Optimization of Machining Parameters for Improving Accuracy of Dimension and Shape of Bent Part in Rotary Draw Bending

2021 ◽  
Vol 904 ◽  
pp. 480-484
Author(s):  
Xia Zhu ◽  
Sheng Lin Mu ◽  
Hiroshi Kurosu ◽  
Hiromichi Toyota ◽  
Ken Uwagawa
Keyword(s):  
Optimal Solution ◽  
Transverse Plane ◽  
Machining Accuracy ◽  
Machining Parameters ◽  
Tube Bending ◽  
Rotary Draw Bending ◽  
Swarm Optimization ◽  
Improving Accuracy ◽  
Draw Bending ◽  
Normal Processing

This study dealt with the rotary draw bending method most used for tube bending and investigates how applied bending such as normal bending, using mandrels or pressing with booster have an effect on machining accuracy, focusing on dimensional defects due to springback and flat deformation to the transverse plane. The study used particle swarm optimization (PSO) algorithms to investigate the optimal machining conditions for improving the accuracy of dimension and shape of a bent part. The following findings were obtained: The springback during applied machining using a mandrel, or using a mandrel and booster together, is almost the same as during normal processing; The flattening near the center of the bend in applied processing using a mandrel, or a mandrel and booster together, decreases more than with normal processing at mandrel protrusion L ≥ 4 mm, and the maximum can be suppressed to approximately 0.15%; When the sum of the springback and the flattening is taken as the objective function and the minimum value is obtained, the optimal solution is around L = 7 mm.

scholarly journals INFLUENCE OF THE PRESSURE DIE GEOMETRY ON THE BENT TUBE OVALITY

2021 ◽  
Vol 2021 (2) ◽  
pp. 4474-4482
Author(s):  
JAN RIHACEK ◽  
◽  
MICHAELA CISAROVA ◽  
EVA PETERKOVA ◽  
KAMIL PODANY ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Tube Bending ◽  
Ansys Software ◽  
Rotary Draw Bending ◽  
Initial State ◽  
Die Geometry ◽  
Bending Process ◽  
Simulation Results ◽  
Draw Bending ◽  
Pressure Bar

The paper deal with analysis and optimization of the pressure bar geometry in the case of the tube bending. The bending process is realized on Wafios RBV 60 ST CNC bending machine using rotary draw bending system. The processed semi-finished product is a tube, which is made of 24MnB5 steel. Currently, after tube bending by an angle of 120°, an unacceptable ovality occurs on its body. Therefore, the article presents the optimization of the pressure bar geometry, which helps to prevent the occurrence of the mentioned defect. Due to the least possible intervention in the bending process, only the change in the pressure bar geometry is tested. For this reason, a numerical simulation in ANSYS software is performed. Before the actual optimization, an accuracy of the simulation is verified by comparing the real initial state with simulation results.

scholarly journals Particle Swarm Optimization Combined with Inertia-Free Velocity and Direction Search

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 597
Author(s):  
Kun Miao ◽  
Qian Feng ◽  
Wei Kuang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Small Region ◽  
Benchmark Problems ◽  
Swarm Optimization ◽  
Local Searches ◽  
Engineering Design Problems ◽  
Direction Search

The particle swarm optimization algorithm (PSO) is a widely used swarm-based natural inspired optimization algorithm. However, it suffers search stagnation from being trapped into a sub-optimal solution in an optimization problem. This paper proposes a novel hybrid algorithm (SDPSO) to improve its performance on local searches. The algorithm merges two strategies, the static exploitation (SE, a velocity updating strategy considering inertia-free velocity), and the direction search (DS) of Rosenbrock method, into the original PSO. With this hybrid, on the one hand, extensive exploration is still maintained by PSO; on the other hand, the SE is responsible for locating a small region, and then the DS further intensifies the search. The SDPSO algorithm was implemented and tested on unconstrained benchmark problems (CEC2014) and some constrained engineering design problems. The performance of SDPSO is compared with that of other optimization algorithms, and the results show that SDPSO has a competitive performance.

Investigation of Neutral Axis Shifting in Rotary Draw Bending Processes for Tubes

2014 ◽  
Vol 85 (7) ◽  
pp. 1209-1214 ◽  
Author(s):  
Bernd Engel ◽  
Hassan Raheem Hassan
Keyword(s):  
Neutral Axis ◽  
Rotary Draw Bending ◽  
Draw Bending

Characteristics of Rotary Draw-Bent Tubes for the Hydroforming

2011 ◽  
Vol 213 ◽  
pp. 320-324
Author(s):  
Byeong Don Joo ◽  
Jeong Hwan Jang ◽  
Hyun Jong Lee ◽  
Young Hoon Moon
Keyword(s):  
Cross Section ◽  
Structural Strength ◽  
Dimensional Accuracy ◽  
Thickness Variation ◽  
Important Process ◽  
Rotary Draw Bending ◽  
Higher Dimensional ◽  
Bending Process ◽  
Geometric Size ◽  
Draw Bending

Hydroformed parts have higher dimensional accuracy, structural strength, and dimensional repeatability. The pre-bending process is an important process for the successful hydroforming in the case where the perimeter of the blank is nearly the same as that of final product. At initial pre-bending stage, the variations of wall thickness and cross-section have effects on the accuracy of final products and quality. Because of a relatively excellent productive velocity, geometric size precision and reliance of product qualities, rotary draw bending is widely used. This study shows the bendability such as cross-section ovality, springback ratio and thickness variation in the various conditions of materials.

