scholarly journals Predictive model and optimization of processing parameters for plastic injection moulding

2017 ◽  
Vol 51 (4) ◽  
pp. 597-602 ◽  
Author(s):  
D. Kramar ◽  
D. Cica
Keyword(s):  
Predictive Model ◽  
Injection Moulding ◽  
Processing Parameters ◽  
Plastic Injection Moulding ◽  
Plastic Injection

scholarly journals Practical Applications of Taguchi Method for Optimization of Processing Parameters for Plastic Injection Moulding: A Retrospective Review

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Ng Chin Fei ◽  
Nik Mizamzul Mehat ◽  
Shahrul Kamaruddin
Keyword(s):  
Taguchi Method ◽  
Injection Moulding ◽  
Principal Component ◽  
Processing Parameters ◽  
Great Success ◽  
Processing Parameter ◽  
Practical Applications ◽  
Multiple Parameters ◽  
Plastic Injection Moulding ◽  
Plastic Injection

Determining the optimal processing parameter is routinely performed in the plastic injection moulding industry as it has a direct and dramatic influence on product quality and costs. In this volatile and fiercely competitive market, traditional trial-and-error is no longer sufficient to meet the challenges of globalization. This paper aims to review the research of the practical use of Taguchi method in the optimization of processing parameters for injection moulding. Taguchi method has been employed with great success in experimental designs for problems with multiple parameters due to its practicality and robustness. However, it is realized that there is no single technique that appears to be superior in solving different kinds of problem. Improvements are to be expected by integrating the practical use of the Taguchi method into other optimization approaches to enhance the efficiency of the optimization process. The review will shed light on the standalone Taguchi method and integration of Taguchi method with various approaches including numerical simulation, grey relational analysis (GRA), principal component analysis (PCA), artificial neural network (ANN), and genetic algorithm (GA). All the features, advantages, and connection of the Taguchi-based optimization approaches are discussed.

scholarly journals Optimisation of Shrinkage and Strength on Thick Plate Part Using Recycled LDPE Materials

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1795
Author(s):  
Norshahira Roslan ◽  
Shayfull Zamree Abd Rahim ◽  
Abdellah El-hadj Abdellah ◽  
Mohd Mustafa Al Bakri Abdullah ◽  
Katarzyna Błoch ◽  
...  
Keyword(s):  
Tensile Strength ◽  
Thick Plate ◽  
Processing Parameters ◽  
Processing Parameter ◽  
Plastic Injection Moulding ◽  
Optimal Setting ◽  
Quality Of Products ◽  
Validation Tests ◽  
Plastic Injection

Achieving good quality of products from plastic injection moulding processes is very challenging, since the process comprises many affecting parameters. Common defects such as warpage are hard to avoid, and the defective parts will eventually go to waste, leading to unnecessary costs to the manufacturer. The use of recycled material from postindustrial waste has been studied by a few researchers. However, the application of an optimisation method by which to optimise processing parameters to mould parts using recycled materials remains lacking. In this study, Response Surface Methodology (RSM) and Particle Swarm Optimisation (PSO) methods were conducted on thick plate parts moulded using virgin and recycled low-density polyethylene (LDPE) materials (100:0, 70:30, 60:40 and 50:50; virgin to recycle material ratios) to find the optimal input parameters for each of the material ratios. Shrinkage in the x and y directions increased in correlation with the recycled ratio, compared to virgin material. Meanwhile, the tensile strength of the thick plate part continued to decrease when the recycled ratio increased. R30 (70:30) had the optimum shrinkage in the x direction with respect to R0 (100:0) material where the shrinkage increased by 24.49% (RSM) and 33.20% (PSO). On the other hand, the shrinkage in the y direction for R30 material increased by 4.48% (RSM) and decreased by 2.67% (PSO), while the tensile strength of R30 (70:30) material decreased by 0.51% (RSM) and 2.68% (PSO) as compared to R0 (100:0) material. Validation tests indicated that the optimal setting of processing parameter suggested by PSO and RSM for R0 (100:0), R30 (70:30), R40 (60:40) and R50 (50:50) was less than 10%.

Practice vs. laboratory tests for plastic injection moulding

2001 ◽  
Vol 142-144 ◽  
pp. 143-145 ◽  
Author(s):  
M. Van Stappen ◽  
K. Vandierendonck ◽  
C. Mol ◽  
E. Beeckman ◽  
E. De Clercq
Keyword(s):  
Injection Moulding ◽  
Laboratory Tests ◽  
Plastic Injection Moulding ◽  
Plastic Injection
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