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Complex form of manufactured plastic parts can be achieved with the utility of industrial injection molding processes. The process have its weaknesses where shrinkage and warpage are found to be major defects. There are various optimization algorithms that can be employed to overcome the issue of shrinkage. One of it is Glowworm Swarm Optimization (GSO) which can be utilized to identify the optimal processing parameters setting to minimize shrinkages. A Low Density Polyethylene (LDPE) part was tested with the processing parameters of packing pressure, cooling time, melting temperature and mold temperature. The Autodesk Moldflow Insight (AMI) simulation recommended shrinkage value are 1.95% in x direction and 1.85% in the y direction. GSO approach demonstrated a reduction in shrinkage percentage in both x direction and y direction and the results were 1.84% and 1.70% respectively, thus ind minimizing the shrinkage can be employed in injection molding industries. [ABSTRACT FROM AUTHOR]

This study was concentrated on the effects of parameters processing on the molded part towards the warpage issues by implementing Computer-Aided Engineering (CAE) which is Autodesk Moldflow Insight (AMI) software for the simulation of the experiment. Details properties of 80 Tonne Nessei NEX 1000 injection molding machine has been used in this study. Acrylonitrile Butadiene Styrene (ABS) was used as the thermoplastic material to mold the front panel housing. The variable parameters of the process are melt temperature, cooling time, packing pressure and packing time. Experimental data are set off by Design of Experiment (DOE) based on face centred Center Composite Design (CCD). The prediction model of warpage will be used in Genetic Algorithm (GA) for optimization of variables to minimize the warpage. The result shows that GA has reduced the warpage value by 36.15%. [ABSTRACT FROM AUTHOR]

Industrial injection molding processes is a well-known process in producing and replicating a complex form of plastic parts. However, the process have some weaknesses where shrinkage and warpage are found to be major defects which are hard to control. There are a lot of optimization approaches that can be employed to overcome this kind of defects. In this study, Glowworm Swarm Optimization (GSO) approach has been applied to minimize warpage condition. A thin shell part was tested with the selected processing parameters of packing pressure, cooling time, melting temperature and mold temperature. Based on the Autodesk Moldflow Insight (AMI) simulation results warpage values in x and y directions are 0.2133mm and 0.2194mm respectively. GSO approach demonstrated a warpage reduction in both x and y directions and the results were 0.2053mm and 0.1824mm respectively. Thus, by utilizing GSO in minimizing warpage on the molded part can be applied in injection molding industries. [ABSTRACT FROM AUTHOR]

The development of comprehensive plastic injection molding process models and Computer-Aided Engineering (CAE) manufacturing provides a basis for realizing optimization of process parameters in plastic injection molding process towards warpage problems. The variable parameters of the process are melt temperature, melt temperature, packing pressure and packing time. In this study, front panel housing has been analyzed with thermoplastic material of Acrylonitrile Butadiene Styrene (ABS) used as the molded material. Design of Experiment (DOE) and Response surface methodology method were used to analyze the optimal process parameters setting. From the optimal processing parameters, the warpage has been optimized by 34.66%. [ABSTRACT FROM AUTHOR]

A molten plastic material that was injected into the mold cavity was one of the phase to undergo the injection molding process. Then, the part that was injected need to be packed under pressure that has been set. After that, it need to be ensure being solidified within the cooling time set. In addition, plastic injection molding has been widely used in manufacturing industry which were design in various form and complex shapes. Therefore, a better quality of plastic part produce need to be ensured in order to maintain the production time and cost. Warpage can be categorised as one of the critical defect that affect the quality of the molded part. Due to this defect, the optimization method had been implement in order to minimize the cost and production time. In this study, Response Surface Method (RSM) and Particle Swarm Optimization (PSO) were used as the optimization method. A front panel housing made from Polycarbonate (PC) was taken as the plastic part that need to be study. The highest contribution that leads to warpage was caused by the melt temperature parameter by 89.27% and the lowest contribution was packing time by 0.045%. The value of percentage difference of warpage in y direction using RSM and PSO were 015795 mm. The percentage difference calculates between RSM and PSO were 36.82%. This show there was no difference of percentage between these two methods. Therefore, both of these two parameters values of RSM and PSO can be used in order to optimize the warpage occur in Y direction. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization model of process parameters in Plastic Injection Molding (PIM) in which the quality characteristics for the plastic injection product that been study are warpage. In this study, front panel housing has been analyzed with thermoplastic material of Acrylonitrile Butadiene Styrene (ABS) used as the molded material. Design of Experiment (DOE), Response surface methodology (RSM) and Particle Swarm Optimization (PSO) method were used to analyze the optimal process parameters setting. From the results, warpage value has reduced by 35.77%. [ABSTRACT FROM AUTHOR]

