scholarly journals Crystallinity control in parts produced from stereolithography injection mould tooling

2003 ◽  
Vol 217 (4) ◽  
pp. 269-276 ◽  
Author(s):  
R A Harris ◽  
R J M Hague ◽  
P M Dickens
Keyword(s):  
Material Property ◽  
Injection Moulding ◽  
Degree Of Crystallinity ◽  
Scanning Calorimetry ◽  
Mould Material ◽  
Moulding Process ◽  
Process Modification ◽  
Injection Moulding Process ◽  
Metal Tooling ◽  
Metal Tools

The use of moulds produced by stereolithography (SL) for injection moulding provides a quick route to manufacturing a low volume of parts without expensivehard tooling. However, these parts have been shown to exhibit different material property characteristics than those produced from metal tooling. The aim of the present work is to research methods that would allow SL moulds to produce parts of similar material property characteristics to those from conventional metal tools. This work has identified that the different part characteristics are due to differing levels of crystallinity developed in the parts from the comparative mould varieties (SL and metal). These crystallinity differences have been associated with the cooling rates imparted owing to the thermal properties of the mould material. The latter part of this work concerns controlling and manipulating this degree of crystallinity. After a discussion of possible methods, two approaches are taken to modifying the crystalline content of parts produced by SL moulds. One of the approaches is material based, the other concerns the injection moulding process. Differential scanning calorimetry (DSC) is used to quantify the resulting levels of crystallinity in the parts. The results show that by process modification it is possible to produce parts by SL moulding that possess a similar crystalline content to those moulded from metal tooling. The use of modified materials allows parts created in SL and metal tools to be of a consistent crystalline content. The work concludes that not only are SL moulds capable of producing parts that are more like those from metal moulds but also present some unique opportunities that have been demonstrated to be unachievable in metal moulds.

Influence of mould material on ceramic disc dimensions in low-pressure injection moulding

2016 ◽  
Vol 231 (1-2) ◽  
pp. 187-195 ◽  
Author(s):  
Carlos A Costa ◽  
Carlos R Altafini ◽  
Fabio R Visioli ◽  
André P Baccin
Keyword(s):  
Cooling Rate ◽  
Injection Moulding ◽  
Low Pressure ◽  
Extraction Temperature ◽  
Mould Insert ◽  
Mould Material ◽  
Moulding Process ◽  
Pressure Injection ◽  
Injection Moulding Process ◽  
Geometric Deviations

This work presents a study regarding the influence of the cooling process, as a result of different mould insert materials, on ceramic parts dimensions obtained by low-pressure injection moulding process. Discs of ceramic with Ø80 × 2 mm, composed by 86 wt.% alumina (Al2O3) and 14 wt.% organic vehicle, were produced. An experimental injection mould was designed and manufactured with built-in heating and cooling systems, controlled by a DAQ (Measurement Computing – USB-TC) and thermocouples K type. Four types of insert materials were used: aluminium alloy (AA7075-T6), electrolytic copper, brass alloy (C36000) and SAE1045 steel. Tests were carried out considering injection moulding parameters constant, i.e. initial mould temperature, injection pressure and time and extraction temperature. All the post-process (debinding by wicking; final debinding and sintering) parameters were also kept constant. Parts were analysed considering dimensions, mass, geometry, visual aspects and defects. The results showed that the cooling rate resulting from the thermal conductivity of each material has influenced more significantly the dimensional shrinkage and mass reduction of the samples during the intermediate post-processes phases. The geometric deviations were different for each condition throughout the process and they increased in the final parts. The parts produced with higher cooling rate had higher geometric deviations.

