A methodology for shrinkage measurement in micro-injection moulding

Annicchiarico, Daniele; Attia, Usama M.; Alcock, Jeffrey R.

doi:10.1016/j.polymertesting.2013.03.021

Cited by 24 publications

(24 citation statements)

References 16 publications

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“…By considering semicrystalline (POM [106,111,112], HDPE and PP [105], HCPP and PC [113,114], PP and PA [111] or PA mixed with 316L [115]), amorphous polymers (PMMA [105,113,116], PS [105,113], COC [117], ABS [118]) or ceramic feedstock (Zr [119]), results identified the mold temperature as a critical parameter affecting shrinkage. Also, authors [11,112,120] determined that by increasing this parameter, led to an increased shrinkage. Same trend was determined by Tay et al [121] even considering a different material (316L feedstock).…”

Section: Processing Parameter Influencesmentioning

confidence: 99%

“…This parameter affected shrinkage in semicrystalline (POM [11], HDPE [105], HCPP [114], PC [113,114], PP [105]) amorphous (PMMA [105,110,113], PS [105,113]) or cyclic olefin polymers [117].…”

Section: Processing Parameter Influencesmentioning

confidence: 99%

“…The holding time critically affected shrinkage according to Wen and Wen [110]. A combined effect of holding time and mold temperature was identified as critical by Annicchiarico, Attia, and Alcock [11]. In the study conducted by Chang and Faison [36], the authors investigated the influence of five parameters in terms of shrinkage in both longitudinal and transversal to the flow direction, by molding amorphous (GPS and ABS) and semicrystalline polymers (HDPE).…”

Section: Processing Parameter Influencesmentioning

confidence: 99%

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Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Annicchiarico¹,

Alcock²

2014

Materials and Manufacturing Processes

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119

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Purpose: This paper reviews the factors affecting shrinkage of molded parts in injection molding. Methods: A selective screening of the papers published in the last 10 years was adopted. The review was organized according to molding scale (macro or micro) and by considering four branches of influence: material behaviors, processing parameters, mold, and specimen design. Results: Within the interval of confidence, at the macroscale, critical processing parameters were the temperatures, the packing parameters, cooling time, and injection speed; temperatures and packing parameters resulted critical factors at the microscale as well. Concerning the design aspects, the runner size and the ribs affect shrinkage at the macro and microscale, respectively. The analysis of the literature review has shown an absence of statistical approach for determining the material influences, a lack of information on shrinkage occur in powder-molded parts and the absence of data in specimen with dimensions below 10 m. Conclusions: The review collected the factors that affect shrinkage in injection molding, and identified three possible areas for further works.

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Section: Processing Parameter Influencesmentioning

confidence: 99%

Section: Processing Parameter Influencesmentioning

confidence: 99%

Section: Processing Parameter Influencesmentioning

confidence: 99%

See 1 more Smart Citation

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Annicchiarico¹,

Alcock²

2014

Materials and Manufacturing Processes

Self Cite

119

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show abstract

“…The melt flow length comparison with different injection speeds are shown in Figure 5. According to these results, with the common injection speed (lower than 500 mm/s [1,8,9]), when the injection speed increases from 100 mm/s to 500 mm/s, the melt flow length was increased 39.7%. However, with high-speed injection molding, when the injection speed increases to 1400 mm/s, the flow length could reach to 91% longer than the case of 100 mm/s.…”

Section: Resultsmentioning

confidence: 90%

Numerical Study on Flow Length in Injection Molding Process with High-Speed Injection Molding

Minh¹

2014

IJMEA

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Abstract:In thin-wall injection molding, due to the very fast polymer melt heat transfer to the mold wall, the freeze layer appears quickly during the filling stage. In this study, high-speed injection molding (up to 1400 mm/s injection speed) was studied. A mold of spiral shape, 0.4 mm thick, is used to verify the ability of melt filling under different injection speeds. Simulation by Moldflow software was also performed for verification. The result shows that when injection speeds vary for 100 mm/s, 500 mm/s, 1000 mm/s, and 1400 mm/s, the flow length to thickness ratio was increased with the value of 335, 467.5, 605, and 640, respectively. The simulation results also show that the heat transfer coefficient between hot melt and mold wall has a strong influence on the flow length, especially with the high-speed injection molding. In general, slower injection speed requires a higher heat transfer coefficient, whereas higher injection speed require only a lower heat transfer coefficient.

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“…For instances, Annicchiarico et al [6], proposed the half fractional factorial design of experiment optimisation method to investigate the processing parameter influence on the shrinkage in order to improve part quality. Squared specimen made from polyoxymethylene (POM) was used in this research.…”

Section: Introductionmentioning

confidence: 99%

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

et al. 2017

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Abstract. Nowadays, there are various of optimisation methods that have been explored by many researchers to find the appropriate processing parameters setting for the injection moulding process. From the previous researches, it was reported that the optimisation work has improved the moulded part quality. In this study, the application of optimisation work to improve warpage of the front panel housing have been explored. By selecting cooling time, coolant temperature, packing pressure and melt temperature as the variable parameters, design of experiment (DOE) have been constructed by using the rotatable central composite design (CCD) approach. Response Surface Methodology (RSM) was performed to obtain the mathematical model. This mathematical model then will be used in Glowworm Swarm Optimisation (GSO) method in order to determine the optimal processing parameters setting which will optimise the warpage condition. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 39.1% after optimisation. The finding shows that the application of optimisation work offers the best quality of moulded part produced.

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A methodology for shrinkage measurement in micro-injection moulding

Cited by 24 publications

References 16 publications

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Review of Factors that Affect Shrinkage of Molded Part in Injection Molding

Numerical Study on Flow Length in Injection Molding Process with High-Speed Injection Molding

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

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