The injection molding process has become known for its ability to form complex part. However, it also produced defects, the main defects form in this process were the shrinkage and warpage. These defects may formed due to several factors which involves the plastic injection molding process. The Genetic Algorithm (GA) approach is utilized in finding the shrinkage percentage and settings in minimizing the shrinkage. The part used is the Low Density Polyethylene (LDPE). The processing parameters used were packing pressure, cooling time, melt temperature and mold temperature. The recommended shrinkage values by AMI simulation are 1.95% in x direction and 1.85% in y direction. Meanwhile for GA results showed reduction in shrinkage percentage in the x and y direction. They are 1.79% and 1.63% respectively. Thus shows the GA ability in minimizing the shrinkage percentage and finding the optimal settings in producing the part. [ABSTRACT FROM AUTHOR]

Warpage is one of the common defect that occur during the injection molding process and one of the causes was process condition or parameter setting. The minimization of warpage in x and y direction were studied by going through a few stages of simulation using Integrating Finite Element (FE) Analysis, Moldflow analysis and Response Surface Methodology (RSM). The plastic part that examines in this study was front panel housing part with a thickness of 2.5 mm. There were four parameters that were selected by reviewing the previous research study, which were melt temperature, packing time, cooling time and packing pressure. All these parameters were combined and analyzed by conduct a two full factorial experimental design in Design Expert software. The FE analysis result obtains via analysis of variance (ANOVA) method was run as to determine the percentage contribution among these four parameters toward the warpage occur. [ABSTRACT FROM AUTHOR]

Injection molding process is a quite popular process in current industries to produce and replicate a various shape of plastic parts. However, the process involved a lot of processing parameters which is importance to control in order to minimize defect such as warpage. Nowadays, there are a lot of optimization approaches that can be employed to obtain the suitable processing parameters setting to overcome this kind of defects. In this study, an artificial intelligent optimization method which is Glowworm Swarm Optimization (GSO) approach has been carried out to minimize warpage condition. The front panel housing was tested with the selected processing parameters of melting temperature, cooling time, packing pressure and packing time. Based on the Autodesk Moldflow Insight (AMI) simulation results warpage value is 0.26mm and GSO approach demonstrated a warpage reduction and the results were 0.1625mm. Thus, by utilising GSO in minimising warpage on the molded part can be applied in injection molding industries. [ABSTRACT FROM AUTHOR]

The injection molding process has become known for its ability to form complex part. However, it also produced defects, the main defects form in this process were the shrinkage and warpage. These defects may formed due to several factors which involves the plastic injection molding process. The Response Surface Methodology (RSM) approach is utilized in finding the significant factor and recommended settings in minimizing the shrinkage percentage. The processing parameters used were packing pressure, cooling time, melt temperature and mold temperature. The results showed reduction in shrinkage percentage in the x and y direction as compared to recommended shrinkage percentage gained by AMI. They are 1.78% from 1.95% in x direction and 1.69% from 1.85 % respectively. Thus showed the RSM ability in minimizing the shrinkage percentage and finding the optimal setting in producing the part. [ABSTRACT FROM AUTHOR]

Warpage is one of the common defect that usually occur due to the inappropriate setting factor, material use and complex of mold design. Front panel housing was used as the plastic part that need to minimize their warpage value. The warpage in this study was optimize by using Response Surface Methodology and proceed with the Genetic Algorithm method. The Latin Square orthogonal array was utilise in determine the Design of Experiment method (DOE). The relationship of the parameter setting value and the output response which is warpage was shown in mathematical model obtain from RSM. The DOE and RSM were used to validate the model accuracy while the mathematical model was used in Genetic Algorithm in order to gain the appropriate parameter value of minimize warpage. These two optimization method then being compare with the recommended setting as to gain a better optimization method and parameter values. In addition, a better accuracy and reliability in injection molding process in molding the front panel plastic part can be largely improved in the industry due to an improvement shown in minimising the warpage. [ABSTRACT FROM AUTHOR]

In injection molding process, warpage is one of the most common defect that has been look into. Warped products not only visually unsatisfied, but might affect its functionality. Thus, a good parameter setting combination through optimization is required to minimize warpage. The conventional approach are complicated and inefficient. This paper review the recent non-conventional optimization approaches in injection molding process. It was found that naturally inspired algorithm is the mostly applied technique for warpage optimization problem. [ABSTRACT FROM AUTHOR]

