Analysis of Volumetric Shrinkage and Optimization of Process Parameters in Injection Molding

2012 ◽  
Vol 217-219 ◽  
pp. 2065-2069 ◽  
Author(s):  
Ji Ping Chen ◽  
Zhi Ping Ding
Keyword(s):  
Injection Molding ◽  
Regression Model ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Processing Parameters ◽  
Volumetric Shrinkage ◽  
Plastic Part ◽  
Melt Temperature ◽  
Optimization Of Process Parameters ◽  
Design Variables

Based on experimental method of factorial design, numerical simulation of injection molding using Moldflow software has been done. The effects of the gate number-distribution, melt temperature, packing pressure, packing time, injection time, etc. on volumetric shrinkage and the two-way interactions among factors in injection molding of plastic part have been researched. The regression model for volumetric shrinkage of plastic part has been obtained through multiple linear regression analysis of the experimental data. The optimization model has been established to optimize processing parameters setting leading factors which effect volumetric shrinkage as design variables and regression model of volumetric shrinkage as objective function. The volumetric shrinkage value of plastic part is less than the minimum volumetric shrinkage value of the main experiment, which indicates that the method has a good practical value in engineering.

Optimization of Injection Molding Parameters for Plastic Part Using Taguchi-TOPSIS Method

2011 ◽  
Vol 421 ◽  
pp. 440-443 ◽  
Author(s):  
Shie Chen Yang ◽  
Feng Che Tsai ◽  
Tsuo Fei Mao ◽  
Amine Ghali Benna ◽  
Ling You Huang
Keyword(s):  
Injection Molding ◽  
Volumetric Shrinkage ◽  
Prototype Model ◽  
Topsis Method ◽  
Plastic Part ◽  
Melt Temperature ◽  
Automobile Part ◽  
Finite Element Software ◽  
Injection Parameters ◽  
Outstanding Result

This paper reports an simulation study to improve the shrinkage of plastic automobile part by optimizing the injection molding parameters using the Taguchi-TOPSIS method. The Reverse Engineering(RE) and rapid prototyping (RP) technique were used to modelling and createing a prototype model of plastic automobile part. Employing the finite element software, MoldFlow Plastic Insight, the effect of injection parameters on the warpage and shrinkage of plastic part were examined carefully. The simulation results show that Taguchi-TOPSIS method provided an outstanding result for the optimization of injection parameters to produce minimum volumetric shrinkage. The injection parameter of melt temperature was the most significant parameter that influences the warpage and volumetric shrinkage for plastic automobile part in this study.

scholarly journals Effects of Injection Molding Screw Tips on Polymer Mixing

2018 ◽  
Vol 62 (3) ◽  
pp. 241-246 ◽  
Author(s):  
Dániel Török ◽  
József Gábor Kovács
Keyword(s):  
Injection Molding ◽  
Processing Parameters ◽  
Raw Material ◽  
Molding Machine ◽  
Surface Color ◽  
Melt Temperature ◽  
Injection Molding Machine ◽  
Aesthetic Appearance ◽  
Molded Parts ◽  
Injection Molded

In all fields of industry it is important to produce parts with good quality. Injection molded parts usually have to meet strict requirements technically and aesthetically. The aim of the measurements presented in our paper is to investigate the aesthetic appearance, such as surface color homogeneity, of injection molded parts. It depends on several factors, the raw material, the colorants, the injection molding machine and the processing parameters. In this project we investigated the effects of the injection molding machine on surface color homogeneity. We focused on injection molding screw tips and investigated five screw tips with different geometries. We produced flat specimens colored with a masterbatch and investigated color homogeneity. To evaluate the color homogeneity of the specimens, we used digital image analysis software developed by us. After that we measured the plastication rate and the melt temperature of the polymer melt because mixing depends on these factors. Our results showed that the screw tips (dynamic mixers) can improve surface color homogeneity but they cause an increase in melt temperature and a decrease in the plastication rate.

Warpage and Shrinkage Analysis and Optimization of Rapid Tooling Molded thin Wall Component Using Modified Particle Swarm Algorithm

2019 ◽  
Vol 18 (01) ◽  
pp. 85-102 ◽  
Author(s):  
Sagar Kumar ◽  
Amit Kumar Singh
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Simulation Analysis ◽  
Statistical Significance ◽  
Particle Swarm ◽  
Processing Parameters ◽  
Particle Swarm Algorithm ◽  
Thin Wall ◽  
Polybutylene Terephthalate ◽  
Melt Temperature

