials is identified; and the estimation results of fatigue life of metal materials are obtained from two aspects of crack formation life and crack growth life. The experimental results show that the estimation error of this method is reduced by about 9.17 h, and the running speed is significantly improved.]]>
10.1504/IJMPT.2024.136847
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 86 - 106
Junfeng Wu
Lei Wang
Bing Chen
Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China ' Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China ' Faculty of Engineering, Huanghe Science and Technology University, Zhengzhou, 450063, China; Henan Engineering Research Center of Acoustic Meta-Structure, Huanghe Science and Technology University, Zhengzhou, 450063, China
finite element analysis
metal materials
fatigue life estimation
cyclic stress-strain characteristics
crack formation life
crack growth life
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
86
106
2024-02-22T23:20:50-05:00
-
Effect of process parameters on impact strength and hardness of FDM printed ABS parts
http://www.inderscience.com/link.php?id=136836
Fused deposition modelling, an additive manufacturing (AM) process, helps in manufacturing complex components that are influenced by the various process parameters. The main objective is to experimentally evaluate the Shore D hardness and Izod impact of 3D-printed test specimens. Using a 3D printer, the test specimens are manufactured. The test specimens were manufactured taking into account various printing factors such as printing orientation, printing pattern, and infill density. The specimens were produced with three printing orientations (edge, vertical, and flat), four infill patterns (grid, rectilinear, honeycomb, and cubic), and an infill density range of 20% to 100%. For 60% infill density, cubic infill structure, and edge printing orientation, the highest impact strength is obtained (2,024 J/m) and a Shore D hardness of 45.7, and for 40% infill density, honeycomb infill structure, and edge printing orientation, the lowest impact strength is obtained (203 J/m), with a hardness of 42.8 on the Shore D scale. The study shows that the Izod impact strength and Shore D hardness of FDM-printed ABS items are affected by process parameters.
Effect of process parameters on impact strength and hardness of FDM printed ABS parts
Ajit B. Kolekar; Shrikant M. Bhosale; Mahesh S. Salunkhe; Nikhil P. Raut
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 107 - 121
Fused deposition modelling, an additive manufacturing (AM) process, helps in manufacturing complex components that are influenced by the various process parameters. The main objective is to experimentally evaluate the Shore D hardness and Izod impact of 3D-printed test specimens. Using a 3D printer, the test specimens are manufactured. The test specimens were manufactured taking into account various printing factors such as printing orientation, printing pattern, and infill density. The specimens were produced with three printing orientations (edge, vertical, and flat), four infill patterns (grid, rectilinear, honeycomb, and cubic), and an infill density range of 20% to 100%. For 60% infill density, cubic infill structure, and edge printing orientation, the highest impact strength is obtained (2,024 J/m) and a Shore D hardness of 45.7, and for 40% infill density, honeycomb infill structure, and edge printing orientation, the lowest impact strength is obtained (203 J/m), with a hardness of 42.8 on the Shore D scale. The study shows that the Izod impact strength and Shore D hardness of FDM-printed ABS items are affected by process parameters.]]>
10.1504/IJMPT.2024.136836
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 107 - 121
Ajit B. Kolekar
Shrikant M. Bhosale
Mahesh S. Salunkhe
Nikhil P. Raut
Department of Technology, Shivaji University, Kolhapur, Maharashtra, India ' Department of Technology, Shivaji University, Kolhapur, Maharashtra, India ' Department of Technology, Shivaji University, Kolhapur, Maharashtra, India ' Department of Technology, Shivaji University, Kolhapur, Maharashtra, India
Shore D hardness
additive manufacturing
Izod impact strength
process parameters
fused deposition modelling
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
107
121
2024-02-22T23:20:50-05:00
-
Effectiveness of green manufacturing in resolving environmental issues: a review
http://www.inderscience.com/link.php?id=136813
Green manufacturing (GM) has been garnering the attention of academia since the 1990s, with the evolution of many related concepts, as one of the most essential topics for human beings' sustainable development. After nearly three decades of growth, a general map of existing research is now required to reflect the major concepts and concerns at hand. A bibliometric analysis is used to do this. The main contribution of this research is to concentrate on the use and impact of lean and green manufacturing approaches. The manufacturing industry's frequent issues and misunderstandings are investigated. This study examines the parallels and benefits of both lean and green techniques. It enables industries to have a better grasp of the tools' use and challenges before moving on with the lean and green approach's actual deployment. This report also addresses potential research gaps related to the industry's need for an effective green implementation approach.