In producing plastic products, injection moulding was well known for its manufacturing process. The quality of the plastic product depends on a certain processing parameter, and defects may occur when the processing parameters are wrongly set up. The purpose of this paper is to review the techniques related to the optimisation in injection moulding process of the shrinkage defect. One of the two categories of optimisation approach are nonclassical approach (Artificial Intelligence (AI) techniques) is reviewed by focusing on the shrinkage defects in optimising the injection moulding process from year 2012 until year 2016 (2017 instead). The result of review indicates that Artificial Neural Network (ANN) categorized as non-classical approach AI approach is considered as the most used by researchers for optimisation process besides shows good performance for optimisation of the injection moulding process. [ABSTRACT FROM AUTHOR]

Plastic injection moulding process has been one of the most widely employed processes in the production of plastics products. Similar to other forming processes, the characteristics of plastic injection moulding procedures are significantly affected by different quality level of the plastic products, particularly in regard to its process parameters. Several attempts have been made to investigate the effect of various level of process parameters, or in other words, in determining the efficient frontier of the parameters. A considerable amount of research has determined the effect of parameters in plastic injection moulding process as well as its influence on the quality and costs of the product. Hence, the purpose of the current research was to study the effect of different parameters which include injection moulding temperature and injection moulding pressure on polypropylene work material performed with plastic injection moulding process in the case of manufacturing USB Clip. [ABSTRACT FROM AUTHOR]

Today, there are various optimisation methods that have been explored by many researchers to find the appropriate processing parameters setting in injection moulding process. Based on previous researches, the application of optimisation work enhanced the moulded part quality. Apart from the quality, the productivity also plays an important role in the injection moulding process. Thus, some researchers have introduced the application of conformal cooling channels which have been proven improved both quality and productivity of the moulded part. Nonetheless, most of the previous researches in optimisation work are only focusing on the conventional straightdrilled cooling channels and the application of optimisation work on conformal cooling channels are still lacking. Therefore in this study, the application of optimisation work to improve warpage of the front panel housing part with straight-drilled and Milled Groove Square Shape (MGSS) conformal cooling channels has been presented. By performing Response Surface Methodology (RSM) optimisation approach, warpage of the moulded part has been optimised for both cooling channels. Based on the results warpage has optimised by 47.1% for straight-drilled cooling channels. While, for MGSS conformal cooling channels warpage has optimised by 46.5%. In addition, the finding also shows that the application of optimisation work on the conformal cooling channels offers the best outcome. [ABSTRACT FROM AUTHOR]

Plastic products nowadays have been leaning towards thin and light design concept. One of the way to achieve this is by reducing the wall thickness of the products. Due to this reason, technique in producing products with thin shell feature gradually increasing in demand. However, applying this feature increase the tendency of defects such as shrinkage and warpage. These defects may occur because of several factors that involved in the plastic injection moulding process. The approach used was based on the Response Surface Methodology (RSM) technique in finding the significant factor in the injection moulding process and recommended settings in minimising the warpage. The processing parameters used were packing time, cooling time, melt temperature and packing pressure for effective process. The results showed reduction of warpage in x,y and z direction. In minimising the response, RSM produce a suitable processing parameter for the part. [ABSTRACT FROM AUTHOR]

As the product nowadays moving towards thinner design, causing the production of the plastic product facing a lot of difficulties. This is due to the higher possibilities of defects occur as the thickness of the wall gets thinner. Demand for technique in reducing the defects increasing due to this factor. These defects has seen to be occur due to several factors in injection moulding process. In the study a Moldflow software was used in simulating the injection moulding process. While RSM is used in producing the mathematical model to be used as the input fitness function for the Matlab software. Particle Swarm Optimisation (PSO) technique is used in optimising the processing condition to reduce the amount of shrinkage and warpage of the plastic part. The results shows that there are a warpage reduction of 17.60% in x direction, 18.15% in y direction and 10.25% reduction in z direction respectively. The results shows the reliability of this artificial method in minimising the product warpage. [ABSTRACT FROM AUTHOR]

