The optimization of accuracy and efficiency for multistage precision grinding process with an improved particle swarm optimization algorithm
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Yiming Rong | Liping Wang | Xuekun Li | Sheng Jiang | Zhanying Chen | Zeming Zhao | Zongyu Zhu | Liping Wang | Xuekun Li | Y. Rong | Zhanying Chen | Sheng Jiang | Zongyu Zhu | Zeming Zhao
[1] Taihua Mu,et al. Optimization of processing technology using response surface methodology and physicochemical properties of roasted sweet potato. , 2019, Food chemistry.
[2] Gang Wang,et al. Hybrid particle swarm optimization for first-order reliability method , 2017 .
[3] Nilanjan Dey,et al. Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings , 2016, Neural Computing and Applications.
[4] V. Stojanovic,et al. Robust identification of pneumatic servo actuators in the real situations , 2011 .
[5] Vladimir Stojanovic,et al. A Nature Inspired Parameter Tuning Approach to Cascade Control for Hydraulically Driven Parallel Robot Platform , 2016, J. Optim. Theory Appl..
[6] Yao Li. Service-oriented Research on Multi-pass Milling Parameters Optimization for Green and High Efficiency , 2015 .
[7] D. Maiti,et al. Buckling load enhancement of damaged composite plates under hygrothermal environment using unified particle swarm optimization , 2017 .
[8] Gary G. Yen,et al. Rank-density-based multiobjective genetic algorithm and benchmark test function study , 2003, IEEE Trans. Evol. Comput..
[9] Satish Vadlamani,et al. Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem , 2014, Neural Computing and Applications.
[10] İlhan Asiltürk,et al. Determining the optimum process parameter for grinding operations using robust process , 2012 .
[11] P. V. Rao,et al. Selection of optimum conditions for maximum material removal rate with surface finish and damage as constraints in SiC grinding , 2003 .
[12] Li Li,et al. Selection of optimum parameters in multi-pass face milling for maximum energy efficiency and minimum production cost , 2017 .
[13] Xuekun Li,et al. The development of a hybrid firefly algorithm for multi-pass grinding process optimization , 2019, J. Intell. Manuf..
[14] Xiguang Chen,et al. Optimization of the preparation conditions of thermo-sensitive chitosan hydrogel in heterogeneous reaction using response surface methodology. , 2019, International journal of biological macromolecules.
[15] Tuğrul Özel,et al. Multi-objective process optimization for micro-end milling of Ti-6Al-4V titanium alloy , 2012 .
[16] Michael N. Vrahatis,et al. Parameter selection and adaptation in Unified Particle Swarm Optimization , 2007, Math. Comput. Model..
[17] J. M. Crichigno Filho,et al. Applying extended Oxley’s machining theory and particle swarm optimization to model machining forces , 2017 .
[18] Amit Prakash,et al. Surface Wave Based Ultrasonic Technique for Finding the Optimal Grinding Condition of High Speed Steel (HSS) Work Rolls , 2013 .
[19] Yanbin Zhang,et al. Study on the optimization of cutting parameters in turning thin-walled circular cylindrical shell based upon cutting stability , 2013 .
[20] Mahdi Hasanipanah,et al. Prediction of blast-produced ground vibration using particle swarm optimization , 2017, Engineering with Computers.
[21] André Abee,et al. Effect of coil set on shape defects in roll forming steel strip , 2017 .
[22] HosseiniSeyedmohsen,et al. A survey on the Imperialist Competitive Algorithm metaheuristic , 2014 .
[23] Romesh Nagarajah,et al. Particle Swarm Optimization approach to defect detection in armour ceramics , 2017, Ultrasonics.
[24] Ali R. Yildiz,et al. A comparative study of population-based optimization algorithms for turning operations , 2012, Inf. Sci..
[25] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[26] Kiran Solanki,et al. Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach , 2012 .
[27] Bin He,et al. Product environmental footprints assessment for product life cycle , 2019, Journal of Cleaner Production.
[28] Ali Rıza Yıldız,et al. Structural Damage Detection Using Modal Parameters and Particle Swarm Optimization , 2012 .
[29] S. Agarwal. Optimizing machining parameters to combine high productivity with high surface integrity in grinding silicon carbide ceramics , 2016 .
[30] S. G. Deshmukh,et al. A genetic algorithmic approach for optimization of surface roughness prediction model , 2002 .
[31] Gianni Campatelli,et al. Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel , 2014 .
[32] Bin He,et al. Product carbon footprint across sustainable supply chain , 2019 .
[33] Kusum Deep,et al. Parameter optimization of multi-pass turning using chaotic PSO , 2015, Int. J. Mach. Learn. Cybern..
[34] Bin He,et al. Underactuated robotics: A review , 2019, International Journal of Advanced Robotic Systems.
[35] V. Stojanovic,et al. Application of cuckoo search algorithm to constrained control problem of a parallel robot platform , 2016, The International Journal of Advanced Manufacturing Technology.
[36] James T. Lin,et al. A hybrid particle swarm optimization with local search for stochastic resource allocation problem , 2018, J. Intell. Manuf..
[37] Siba Sankar Mahapatra,et al. A particle swarm approach for multi-objective optimization of electrical discharge machining process , 2016, J. Intell. Manuf..
[38] Vladimir Stojanovic,et al. Joint state and parameter robust estimation of stochastic nonlinear systems , 2016 .
[39] Ali Rıza Yıldız,et al. Moth-flame optimization algorithm to determine optimal machining parameters in manufacturing processes , 2017 .
[40] Jian Li,et al. Multi-objective optimization for surface grinding process using a hybrid particle swarm optimization algorithm , 2014 .
[41] Liang Gao,et al. An effective cellular particle swarm optimization for parameters optimization of a multi-pass milling process , 2012, Appl. Soft Comput..
[42] Seyedmohsen Hosseini,et al. A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research , 2014, Appl. Soft Comput..
[43] Liang Gao,et al. Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm , 2016 .
[44] Tianyou Chai,et al. Two-stage Method for Solving Large-scale Hot Rolling Planning Problem in Steel Production , 2011 .
[45] Angelos P. Markopoulos,et al. Surface roughness prediction for the milling of Ti–6Al–4V ELI alloy with the use of statistical and soft computing techniques , 2016 .