Intelligent Sequence Optimization Method for Hole Making Operations in 2M Production Line

Author(s):  
Thanveer Ahammed ◽  
Jaber Abu Qudeiri ◽  
Abdel-Hamid Mourad ◽  
Aiman Ziout ◽  
Faris Safieh
Author(s):  
Chuanwei Zhang ◽  
Feiyan Han ◽  
Wu Zhang

Defining the cutting sequence of each cutter scientifically in the process of removing the allowance has an important influence on the machining efficiency for complex parts, which have multiple machining features. In order to satisfy the needs of high efficiency for rough machining, after determining the tool path of the machining region, a cutting sequence optimization method based on the tabu search algorithm is presented to define the cutting order in rough machining of complex parts. First, a cutting sequence optimization mathematical model is established, which relates to the shortest total length of the tool path. Second, through the problem analysis, the cutting sequence optimization model is converted into an open and constrained traveling salesman problem. And then, the optimization model is solved by dealing with an open and constrained traveling salesman problem using the tabu search algorithm. Finally, the optimal cutting sequence of machining a casing part is calculated, and a simulation and experiment are carried out. The result shows that the optimization approach presented in this article can optimize the cutting sequence and cutter position of advance and retract. Compared with the non-optimized cutting sequence method, the total length of tool path is reduced by 16.7%, the cutter lifting times are reduced to 26, and the efficiency is increased by 21.62%.


2020 ◽  
Vol 33 (10) ◽  
pp. 2770-2781
Author(s):  
Yinfei YANG ◽  
Longxin FAN ◽  
Liang LI ◽  
Guolong ZHAO ◽  
Ning HAN ◽  
...  

2013 ◽  
Vol 631-632 ◽  
pp. 754-758
Author(s):  
Zhong Lei Sun ◽  
Mei Ying Zhao ◽  
Li Long Luo

A dual-zone reinforcement ply stacking sequence optimization method used for comosite laminate with large cutout is present. The optimization method utilized a new Genetic Algorithm. The new Genetic Algorithm introduced a new strategy which can improve the efficiency of the traditional Genetic Algorithm and overcome the shortages of the worse convergency and prematurity of the Simple Genetic Algorithm. In the new Genetic Algorithm, the selection probability and the mutation probability are self-adaptive. Compared with the Simple Genetic Algorithm, the new Genetic Algorithm method shows good consistency, fast convergency and practical feasibility. By using the new Genetic Algorithm, the reinforcement ply stacking sequence optimization method got reasonable symmetric and balance stacking sequence which could meet the design requirements.


2014 ◽  
Vol 27 (2) ◽  
pp. 417-429 ◽  
Author(s):  
W. C. E. Lim ◽  
G. Kanagaraj ◽  
S. G. Ponnambalam

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Bingbing San ◽  
Zhi Xiao ◽  
Ye Qiu

A simultaneous shape and stacking sequence optimization algorithm is presented for laminated composite free-form shells, by which the coupled effect of shape and stacking sequence can be considered. The optimization objective is determined as maximizing fundamental natural frequency to obtain largest stiffness of shells. Nonuniform rational B-spline (NURBS) is employed to represent free-form geometrical shapes. The coordinates of NURBS control points and fiber orientations are set up as continuous and discrete optimization variables, respectively, and optimized simultaneously. To improve the efficiency of the mixed continuous-discrete optimization, multi-island genetic algorithm (MIGA) is employed to search for the global result. Through several numerical examples, the performance of the proposed approach is demonstrated in comparison with the two-phase optimization method; the effect of boundary conditions and the setup of control points on optimal results are investigated, respectively.


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