Roles of Thermal Control in Polymer Injection Molding Process

1990 ◽  
Vol 93 (864) ◽  
pp. 930-931
Author(s):  
Yasuo KUROSAKI
Keyword(s):  
Injection Molding ◽  
Thermal Control ◽  
Injection Molding Process ◽  
Molding Process ◽  
Polymer Injection ◽  
Polymer Injection Molding

scholarly journals Electricity Consumption Estimation of the Polymer Material Injection-Molding Manufacturing Process: Empirical Model and Application

Materials ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 1740 ◽  
Author(s):  
Ana Elduque ◽  
Daniel Elduque ◽  
Carmelo Pina ◽  
Isabel Clavería ◽  
Carlos Javierre
Keyword(s):  
Environmental Impact ◽  
Injection Molding ◽  
Empirical Model ◽  
Electricity Consumption ◽  
Injection Molding Process ◽  
Molding Process ◽  
Polymer Injection ◽  
Wide Range ◽  
Molded Parts ◽  
Polymer Injection Molding

Polymer injection-molding is one of the most used manufacturing processes for the production of plastic products. Its electricity consumption highly influences its cost as well as its environmental impact. Reducing these factors is one of the challenges that material science and production engineering face today. However, there is currently a lack of data regarding electricity consumption values for injection-molding, which leads to significant errors due to the inherent high variability of injection-molding and its configurations. In this paper, an empirical model is proposed to better estimate the electricity consumption and the environmental impact of the injection-molding process. This empirical model was created after measuring the electricity consumption of a wide range of parts. It provides a method to estimate both electricity consumption and environmental impact, taking into account characteristics of both the molded parts and the molding machine. A case study of an induction cooktop housing is presented, showing adequate accuracy of the empirical model and the importance of proper machine selection to reduce cost, electricity consumption, and environmental impact.

Computer Simulation of Warpage Formation in Polymer Injection Molding of a Step Pad

2006 ◽  
Author(s):  
Sridhar P. Ramamurthy ◽  
Lyle Steenson ◽  
Zhong Hu
Keyword(s):  
Injection Molding ◽  
Cooling System ◽  
Three Dimensional ◽  
Nonlinear Material ◽  
Injection Molding Process ◽  
Molding Process ◽  
Element Analysis ◽  
Polymer Injection ◽  
Fea Model ◽  
Polymer Injection Molding

Warpage is one of the most common defects of a plastic product in the polymer injection molding process. It is attributed to the differential shrinkage after the part is ejected from the die cavity due to the nonlinear material property of the polymer, improper design of the cooling system, geometry of the part and the related process parameters. In this paper, the warpage formation of a plastic part, Step Pad of polypropylene copolymer, in the cooling stage of the polymer injection molding process was simulated by finite element analysis (FEA). A three-dimensional FEA model, taking into account the nonlinear material (polypropylene copolymer) properties, with a thermal-structural sequential coupled approach of higher computing efficiency was developed. The effects of mold closed time and layout of cooling system on the dimension and shape of the part were investigated. Industrial experiments for the different mold closed times (25s, 30s, 35s, 40s, 45s, 50s, and 55s) were conducted. The simulation results were compared with the experimental results. The approach is effective in predicting warpage in the polymer injection molding processes.

Optimal Sensor Locations for Polymer Injection Molding Process

2014 ◽  
Vol 611-612 ◽  
pp. 1724-1733
Author(s):  
David Garcia ◽  
Ronan Le Goff ◽  
Maxime Gasse ◽  
Alexandre Aussem
Keyword(s):  
Injection Molding ◽  
Physical Phenomenon ◽  
Sensor Data ◽  
Injection Molding Process ◽  
Molding Process ◽  
Virtual Sensor ◽  
Polymer Injection ◽  
Sensor Configuration ◽  
Data Driven Modeling ◽  
Polymer Injection Molding

The subject discussed in this article concerns the determination of optimal sensor (pressure & temperature) configurations for polymer injection moulds. A sensor configuration is considered optimal when it is able to predict the product quality (dimension, warpage, etc.) with a good accuracy (from experimental data provided by these sensors). Initially, plastic engineers integrated sensors in moulds to acquire knowledge about their processes and to have better understanding of physical phenomenon. This article presents a numerical methodology to identify optimal combinations of sensors. The methodology is firstly based on polymer injection molding simulation to collect virtual sensor data. In a second step, virtual sensor data are analyzed by modern data-driven modeling techniques to identify optimal sensor configurations.