Effectiveness of green manufacturing in resolving environmental issues: a review
Jasvinder Singh; Chandan Deep Singh; Dharmpal Deepak
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 122 - 157
Green manufacturing (GM) has been garnering the attention of academia since the 1990s, with the evolution of many related concepts, as one of the most essential topics for human beings' sustainable development. After nearly three decades of growth, a general map of existing research is now required to reflect the major concepts and concerns at hand. A bibliometric analysis is used to do this. The main contribution of this research is to concentrate on the use and impact of lean and green manufacturing approaches. The manufacturing industry's frequent issues and misunderstandings are investigated. This study examines the parallels and benefits of both lean and green techniques. It enables industries to have a better grasp of the tools' use and challenges before moving on with the lean and green approach's actual deployment. This report also addresses potential research gaps related to the industry's need for an effective green implementation approach.]]>
10.1504/IJMPT.2024.136813
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 122 - 157
Jasvinder Singh
Chandan Deep Singh
Dharmpal Deepak
School of Mechanical Engineering, Lovely Professional University, Phagwara, Punjab, 144411, India ' Department of Mechanical Engineering, Punjabi University Patiala, Punjab, 144402, India ' Department of Mechanical Engineering, Punjabi University Patiala, Punjab, 144402, India
green manufacturing
GM
sustainable manufacturing
lean and green
sustainability
manufacturing industry
green implementation
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
122
157
2024-02-22T23:20:50-05:00
-
Analysis of factors affecting core functional competencies in manufacturing industries using fuzzy AHP
http://www.inderscience.com/link.php?id=136818
For firms to be more competitive in the market, core functional abilities are crucial. They give a business the tools it needs to outperform rivals in terms of performance speed, adaptability, and dependability. Many tools and approaches, such as instruments for quantitative and qualitative analysis, are utilised to analyse these elements. This paper deals with the analysis of attributes using Fuzzy AHP technique. During the analysis different factors have been identified and categorised on the priority basis using the Fuzzy AHP which can help the organisation through better insight of core functional competencies.
Analysis of factors affecting core functional competencies in manufacturing industries using fuzzy AHP
Rajdeep Singh
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 158 - 168
For firms to be more competitive in the market, core functional abilities are crucial. They give a business the tools it needs to outperform rivals in terms of performance speed, adaptability, and dependability. Many tools and approaches, such as instruments for quantitative and qualitative analysis, are utilised to analyse these elements. This paper deals with the analysis of attributes using Fuzzy AHP technique. During the analysis different factors have been identified and categorised on the priority basis using the Fuzzy AHP which can help the organisation through better insight of core functional competencies.]]>
10.1504/IJMPT.2024.136818
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 158 - 168
Jasvinder Singh
Chandan Deep Singh
Dharmpal Deepak
Department of Mechanical Engineering, Punjabi University, Patiala, 147002, India
fuzzy AHP
competitiveness
core functional competencies
MCDM
multi-criteria decision-making
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
158
168
2024-02-22T23:20:50-05:00
-
Improving CNTs properties using computational intelligence algorithms
http://www.inderscience.com/link.php?id=136839
Carbon nanotubes (CNTs) have emerged in various applications due to their outstanding characteristics. The most common technique for producing CNTs with high yield and quality is known as chemical vapour deposition (CVD). However, manufacturers rely on conventional experimental studies to produce CNTs, which raise issues such as time, cost, and dealing with toxic materials. Alternatively, modelling and optimisation using metaheuristic algorithms are suggested to address these issues. This paper uses response surface methodology (RSM) for modelling work, while four metaheuristic algorithms are employed for optimisation. The regression and mathematical models, correlations, and significant CNTs process parameters are identified, analysed, and validated using RSM. The optimisation process and result are validated using different performance measure metrics and supported by other researchers. The CNTs yield and quality values improvement percentages in this paper are up to 36.45% compared to the referred original work.
Improving CNTs properties using computational intelligence algorithms
Muath Jarrah; Zakaria N.M. Alqattan; Abdul Syukor Mohamad Jaya; Sharif Naser Makhadmeh; Ahmed Ismail Abu-Khadrah; Ibrahim Aljarrah; Osama Ahmad Alomari
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 169 - 198
Carbon nanotubes (CNTs) have emerged in various applications due to their outstanding characteristics. The most common technique for producing CNTs with high yield and quality is known as chemical vapour deposition (CVD). However, manufacturers rely on conventional experimental studies to produce CNTs, which raise issues such as time, cost, and dealing with toxic materials. Alternatively, modelling and optimisation using metaheuristic algorithms are suggested to address these issues. This paper uses response surface methodology (RSM) for modelling work, while four metaheuristic algorithms are employed for optimisation. The regression and mathematical models, correlations, and significant CNTs process parameters are identified, analysed, and validated using RSM. The optimisation process and result are validated using different performance measure metrics and supported by other researchers. The CNTs yield and quality values improvement percentages in this paper are up to 36.45% compared to the referred original work.]]>
10.1504/IJMPT.2024.136839
International Journal of Materials and Product Technology, Vol. 68, No. 1/2 (2024) pp. 169 - 198
Muath Jarrah
Zakaria N.M. Alqattan
Abdul Syukor Mohamad Jaya
Sharif Naser Makhadmeh
Ahmed Ismail Abu-Khadrah
Ibrahim Aljarrah
Osama Ahmad Alomari
College of Computing and Informatics, University of Sharjah, Sharjah, 27272, UAE; Department of Computer Science, University Malaysia of Computer Science and Engineering (UNIMY), Cyberjaya, Selangor, Malaysia ' Department of Cyber Security and Cloud Computing Techniques Engineering, Northern Technical University, Mosul, Iraq; Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia ' Department of Intelligent Computing and Analytics, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100, Melaka, Malaysia ' Department of Data Science and Artificial Intelligence, University of Petra, Amman, 11196, Jordan ' College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia ' Department of Computer Information Systems (CIS), Jordan University of Science and Technology, Irbid, Jordan ' Department of Computer Science and Information Technology, College of Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates
carbon nanotubes
CNTs
chemical vapour deposition
CVD
optimisation algorithms
response surface methodology
RSM
2024-02-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
68
1/2
169
198
2024-02-22T23:20:50-05:00