This paper presents a systematic methodology to determine optimal injection molding conditions for minimum warpage and shrinkage in a thin wall relay part using modified particle swarm optimization algorithm (MPSO). Polybutylene terephthalate (PBT) and polyethylene terephthalate (PET) were injected in a thin wall relay component for different processing parameters: melt temperature, packing pressure and packing time. Further, Taguchi’s L9 (3[Formula: see text] orthogonal array is used for conducting simulation analysis to consider the interaction effects of the above parameters. A predictive mathematical model for shrinkage and warpage is developed in terms of the above process parameters using regression analysis. ANOVA analysis is performed to establish statistical significance within the injection molding parameters. The analytical model is further optimized using a newly developed MPSO algorithm and the process parameters values are predicted for minimizing shrinkage and warpage. The predicted values of shrinkage and warpage using MPSO algorithm are improved by approximately 30% as compared to the initial simulation values and comparable to previous literature results.

scholarly journals Cluster and regression analysis for predicting salinity in groundwater

2018 ◽  
Vol 192 ◽  
pp. 02007
Author(s):  
Phiraphat Aphiphan ◽  
Uma Seeboonruang ◽  
Somyot Kaitwanidvilai
Keyword(s):  
Electrical Conductivity ◽  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Water Levels ◽  
Groundwater Salinity ◽  
Groundwater Levels

Groundwater salinity is a major problem particularly in the northeastern region of Thailand. Saline groundwater can cause widespread saline soil problem resulting in reducing agricultural productivity as in the Lower Nam Kam River Basin. In order to better manage the salinity problem, it is important to be able to predict the groundwater salinity. The objective of this research was to create a cluster-regression model for predicting the groundwater salinity. The indicator of groundwater salinity in this study was electrical conductivity because it was simple to measure in field. Ninety-eight parameters were measured including precipitation, surface water levels, groundwater levels and electrical conductivity. In this study, the highest groundwater salinity at 3 wells was predicted using the combined cluster and multiple linear regression analysis. Cross correlation and cluster analysis were applied in order to reduce the number of parameters to effectively predict the quality. After the parameter selection, multiple linear regression was applied and the modeling results obtained were R2 of 0.888, 0.918, and 0.692, respectively. This linear regression model technique can be applied elsewhere in the similar situation.

The simulation of the warpage rule of the thin-walled part of polypropylene composite based on the coupling effect of mold deformation and injection molding process

2018 ◽  
Vol 25 (3) ◽  
pp. 593-601 ◽  
Author(s):  
Jixiang Zhang ◽  
Xiaoyi Yin ◽  
Fengzhi Liu ◽  
Pan Yang
Keyword(s):  
Injection Molding ◽  
Coupling Effect ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Plastic Part ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure ◽  
Thin Walled ◽  
Packing Time

Abstract Aiming at the problem that a thin-walled plastic part easily produces warpage, an orthogonal experimental method was used for multiparameter coupling analysis, with mold structure parameters and injection molding process parameters considered synthetically. The plastic part deformation under different experiment schemes was comparatively studied, and the key factors affecting the plastic part warpage were analyzed. Then the injection molding process was optimized. The results showed that the important order of the influence factors for the plastic part warpage was packing pressure, packing time, cooling plan, mold temperature, and melt temperature. Among them, packing pressure was the most significant factor. The optimal injection molding process schemes reducing the plastic part warpage were melt temperature (260°C), mold temperature (60°C), packing pressure (150 MPa), packing time (2 s), and cooling plan 3. In this situation, the forming plate flatness was better.

Reduction in Defect Rate by Taguchi Method in Plastic Injection Molded Components

2012 ◽  
Vol 488-489 ◽  
pp. 269-273 ◽  
Author(s):  
G.S. Dangayach ◽  
Deepak Kumar
Keyword(s):  
Injection Molding ◽  
Injection Pressure ◽  
Processing Parameters ◽  
Process Conditions ◽  
Melt Temperature ◽  
Defect Rate ◽  
Packing Pressure ◽  
Optimal Injection ◽  
Packing Time ◽  
Plastic Injection

In the present era, competition gets tougher; there is more pressure on manufacturing sectors to improve quality and customer satisfaction while decreasing cost and increasing productivity. These can be achieved by using modern quality management systems and process improvement techniques to reduce the process variability and driven waste within manufacturing process using effective application of statistical tools. Taguchi technique is well known technique to solve industrial problems. This technique is fast and can pinpoint the chief causes and variations. Plastic injection molding is suitable for mass production articles since complex geometries can be obtained in a single production step. The difficulty in setting optimal process conditions may cause defects in parts, such as shrinkage and warpage. In this paper, optimal injection molding conditions for minimum shrinkage were determined by the Taguchi design of experiment (DOE) approach. Polypropylene (PP) was injected in circular shaped specimens under various processing parameters: melt temperature, injection pressure, packing pressure and packing time. S/N ratios were utilized for determining the optimal set of parameters. According to the results, 2400 C of melt temperature, 75 MPa of injection pressure, 50 MPa of packing pressure and 15 sec. of packing time gave minimum shrinkage of 0.951% for PP. Statically the most significant parameter was melt temperature for the PP. Injection pressure had the least effect on the shrinkage. The defect rate was reduced from 14% to 3%.