Application of RSM to Optimize Moulding Conditions for Minimizing Shrinkage in Thermoplastic Processing

2016 ◽  
Vol 700 ◽  
pp. 12-21 ◽  
Author(s):  
S.M. Nasir ◽  
K.A. Ismail ◽  
Z. Shayfull
Keyword(s):  
Injection Moulding ◽  
Variable Parameter ◽  
Acrylonitrile Butadiene Styrene ◽  
Cooling Time ◽  
Inlet Temperature ◽  
Melt Temperature ◽  
Mould Material ◽  
Moulding Process ◽  
Packing Pressure ◽  
Injection Moulding Process

This study focuses on the analysis of plastic injection moulding process simulation using Autodesk Moldflow Insight (AMI) software in order to minimize shrinkage by optimizing the process parameters. Two types of gates which is single and dual gates have been analysed. Nessei NEX 1000 injection moulding machine and P20 mould material details are incorporated in this study on top of Acrylonitrile Butadiene Styrene (ABS) as a moulded thermoplastic material. Coolant inlet temperature, melt temperature, packing pressure and cooling time are selected as a variable parameter. Design Expert software is obtained as a medium for analysis and optimisation to minimize the shrinkage. The polynomial models are obtained using Design of Experiment (DOE) integrated with RSM Center Composite Design (CCD) method in this study. The results show that packing pressure is a main factor that contributed to shrinkage followed by coolant inlet temperature, while melt temperature and cooling time has less significant for both single and dual gates. Meanwhile, single gate shows a better result of shrinkage compared to the dual gates.

Warpage Analysis of Single and Dual Gates Designed for Injection Moulding Using Response Surface Methodology

2015 ◽  
Vol 754-755 ◽  
pp. 775-783 ◽  
Author(s):  
S.M. Nasir ◽  
Khairul Azwan Ismail ◽  
Z. Shayfull ◽  
M.A. Fairuz
Keyword(s):  
Injection Moulding ◽  
Variable Parameter ◽  
Acrylonitrile Butadiene Styrene ◽  
Inlet Temperature ◽  
Melt Temperature ◽  
Mould Material ◽  
Moulding Process ◽  
Packing Pressure ◽  
Injection Moulding Process ◽  
Mould Design

This study focuses on the analysis of plastic injection moulding process simulation using Autodesk Moldflow Insight (AMI) software in order to correlate between process parameters as an input and warpage as an output for single and dual gates mould design. Nessei NEX 1000 injection moulding machine and P20 mould material details are incorporated in this study on top of Acrylonitrile Butadiene Styrene (ABS) as a moulded thermoplastic material. Coolant inlet temperature, material melt temperature, packing pressure and packing time are selected as a variable parameter. Design Expert software is obtained as a medium for analysis and optimization of input variables in order to minimize the warpage. RSM method as well as Analysis of Variance (ANOVA) has been applied in this study. The results of ANOVA show that some interactions between factors are significant towards warpage existence, which is coolant inlet temperature, material melt temperature and packing pressure. Furthermore, the model created using RSM can be used for warpage prediction and improvement due to a minimum value of error. From this study, the dual gate is the best solution which able to improve the warpage up to 80% instead of single.

Feedstock Characterization of Elemental Nickel and Titanium Powders Mixture for Metal Injection Moulding Process

2014 ◽  
Vol 575 ◽  
pp. 78-82 ◽  
Author(s):  
Rosliza Razali ◽  
Zulaila Abdullah ◽  
Istikamah Subuki ◽  
Muhammad Hussain Ismail ◽  
Norhamidi Muhamad
Keyword(s):  
Injection Moulding ◽  
Palm Stearin ◽  
Scanning Calorimetry ◽  
Moulding Process ◽  
Metal Injection Moulding ◽  
Injection Moulding Process ◽  
Initial Characterization ◽  
Titanium Powders ◽  
Internal Mixer

The success of metal injection moulding (MIM) process is significantly influenced by the homogeneity level of the powder-binder mixture (feedstock). This paper highlights some initial characterization of the feedstock containing elemental Ni and Ti powders mixture, (50.8 at.% Ni/ 49.2 at.% Ti) mixed with Palm stearin-based binder system. The feedstock was prepared using an internal mixer, HAAKE Rheomix at a temperature of 160°C for 2 hours. The feedstock was then characterized by Differential Scanning Calorimetry (DSC), Thermogravimetric (TGA), Scanning Electron Microscopy (SEM) and Capillary Rheometer. All the results obtained were analyzed and discussed for further injection moulding process.