In manufacturing a variety of parts, plastic injection moulding is widely use. The injection moulding process parameters have played important role that affects the product's quality and productivity. There are many approaches in minimising the warpage ans shrinkage such as artificial neural network, genetic algorithm, glowworm swarm optimisation and hybrid approaches are addressed.In this paper, a systematic methodology for determining a warpage and shrinkage in injection moulding process especially in thin shell plastic parts are presented. To identify the effects of the machining parameters on the warpage and shrinkage value, response surface methodology is applied. In thos study, a part of electronic night lamp are chosen as the model. Firstly, experimental design were used to determine the injection parameters on warpage for different thickness value. The software used to analyse the warpage is Autodesk Moldflow Insight (AMI) 2012. [ABSTRACT FROM AUTHOR]

Warpage is a crucial topic in plastic injection moulding. Minimizing the warpage are significant for improving the quality of the moulded parts.one of the most influential factor in decreasing warpage in thin shell plastic part is dimensional stability. In this study, the thin shell plastic parts efficient minimization investigated by statistical design of experiment method and response surface methodology. To achieve the minimum warpage value, considering an example of a thin shell plastic part, the optimum process of dimensional parameters are determined. The model variables are the X dimension, Y dimension and Z dimension. The other parameters of effective parameter for minimization of warpage in thin shell plastic parts are mould temperature, melt temperature, cooling time, packing pressure, etc. Response Surface Methodology is used to create a predictive model for warpage. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization model of process parameters in Plastic Injection Moulding (PIM) in which the quality characteristics for the plastic injection product that been study are warpage. In this study, plastic dispenser of dental floss (thin shell part) has been analysed with thermoplastic material of Polypropylene (PP) used as the moulded material. Design of Experiment (DOE), Response surface methodology (RSM) and Particle Swarm Optimisation (PSO) method were used to analyse the optimal process parameters setting. From optimal processing parameter, the value of warpage inx, y and z-axis have been optimised by 22.1%, 27.34% and 23.81%, respectively. [ABSTRACT FROM AUTHOR]

This study was concentrated on the effects of process parameters in plastic injection moulding process towards warpage problem by using Autodesk Moldflow Insight (AMI) software for the simulation. In this study, plastic dispenser of dental floss has been analysed with thermoplastic material of Polypropylene ( PP ) used as the moulded material and details properties of 80 Tonne Nessei NEX 1000 injection moulding machine also has been used in this study. The variable parameters of the process are packing pressure, packing time, melt temperature and cooling time. Minimization of warpage obtained from the optimization and analysis data from the Design Expert software. Integration of Response Surface Methodology (RSM), Center Composite Design (CCD) with polynomial models that has been obtained from Design of Experiment (DOE) is the method used in this study. The results show that packing pressure is the main factor that will contribute to the formation of warpage in x-axis and y-axis. While in z-axis, the main factor is melt temperature and packing time is the less significant among the four parameters in x, y and z-axes. From optimal processing parameter, the value of warpage in x, y and z-axis have been optimised by 21.60%, 26.45% and 24.53%, respectively. [ABSTRACT FROM AUTHOR]

In this study, Computer Aided Engineering was used for injection moulding simulation. The method of Design of experiment (DOE) was utilize according to the Latin Square orthogonal array. The relationship between the injection moulding parameters and warpage were identify based on the experimental data that used. Response Surface Methodology (RSM) was used as to validate the model accuracy. Then, the RSM and GA method were combine as to examine the optimum injection moulding process parameter. Therefore the optimisation of injection moulding is largely improve and the result shown an increasing accuracy and also reliability. The propose method by combining RSM and GA method also contribute in minimising the warpage from occur. [ABSTRACT FROM AUTHOR]

Plastic injection moulding is a popular manufacturing method not only it is reliable, but also efficient and cost saving. It able to produce plastic part with detailed features and complex geometry. However, defects in injection moulding process degrades the quality and aesthetic of the injection moulded product. The most common defect occur in the process is warpage. Inappropriate process parameter setting of injection moulding machine is one of the reason that leads to the occurrence of warpage. The aims of this study were to improve the quality of injection moulded part by investigating the optimal parameters in minimizing warpage using Response Surface Methodology (RSM) and Glowworm Swarm Optimization (GSO). Subsequent to this, the most significant parameter was identified and recommended parameters setting was compared with the optimized parameter setting using RSM and GSO. In this research, the mobile phone case was selected as case study. The mould temperature, melt temperature, packing pressure, packing time and cooling time were selected as variables whereas warpage in y-direction was selected as responses in this research. The simulation was carried out by using Autodesk Moldflow Insight 2012. In addition, the RSM was performed by using Design Expert 7.0 whereas the GSO was utilized by using MATLAB. The warpage in y direction recommended by RSM were reduced by 70 %. The warpages recommended by GSO were decreased by 61 % in y direction. The resulting warpages under optimal parameter setting by RSM and GSO were validated by simulation in AMI 2012. RSM performed better than GSO in solving warpage issue. [ABSTRACT FROM AUTHOR]

