molding system
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2021 ◽  
Author(s):  
Jianhao Song ◽  
Feng Gao ◽  
Qiu-an Huang ◽  
Yuezhi Liu ◽  
Longjie Zhang ◽  
...  

Author(s):  
Daniel Enrique Reyes-Castrejon ◽  
Angélica Elizabeth Bonilla-Blancas ◽  
Eduardo Figueroa-Estrada ◽  
Martín Salazar-Pereyra

The manufacture of plastic products in the current markets demands the use of technologies that allow the molding of components with highly complex geometries and every time the time to manufacture is reduced. The presence of subsystems for the molding and release of negative structures increases the complexity of the mould, as well as the time required for the manufacture and adjust of the mould, since it is traditionally used mechanisms with angular pins. In this work the design of an injection mould is made for a component with negatives, which uses a system with actuator for the secondary molding and release of the negative structure according to the mould partition line. The mold is also design for the same component with the use of a secondary system of moulding totally mechanical and of conventional use. The analysis of the design and operation between a secondary mechanical molding system and a system with actuator for molding and releasing negative structures in plastic injection molds, alternative for reducing costs and times of Manufacturing.


2019 ◽  
Author(s):  
Ken Fujisaki ◽  
Hirotaka Goto ◽  
Tatsuya Tanaka ◽  
Masatoshi Nakajima ◽  
Takao Maenaka ◽  
...  

2017 ◽  
Vol 12 (9) ◽  
pp. 4389-4397
Author(s):  
S. J. Suji Prasad

The plastic parts having complex three dimensional structures are produced by Plastic injection molding system. Thequality of the product is determined by controlling the temperature of the mold cavity. The mold cavity temperature controlwith the conventional ON/OFF, PI, and PID controllers have several disadvantages. This paper proposes the method toreduce settling time and undershoot in cavity temperature control with selected evolutionary algorithms. The controllerparameters are optimized with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Algorithm for PID and I-PDcontrollers by considering Mean Square Error (MSE) as fitness function. Compared to conventional methods theparameter optimization using soft computing methods such as GA and PSO improves the performance indices of PID andI-PD controllers.


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