Computational Study of the Effect of Governing Parameters on a Polymer Injection Molding Process for Single-Cavity and Multicavity Mold Systems

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
M. Tutar ◽  
A. Karakus
Keyword(s):  
Injection Molding ◽  
Mold Insert ◽  
Polymer Melt ◽  
Injection Molding Process ◽  
Melt Flow ◽  
Flow Conditions ◽  
Molding Process ◽  
Polymer Injection ◽  
Solution Approach ◽  
Polymer Injection Molding

In the present study a more complete numerical solution approach using parallel computing technology is provided for the three-dimensional modeling of mold insert polymer injection molding process by considering the effects of phase-change and compressibility for non-Newtonian fluid flow conditions. A volume of fluid (VOF) method coupled with a finite volume approach is used to simulate the mold-filling stage of the injection molding process. The variations in viscosity and density in the polymer melt flow are successfully resolved in the present VOF method to more accurately represent the rheological behavior of the polymer melt flow during the mold filling. A comprehensive high-resolution differencing scheme (compressive interface capturing scheme for arbitrary meshes or CICSAM) is successfully utilized to capture moving interfaces and the pressure-implicit with splitting operators pressure-velocity coupling algorithm is employed to enable a higher degree of approximate relation between corrections for pressure and velocity. The capabilities of the proposed numerical methodology in modeling real molding flow conditions are verified through quantitative and qualitative comparisons with other simulation programs and the data obtained from the experimental study conducted. The present numerical results are also compared with each other for a polypropylene female threaded adaptor pipe fitting model with a metallic insert for varying governing process conditions/parameters to assess the modeling constraints and enhancements of the present numerical procedure and the effects of these conditions to optimize the polymer melt flow for mold insert polymer injection molding process. The numerical results suggest that the present numerical solution approach can be used with a confidence for further studies of optimization of design of mold insert polymer injection molding processes.

Comprehensive Online Control Strategies for Plastic Injection Molding Process

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Jaho Seo ◽  
Amir Khajepour ◽  
Jan P. Huissoon
Keyword(s):  
Injection Molding ◽  
Injection Pressure ◽  
Thermal Control ◽  
Plastic Injection Molding ◽  
Injection Molding Process ◽  
Molding Process ◽  
Element Analysis ◽  
Thermal Dynamics ◽  
Uncertain Dynamics ◽  
Plastic Injection

This study proposes an effective thermal control for plastic injection molding (polymer: Santoprene 8211-45 with density of 790 kg/m3, injection pressure: 1400 psi (9,652,660 Pa)) in a laminated die. For this purpose, a comprehensive control strategy is provided to cover various themes. First, a new method for determining the optimal sensor locations as a prerequisite step for modeling and controller design is introduced. Second, system identification through offline and online training with finite element analysis and neural network techniques are used to develop an accurate model by incorporating uncertain dynamics of the laminated die. Third, an additive feedforward control by adding direct adaptive inverse control to self-adaptive PID is developed for temperature control of cavity wall (cavity size: 52.9 × 32.07 × 16.03 mm). A verification of designed controller's performance demonstrates that the proposed strategy provides accurate online temperature tracking and faster response under thermal dynamics with various cycle-times in the injection mold process.

Efficient numerical simulation of injection mold filling with the lattice Boltzmann method

2017 ◽  
Vol 34 (2) ◽  
pp. 307-329 ◽  
Author(s):  
Lin Deng ◽  
Junjie Liang ◽  
Yun Zhang ◽  
Huamin Zhou ◽  
Zhigao Huang
Keyword(s):  
Injection Molding ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Present Model ◽  
Injection Molding Process ◽  
Content Type ◽  
Polymer Injection ◽  
Numerical Efficiency ◽  
Boltzmann Method ◽  
Polymer Injection Molding

Purpose Lattice Boltzmann method (LBM) has made great success in computational fluid dynamics, and this paper aims to establish an efficient simulation model for the polymer injection molding process using the LBM. The study aims to validate the capacity of the model for accurately predicting the injection molding process, to demonstrate the superior numerical efficiency in comparison with the current model based on the finite volume method (FVM). Design/methodology/approach The study adopts the stable multi-relaxation-time scheme of LBM to model the non-Newtonian polymer flow during the filling process. The volume of fluid method is naturally integrated to track the movement of the melt front. Additionally, a novel fractional-step thermal LBM is used to solve the convection-diffusion equation of the temperature field evolution, which is of high Peclet number. Through various simulation cases, the accuracy and stability of the present model are validated, and the higher numerical efficiency verified in comparison with the current FVM-based model. Findings The paper provides an efficient alternative to the current models in the simulation of polymer injection molding. Through the test cases, the model presented in this paper accurately predicts the filling process and successfully reproduces several characteristic phenomena of injection molding. Moreover, compared with the popular FVM-based models, the present model shows superior numerical efficiency, more fit for the future trend of parallel computing. Research limitations/implications Limited by the authors’ hardware resources, the programs of the present model and the FVM-based model are run on parallel up to 12 threads, which is adequate for most simulations of polymer injection molding. Through the tests, the present model has demonstrated the better numerical efficiency, and it is recommended for the researcher to investigate the parallel performance on even larger-scale parallel computing, with more threads. Originality/value To the authors’ knowledge, it is for the first time that the lattice Boltzmann method is applied in the simulation of injection molding, and the proposed model does obviously better in numerical efficiency than the current popular FVM-based models.

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