Optimization of the Injection Molding Process Parameters Based on Moldflow and Orthogonal Experiment

2013 ◽  
Vol 561 ◽  
pp. 239-243 ◽  
Author(s):  
Yong Nie ◽  
Hui Min Zhang ◽  
Jia Teng Niu
Keyword(s):  
Injection Molding ◽  
Orthogonal Experiment ◽  
Mold Temperature ◽  
Processing Parameters ◽  
Influential Factors ◽  
Injection Molding Process ◽  
Range Analysis ◽  
Molding Process ◽  
Melt Temperature ◽  
Plastic Parts

This article is using Moldflow analysis and orthogonal experimental method during the whole experiment. The injection molding process of motor cover is simulated under various technological conditions.After forming the maximum amount of warpage of plastic parts for evaluation.According to the range analysis of the comprehensive goal, the extent of the overall influence to the processing parameters, such as gate location, melt temperature, mold temperature and holding pressure is clarified.Through analyzing the diagrams of influential factors resulted from the simulation result,the optimized process parameter scheme is obtained and further verified by simulation.

scholarly journals ANALYSIS ON VOLUMETRIC SHRINKAGE OF PLASTIC FOOD CONTAINER MADE FROM AN INJECTION MOLDING PROCESS

2020 ◽  
Vol 8 (2) ◽  
pp. 22-31
Author(s):  
Rosidah Jaafar ◽  
◽  
Hambali Arep ◽  
Effendi Mohamad ◽  
Jeefferie Abd Razak ◽  
...  
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Food Packaging ◽  
Plastic Injection Molding ◽  
Volumetric Shrinkage ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Plastic Injection

The plastic injection molding process is one of the widely used of the manufacturing process to manufacture the plastic product with high productivity. Moreover, the food packaging manufacturing industry undergoes the trials and errors to obtain the optimal setting of the process parameters in order to minimize the quality issues and these trials and errors are time consuming and costly. The aim of this study is to improve the quality of the butter tub by minimizing the volumetric shrinkage. This study is to deal with the application of Moldflow integrating with the statistical technique to minimize the volumetric shrinkage the butter tub which depends on the process parameters of the plastic injection molding. For this purpose, the rectangular shape of butter tub is designed by utilizing the SolidWorks. Molflow is used to simulate the plastic filling of the single cavity mold of butter tub based on the Taguchi’s �!" orthogonal array table. In addition, the analysis of variance (ANOVA) is applied to investigate significant impact of the process parameters on the quality of the butter tub. Minitab is used to optimize the response of the volumetric shrinkage by selecting the most appropriate process parameters that maximizing the desirability value. Furthermore, the butter tub has a uniform thickness which was 1.2 mm and its factor of safety was 3.383 and the volumetric shrinkage response have optimized by 0.956 %. The melt temperature and mold temperature are found to be the most significant process parameters for the plastic injection molding process of butter tub and the volumetric shrinkage value obtained from the simulation is verified by the calculated volumetric shrinkage value.

scholarly journals Exploring the Trend of New Zealand Housing Prices to Support Sustainable Development

2019 ◽  
Author(s):  
Linlin Zhao ◽  
Jasper Mbachu ◽  
Zhansheng Liu
Keyword(s):  
New Zealand ◽  
Regression Model ◽  
House Prices ◽  
Linear Regression Analysis ◽  
Arima Model ◽  
Housing Prices ◽  
Multiple Linear Regression Analysis ◽  
Housing Sector ◽  
Forecasting Performance ◽  
Sample Method

The New Zealand housing sector is experiencing rapid growth that boosts the national economy but also results in the loss of valuable resources. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: ARIMA and multiple linear regression analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

scholarly journals PENGARUH TRUSTWORTHINESS, EXPERTISE DAN ATTRACTIVENESS CELEBRITY ENDORSER DI INSTAGRAM TERHADAP PURCHASE INTENTION PRODUK HIJAB (Studi Kasus pada Akun Instagram @gitasav)

JEMBATAN ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 13-30
Author(s):  
Syarifah Fatimah Dina Najib H.A ◽  
Islahuddin Daud ◽  
Aslamia Rosa
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Purchase Intention ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Analysis Technique ◽  
Celebrity Endorser

This study was aimed to examine the effects of trustworthiness, expertise, and attractiveness of celebrity endorser on Instagram to purchase intention of hijab products. The sampling technique was done by purposive sampling method. The population in this study was followers of the @gitasav Instagram account. Data was collected through distributing questionnaires to 100 respondents. The analysis technique used in this study is multiple linear regression analysis. The results showed that simultaneously the variables of trustworthiness, expertise, and attractiveness had a significant effect on purchase intention. However, partially the purchase intention variable is only influenced by the trustworthiness variable which is equal to 3,878. In this study a regression model was obtained, which is Y = 10,021 + 0,655X1 + 0,038X2 - 0,122X3. 

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