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  1. 1
    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm

    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm by Mimi Muzlina, Mukri

    Published 2024
    “…To minimize the temperature rise during machining, the cutting speed, feed rate, depth of cut, and nose radius are optimized in this study using a single-objective genetic algorithm. …”
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  2. 2
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Manufacturing cost for machining components is affected by the available machining parameters which include the selection of appropriate cutting material, cutting tools, and machining data of cutting speed, feed, and depth of cut. …”
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  3. 3
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The cutting process has focus on roughing stages. There are enough handbooks to provide recommended cutting parameters and not consider the economic aspects of machining. …”
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  4. 4
    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm

    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm by Al Hazza, Muataz, Adesta, Erry Yulian Triblas, Superianto, M. Y., Riza, Muhammad

    Published 2012
    “…Machining of hard materials at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality. …”
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  5. 5
    Prediction of Optimum Cutting Conditions in Dry Turning Operations of S45C Mild Steel using AIS and PSO Intelligent Algorithm

    Prediction of Optimum Cutting Conditions in Dry Turning Operations of S45C Mild Steel using AIS and PSO Intelligent Algorithm by Minhat, Mohamad, Abd Rahman, Md Nizam, Abbas, Adnan Jameel

    Published 2014
    “…The suggested system is based on Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) intelligent algorithms. S45C Mild steel bars are machined at different cutting conditions (cutting speeds, feed rates and depths of cut) without the use of cutting fluid. …”
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  6. 6
    Optimization of Machining Parameters in Turning for Different Hardness using Multi-Objective Genetic Algorithm

    Optimization of Machining Parameters in Turning for Different Hardness using Multi-Objective Genetic Algorithm by Mimi Muzlina, Mukri, Nor Atiqah, Zolpakar, Pathak, Sunil

    Published 2023
    “…Cutting depth, cutting speed, and feed rate are the machining variables that are used in the process of optimization. …”
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  7. 7
    Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm

    Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm by Mimi Muzlina, Mukri, Nor Atiqah, Zolpakar

    Published 2023
    “…The parameters involve during this optimization are cutting speed, feed rate, depth of cut and nose radius by using genetic algorithm optimization. …”
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  8. 8
    Predictive modelling of machining parameters of S45C mild steel

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…A mild steel material type JIS S45C and a tungsten carbide insert type SPG-422 Grade E30 are used as workpiece and cutting tool materials via dry machining respectively. …”
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  9. 9
    Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method

    Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method by Al Hazza, Muataz Hazza Faizi, Mohmad Bakhari, Nur Amirah Najwa

    Published 2016
    “…The aim of this paper is to determine experimentally the optimum cutting levels that minimize the tooling cost in machining AISI 304 as a work piece machined by a coated carbide tool using one of the non-conventional methods: Genetic Algorithm (GA). …”
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  10. 10
    Energy cost optimization in high speed hard turning using simulated annealing algorithm

    Energy cost optimization in high speed hard turning using simulated annealing algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Hassan, Muhammad Hasibul, Shaffiar, Norhashimah

    Published 2015
    “…Then, the Simulated Annealing Algorithm (SAA) has been used to optimize the cutting parameters. …”
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  11. 11
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…The parameter such as feed per tooth, cutting speed,and depth of cut are considered the important variables to minimize the machining time in milling process since it has produced a significant consequence on the machining process. …”
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  12. 12
    Optimization of machining parameters in turning for different hardness using multi-objective genetic algorithm / Mimi Muzlina Mukri, Nor Atiqah Zolpaka and Sunil Pathak

    Optimization of machining parameters in turning for different hardness using multi-objective genetic algorithm / Mimi Muzlina Mukri, Nor Atiqah Zolpaka and Sunil Pathak by Mukri, Mimi Muzlina, Zolpaka, Nor Atiqah Zolpaka, Pathak, Sunil

    Published 2023
    “…Cutting depth, cutting speed, and feed rate are the machining variables that are used in the process of optimization. …”
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  13. 13
    Machining optimization using Firefly Algorithm / Farhan Md Jasni

    Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

    Published 2020
    “…When any of these targets is not achieved, creating big problem to company and a total loss. The metaheuristic algorithm which being called as Firefly Algorithm (FA) is often used to solve various optimization problem in our daily life. …”
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  14. 14
    Power Consumption Optimization in CNC Turning Process Using Multi Objective Genetic Algorithm

    Power Consumption Optimization in CNC Turning Process Using Multi Objective Genetic Algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Riza, Muhammad, Suprianto, Mohamad Yuhan

    Published 2012
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  15. 15
    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network

    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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  16. 16
    Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey

    Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey by Abbas, Adnan Jameel, Minhat, Mohamad, Abd Rahman, Md Nizam

    Published 2012
    “…In addition, there is a gap of several machining operation parameters especially for cutting temperature optimization in turning operation using PSO and AIS.…”
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  17. 17
    Multi objective optimisation for high speed end milling using simulated annealing algorithm

    Multi objective optimisation for high speed end milling using simulated annealing algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Shaffiar, Norhashimah, Seder, Amin M. F., Riza, Muhammad

    Published 2015
    “…Machining at high cutting speeds produces higher temperatures in the cutting zone. …”
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  18. 18
    Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation

    Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation by Sivarao, Subramonian

    Published 2010
    “…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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  19. 19
    Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm

    Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm by Alam, Md. Shah, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah, Konneh, Mohamed

    Published 2010
    “…Machining was performed on a five-axis NC milling machine with a high speed attachment, using spindle speed, feed rate, and depth of cut as machining variables. …”
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  20. 20
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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