Multi-objective optimization design of injection molding process parameters based on the improved efficient global optimization algorithm and non-dominated sorting-based genetic algorithm

Zhao, Jian; Cheng, Gengdong; Ruan, Shilun; Li, Zheng

doi:10.1007/s00170-014-6770-y

Cited by 58 publications

(33 citation statements)

References 18 publications

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“…GP algorithm takes the data of input-output form and processes it to generate the functions representing the relation between the output and three inputs [20]. GP is considered similar to genetic algorithm (GA) [21,22], except that the solution represented by GP is a structure. Generally, these functions are illustrated by the tree structures [19].…”

Section: Improved Evolutionary System Identification Approachmentioning

confidence: 99%

Performance evaluation of warping characteristic of fused deposition modelling process

Panda

Shankhwar

Garg

et al. 2016

Int J Adv Manuf Technol

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In recent years, fused deposition modelling (FDM) is gaining more popularity due to its distinct advantages in terms of cost-effectiveness, lower build times, and flexibility. Compared to other 3-D printing processes such as SLS, this process does not use any kind of high-intensity laser power to build functional parts out of CAD models and, hence, makes the process much simpler, cheaper, and adaptable. Past studies reveal that productivity of the FDM process can be further increased by effectively controlling its process parameters such as layer thickness, part orientation, extrusion temperature, and so on. In this regard, many authors have investigated the optimal parameter settings for improving part strength, surface finish, wear, and fatigue properties of FDM made prototypes. However, warping performance behavior has got very recent attention due to complex heat transfer mechanism involved during this process. Experimental investigations are necessary to understand the deformation behavior of prototypes. In addition, the quantification and optimization of warp deformation along with dimensional error poses a challenging multi-objective optimization problem. Therefore, this work proposes an evolutionary system identification (SI) approach to explicitly quantify the warp deformation and dimensional error based on the four inputs such as line width compensation, extrusion velocity, filling velocity, and layer thickness of FDM prototypes. The two models' performance analysis comprising of error metrics evaluation, cross-validation, and hypothesis tests is performed to validate its robustness. The analysis concluded that the layer thickness and extrusion velocity influence the warp deformation and, while filling velocity and line width compensation, influences the dimensional error the most.

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Section: Improved Evolutionary System Identification Approachmentioning

confidence: 99%

Performance evaluation of warping characteristic of fused deposition modelling process

Panda

Shankhwar

Garg

et al. 2016

Int J Adv Manuf Technol

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show abstract

“…The application of SAO can be found in Refs. [17][18][19][20][21][22][23], and the SAO is recognized as the effective approach for the process parameters optimization in the PIM. Table 1 shows the summary using the SAO approach in the PIM.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of injection molding process parameters for short cycle time and warpage reduction using conformal cooling channel

Kitayama

Miyakawa

Takano

et al. 2016

Int J Adv Manuf Technol

119

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In this paper, cooling performance of conformal cooling channel in plastic injection molding (PIM) is numerically and experimentally examined. To examine the cooling performance, cycle time and warpage are considered. Melt temperature, injection time, packing pressure, packing time, cooling time, and cooling temperature are taken as the design variables. A multi-objective optimization of the process parameters is then performed. First, the process parameters of conformal cooling channel are optimized. Numerical simulation in the PIM is so intensive that a sequential approximate optimization using a radial basis function network is used to identify a pareto-frontier. It is found from the numerical result that the cooling performance of conformal cooling channel is much improved, compared to the conventional cooling channel. Based on the numerical result, the conformal cooling channel is developed by using additive manufacturing technology. The experiment is then carried out to examine the validity of the conformal cooling channel. Through numerical and experimental result, it is confirmed that the conformal cooling channel is effective to the short cycle time and the warpage reduction.

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“…Traditional suspension optimization is usually to parameterize the virtual prototype simulation model combined with experimental design analysis or optimization algorithm and make multiple simulation optimization, but its calculation is time-consuming and it is difficult to converge for the complex models [14,15] . Integrating the virtual prototyping and optimization algorithm by the Isight Multidisciplinary optimization platform, and building a neural network approximation model based on the radial basis function to describe the relationship between design variables and responses, then substituting the rigid coupling model simulation model to conduct the optimization when precision of neural network model is satisfied, all of which can improve the optimize efficiency significantly.…”

Section: Introductionmentioning

confidence: 99%

Design optimization and test for a pendulum suspension of the crop sprayer boom in dynamic conditions based on a six DOF motion simulator

Cui

Mao

Xue

et al. 2018

International Journal of Agricultural and Biological Engineering

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Spray deposit distribution from a field sprayer is mainly affected by the boom movements when the tractor is driven over a rough soil surface, the pendulum suspension that used to reduce and control the movement of spray boom by isolating the boom from vibrations of the tractor will directly enhance uniform deposition of chemicals. However, how to match the parameters of the suspension with the properties of the boom is the key problem. The dynamic rigid-flexible coupling model of the virtual prototype of the spray boom suspension system was established by using ADAMS and ABAQUS software. An optimization of the suspension parameters for a large spay boom was carried out based on the optimal Latin hypercube design, radial basis function neural network, and multi-objective genetic algorithm NSGA-II. After modified parameters of the suspension, the travel of the sprayer on a typical field motion track was simulated based on a six DOF motion simulator, and the dynamic behavior of the boom suspension was measured. The results show that RMS of the measured boom roll angle and the boom center displacement for optimized solution were reduced by 14.76% and 12.43% compared with the original suspension. Finally, the inertial measurement unit (IMU) was used to measure the movements of the sprayer vehicle during the pesticide application on the Hongze Lake Farm, the experiment of field condition reproduced by using the six DOF motion simulator, the standard deviation of the roll angle and vibration displacement for the optimized sprayer boom are only 0.6382° and 62.279 mm respectively. The research provides theoretical basis and experimental method for parameter optimization of large scale boom suspension.

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Multi-objective optimization design of injection molding process parameters based on the improved efficient global optimization algorithm and non-dominated sorting-based genetic algorithm

Cited by 58 publications

References 18 publications

Performance evaluation of warping characteristic of fused deposition modelling process

Performance evaluation of warping characteristic of fused deposition modelling process

Multi-objective optimization of injection molding process parameters for short cycle time and warpage reduction using conformal cooling channel

Design optimization and test for a pendulum suspension of the crop sprayer boom in dynamic conditions based on a six DOF motion simulator

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