Numerical Research on High-Strength Rectangular Section Steel Tube in Rotary-Draw Bending

2014 ◽  
Vol 620 ◽  
pp. 417-423 ◽  
Author(s):  
Zhong Wen Xing ◽  
Zhi Wei Xu ◽  
Hong Liang Yang ◽  
Cheng Xi Lei
Keyword(s):  
High Strength ◽  
Element Model ◽  
Steel Tube ◽  
Rotary Draw Bending ◽  
Rectangular Section ◽  
Control Variate ◽  
Fillet Radius ◽  
Bending Process ◽  
Bending Radius ◽  
Draw Bending

A finite element model of high-strength rectangular section steel tube in rotary-draw bending is established to study the stress and strain in the bending process. Based on control variate method, this paper analyzes the influence laws of three geometric parameters on rotary-draw bending. The results show that bending radius is the most important factor, forming property increases significantly with the increase of bending radius, the trends of cracking and wrinkling are all decreased. The thickness of wall has influence on the strain of inwall, thinner tube may cause crack and wrinkle. Fillet radius has no effect on ektexine, the strain of inwall decreases slightly with the increase of fillet radius.

scholarly journals Service Composition in IoT using Genetic algorithm and Particle swarm optimization

2020 ◽  
Vol 10 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Neeti Kashyap ◽  
A. Charan Kumari ◽  
Rita Chhikara
Keyword(s):  
Genetic Algorithm ◽  
Quality Of Service ◽  
Particle Swarm Optimization ◽  
Service Composition ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Critical Issue ◽  
Swarm Optimization

AbstractWeb service compositions are commendable in structuring innovative applications for different Internet-based business solutions. The existing services can be reused by the other applications via the web. Due to the availability of services that can serve similar functionality, suitable Service Composition (SC) is required. There is a set of candidates for each service in SC from which a suitable candidate service is picked based on certain criteria. Quality of service (QoS) is one of the criteria to select the appropriate service. A standout amongst the most important functionality presented by services in the Internet of Things (IoT) based system is the dynamic composability. In this paper, two of the metaheuristic algorithms namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized to tackle QoS based service composition issues. QoS has turned into a critical issue in the management of web services because of the immense number of services that furnish similar functionality yet with various characteristics. Quality of service in service composition comprises of different non-functional factors, for example, service cost, execution time, availability, throughput, and reliability. Choosing appropriate SC for IoT based applications in order to optimize the QoS parameters with the fulfillment of user’s necessities has turned into a critical issue that is addressed in this paper. To obtain results via simulation, the PSO algorithm is used to solve the SC problem in IoT. This is further assessed and contrasted with GA. Experimental results demonstrate that GA can enhance the proficiency of solutions for SC problem in IoT. It can also help in identifying the optimal solution and also shows preferable outcomes over PSO.

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Robotica ◽  
2022 ◽  
pp. 1-16
Author(s):  
Peng Zhang ◽  
Junxia Zhang
Keyword(s):  
Optimization Algorithm ◽  
Robot Control ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Global Optimum ◽  
Identification Accuracy ◽  
Dynamic Parameters ◽  
Dynamics Modeling ◽  
Swarm Optimization ◽  
Exoskeleton Robot

Abstract Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual’s judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control.

OPTIMAL PREDICTION AND DESIGN OF SURFACE ROUGHNESS FOR CNC TURNING OF AL7075-T6 BY USING THE TAGUCHI HYBRID QPSO ALGORITHM

2016 ◽  
Vol 40 (5) ◽  
pp. 883-895 ◽  
Author(s):  
Wen-Jong Chen ◽  
Chuan-Kuei Huang ◽  
Qi-Zheng Yang ◽  
Yin-Liang Yang
Keyword(s):  
Surface Roughness ◽  
Particle Swarm Optimization ◽  
Predictive Models ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Cutting Parameters ◽  
Optimization Methods ◽  
Swarm Optimization ◽  
Cnc Turning ◽  
Multi Objective

This paper combines the Taguchi-based response surface methodology (RSM) with a multi-objective hybrid quantum-behaved particle swarm optimization (MOHQPSO) to predict the optimal surface roughness of Al7075-T6 workpiece through a CNC turning machining. First, the Taguchi orthogonal array L27 (36) was applied to determine the crucial cutting parameters: feed rate, tool relief angle, and cutting depth. Subsequently, the RSM was used to construct the predictive models of surface roughness (Ra, Rmax, and Rz). Finally, the MOHQPSO with mutation was used to determine the optimal roughness and cutting conditions. The results show that, compared with the non-optimization, Taguchi and classical multi-objective particle swarm optimization methods (MOPSO), the roughness Ra using MOHQPSO along the Pareto optimal solution are improved by 68.24, 59.31 and 33.80%, respectively. This reveals that the predictive models established can improve the machining quality in CNC turning of Al7075-T6.

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