In injection moulding process ,it is important to keep the productivity increase constantly with least of waste produced such as warpage defect. Thus, this study is concerning on minimizing warpage defect on wheel caster part. Apart from eliminating product wastes, this project also giving out best optimization techniques using response surface methodology. This research studied on five parameters A-packing pressure, B-packing time, C-mold temperature, Dmelting temperature and E-cooling time. The optimization showed that packing pressure is the most significant parameter. Warpage have been improved 42.64% from 0.6524 mm to 0.3742mm. [ABSTRACT FROM AUTHOR]

This paper presents a systematic methodology to analyse the warpage of the side arm part using Autodesk Moldflow Insight software. Response Surface Methodology (RSM) was proposed to optimise the processing parameters that will result in optimal solutions by efficiently minimising the warpage of the side arm part. The variable parameters considered in this study was based on most significant parameters affecting warpage stated by previous researchers, that is melt temperature, mould temperature and packing pressure while adding packing time and cooling time as these is the commonly used parameters by researchers. The results show that warpage was improved by 10.15% and the most significant parameters affecting warpage are packing pressure. [ABSTRACT FROM AUTHOR]

This paper discusses on an analysis run via injection moulding process in determination of the optimum processing parameters used for manufacturing side arms of catheters in minimizing the warpage issues. The optimization method used was RSM. Moreover, in this research tries to find the most significant factor affecting the warpage. From the previous literature review,4 most significant parameters on warpage defect was selected. Those parameters were melt temperature, packing time, packing pressure, mould temperature and cooling time. At the beginning, side arm was drawn using software of CATIA V5. Then, software Mouldflow and Design Expert were employed to analyses on the popular warpage issues. After that, GSO artificial intelligence was apply using the mathematical model from Design Expert for more optimization on RSM result. Recommended parameter settings from the simulation work were then compared with the optimization work of RSM and GSO. The result show that the warpage on the side arm was improved by 3.27 % [ABSTRACT FROM AUTHOR]

The injection moulding process has been widely used in industry to produce plastic parts of a variety of geometries and shapes. However, the difficulty in adjusting optimum process parameter setting will lead some defect on injected moulded part such as warpage. The side arm used as a case study having warpage problem during it production process in injection moulding. Hence, the work reported herein is about in minimising warpage on side arm product by optimising the process parameters using Response Surface Methodology (RSM). Therefore, the melt temperature, packing pressure, mould temperature, packing time and cooling time were selected as variable parameters in reducing warpage from the injection moulding process. [ABSTRACT FROM AUTHOR]

In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively. [ABSTRACT FROM AUTHOR]

Todays, there are various of optimisation methods that have been studied by many researchers in order to find the appropriate combination of processing parameters setting in the injection moulding process. From the previous literatures, the optimisation works have been proven will improve the moulded part quality. In this study, the application of optimisation work to improve warpage of front panel housing has 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 in order to define 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 47.1% after optimisation. The findings show that the application of optimisation work offers the best quality of moulded part produced. [ABSTRACT FROM AUTHOR]

Nowadays, there are various methods of optimisation works that have been explored by many researchers to find the appropriate processing parameters setting of injection moulding process. From the previous researches, it was reported that the optimisation work improved the moulded part quality. Apart from quality, the productivity in the injection moulding process also plays an important role. Therefore, some of the researchers have introduced the conformal cooling channels which have been proven to improve the quality and productivity of the moulded part. However, the application of optimisation work to determine an appropriate processing parameters setting in previous researches are only focusing on the conventional straight-drilled cooling channels and the application in conformal cooling channels are still lacking. In this study, the application of optimisation work to improve warpage of the front panel housing part with Milled Groove Square Shape (MGSS) conformal cooling channels has been explored. By selecting cooling time, cooling temperature, packing pressure and melt temperature as the variables, design of experiment (DOE) has been constructed by using the central composite design (CCD) approach. By performing Response Surface Methodology (RSM) optimisation approach, warpage of the moulded part has been optimised. Based on the results warpage has optimised by 46.5%. The finding shows that the application of optimisation work on the conformal cooling channels offers the best outcome. [ABSTRACT FROM AUTHOR]