Evaluation of Cadmould Software to Simulate the Filling Phase of a Natural Rubber Compound in Injection Moulding Process

2013 ◽  
Vol 747 ◽  
pp. 571-574 ◽  
Author(s):  
Zulkifli Mohamad Ariff ◽  
T.H. Khang
Keyword(s):  
Natural Rubber ◽  
Injection Moulding ◽  
Input Data ◽  
Cure Kinetics ◽  
Rubber Compound ◽  
Moulding Process ◽  
Related Data ◽  
Mould Filling ◽  
Injection Moulding Process ◽  
Material Input

The possibility of using Cadmould software to simulate the filling behaviour of a natural rubber compound during an injection moulding process was investigated. For the simulation process, the determination of required material input data involving the rheological and cure kinetics data of the designed rubber compound were conducted. It was discovered that the acquired data were able to function as reliable material input data as they were comparable with related data available in the Cadmould software materials database. Verification of the simulated filling profiles by experimental short shots specimens showed that the Cadmould Rubber Package was able to predict the realistic filling behaviour of the formulated natural rubber compound inside the mould cavity when the measured material data were utilized. Whereas, the usage of available material database from the software failed to model the mould filling progression of the intended natural rubber compound.

Multi-Response Parameters Optimisation for Energy-Efficient Injection Moulding Process via Dynamic Shainin DOE Method

2013 ◽  
Vol 554-557 ◽  
pp. 1669-1682 ◽  
Author(s):  
Kam Hoe Yin ◽  
Hui Leng Choo ◽  
Dunant Halim ◽  
Chris Rudd
Keyword(s):  
Energy Consumption ◽  
Process Parameters ◽  
Injection Moulding ◽  
Shop Floor ◽  
Operational Experience ◽  
Moulding Process ◽  
Part Quality ◽  
Control Factors ◽  
Injection Moulding Process ◽  
Signal Response

Process parameters optimisation has been identified as a potential approach to realise a greener injection moulding process. However, reduction in the process energy consumption does not necessarily imply a good part quality. An effective multi-response optimisation process can be demanding and often relies on extensive operational experience from human operators. Therefore, this research focuses on an attempt to develop a more user-friendly approach which could simultaneously deal with the requirements of energy efficiency and part quality. This research proposes a novel approach using a dynamic Shainin Design of Experiment (DOE) methodology to determine an optimal combination of process parameters used in the injection moulding process. The Shainin DOE method is adopted to pinpoint the most important factors on energy consumption and the targeted part quality whereas the ‘dynamic’ term refers to the signal-response system. The effectiveness of the proposed approach was illustrated by investigating the influence of various dominant parameters on the specific energy consumption (SEC) and the Charpy impact strength (CIS) of polypropylene (PP) material after being injection-moulded into impact test specimens. From the experimental results, barrel temperature was identified as the signal factor while mould temperature and cooling time were used as control factors in the full factorial experiments. Then, response function modelling (RFM) was built to characterise the signal-response relationship as a function of the control factors. Finally, RFM led to a trade-off solution where reducing part-to-part variation for CIS resulted in an increase of SEC. Therefore, the research outcomes have demonstrated that the proposed methodology can be practically applied at the factory shop floor to achieve different performance output targets specified by the customer or the manufacturer’s intent.

Modelling for Injection Moulding Process Based on Principal Component Regression Method

2011 ◽  
Author(s):  
Nong Gu. ◽  
Dougas Creighton ◽  
Saeid Nahavandi ◽  
Francisco Chinesta ◽  
Yvan Chastel ◽  
...  
Keyword(s):  
Injection Moulding ◽  
Principal Component Regression ◽  
Principal Component ◽  
Regression Method ◽  
Moulding Process ◽  
Injection Moulding Process
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