Design analysis of a standard injection screw for plasticising polycarbonate resins

2016 ◽  
Vol 36 (5) ◽  
pp. 537-548 ◽  
Author(s):  
Ming-Shyan Huang
Keyword(s):  
Simulation Analysis ◽  
Melt Temperature ◽  
Factors Affecting ◽  
Control Factors ◽  
Screw Length ◽  
Plastic Injection Moulding ◽  
Screw Diameter ◽  
Grey Relational ◽  
Injection Screw ◽  
Simulation Programme

Abstract The industrial use of plastic injection moulding machines is widespread. However, few studies have examined the injection screw, which is one of the key components of moulding machines. Studies have demonstrated that a properly designed injection screw improves both the moulding quality and the production rate. Factors that affect the plasticisation properties of conventional standard reciprocating screws include the screw geometry, the screw operation settings, and the processed resins. An ideal standard reciprocating screw exhibits a high plasticising capacity and excellent melt temperature homogeneity; however, these properties typically conflict. Through simulation analysis, this study investigated the optimal design of a standard reciprocating injection screw used for plasticising polycarbonate resins. First, the Taguchi method was integrated with a commercial simulation programme to identify the key control factors affecting the plasticising rate of a screw and the temperature uniformity of the melt. Simulation results revealed that the screw diameter, rotation speed, metering channel depth, ratio of the screw length to the screw diameter, and compression ratio substantially influence performance. Consequently, grey relational analysis was adopted to optimise the design of an injection screw that ensures sufficient quality according to the plasticisation rate and the homogeneity of molten plastic.

Optimization of Reaming Process Parameters for Titanium Ti-6Al-4V Alloy Using Grey Relational Analysis

2016 ◽  
Author(s):  
Shakeel Ahmed L. ◽  
Pradeep Kumar M.
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Factors Affecting ◽  
Significant Control ◽  
Relational Analysis ◽  
Control Factors ◽  
Grey Relational

Reaming is one of the finishing processes that have been widely applied in manufacturing industries. Reaming of Titanium Ti-6Al-4V alloy material is an important and current research topic on manufacturing processes. Optimal process parameter setting is an important element in the machinability study of Titanium Ti-6Al-4V alloy. Optimization has most significant importance, particularly for reaming operations. This research work focuses on the multi-response optimization of reaming process parameters using the Taguchi and Grey relational technique to obtain minimum cutting temperature (T), thrust force (Ft), torque (Mt), surface roughness (Ra) and hole quality. The experiments were performed on Titanium Ti-6Al-4V alloy using uncoated carbide straight shank reamer under wet and cryogenic LN2 conditions. Eighteen experimental runs (L18) based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The environment, cutting speed and feed rate were selected as control factors. Grey relational analysis was used to determine the most significant control factors affecting the output parameters. Grey relational grade obtained from the grey relational analysis was used to solve the reaming process with the optimal levels of the multiple performance characteristics responses were established. The optimum results indicate that the reaming results have been improved in wet coolant than the cryogenic LN2 condition.

Application of the Taguchi method for consistent polymer melt production in injection moulding

1998 ◽  
Vol 212 (8) ◽  
pp. 611-620 ◽  
Author(s):  
N Khoshooee ◽  
P D Coates
Keyword(s):  
Injection Moulding ◽  
Polymer Melt ◽  
Acrylonitrile Butadiene Styrene ◽  
Melt Temperature ◽  
Factors Affecting ◽  
Moulding Process ◽  
Control Factors ◽  
Injection Moulding Process ◽  
Moulding Machine ◽  
Noise Factors

The consistency of polymer melt production in the injection-moulding process has been studied using a Taguchi design-of-experiment method for acrylonitrile butadiene styrene (ABS) and high-density polyethylene. Systematic experimentation with injection-moulding machine settings helped to establish both qualitative and quantitative process understanding in attempting to control the melt quality, assessed here by the shot weight variability. Optimum machine settings were determined which gave the lowest variations in the shot weight. In the case of ABS, uncontrollable influences (noise factors; here the injection stroke and moisture content) were incorporated in the study in such a way that the optimum levels recommended by the analysis make the process (i.e. shot weight) insensitive to variations caused by the noise factors. The set melt temperature and screw-back pressure were observed to be the most influential control factors affecting the shot weight variability for both polymers.

Improving the Strength of Abrasive Wheels and Optimizing the Control over the Strength of Composite Abrasive Materials

2019 ◽  
Vol 946 ◽  
pp. 380-385
Author(s):  
Boris A. Chaplygin ◽  
Viacheslav V. Shirokov ◽  
Tat'yana A. Lisovskaya ◽  
Roman A. Lisovskiy
Keyword(s):  
Mechanical Properties ◽  
Test Results ◽  
Key Factors ◽  
Special Equipment ◽  
Material Density ◽  
Factors Affecting ◽  
Control Factors ◽  
Reinforcing Material ◽  
Special Studies ◽  
First Time

The strength of abrasive wheels is one of the key factors affecting the performance of abrasive machining. The paper discusses ways to improve the strength of abrasive wheels. The stress-state mathematical model presented herein is a generalization of the existing models. It is used herein to find for the first time that there are numerous optimal combinations of the elastic modulus and reinforcing material density, which result in the same minimum value of the objective function. It is found out that increasing the radius of the reinforcing component while also optimizing the mechanical properties of its material may increase the permissible breaking speed of the wheel several times. We herein present a regression equation and a nomogram for finding the optimal combination of control factors. Conventional methods for testing the mechanical properties of materials, which have been proven reliable for testing metals and alloys, are not as reliable for testing abrasive materials, as the test results they generate are not sufficiently stable or accurate. We therefore propose an alternative method that does not require any special equipment or special studies.

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

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.

Experiment and Simulation Analysis of the Pressure Carrying Capacity of X80 Pipe with Metal Loss Defect on the Girth Weld

2021 ◽  
Vol 1035 ◽  
pp. 813-818
Author(s):  
Zheng Long Li ◽  
Lin Chen ◽  
Zhi Hong Li ◽  
Guo Shuai Yan ◽  
Wei Li
Keyword(s):  
Sensitivity Analysis ◽  
Carrying Capacity ◽  
Simulation Analysis ◽  
Water Pressure ◽  
Metal Loss ◽  
Factors Affecting ◽  
Element Simulation ◽  
Simulation Based ◽  
Blasting Test ◽  
Water Pressure Blasting

In order to study the pressure carrying capacity of X80 pipe with metal loss defect on the girth weld the water-pressure blasting test of the pipe with metal loss defect was analyzed by experiment and finite element simulation. Based on this, the sensitivity analysis of the factors affecting the pressure carrying of the pipeline, such as the circular size, the axial size, and the depth of the metal loss defect, was carried out. The research results show that the circular size of the metal loss defect on the girth weld had little impact to the pressure carrying capacity of the pipe while it reduced with the increasing of the axial size and the depth of the metal loss defect.

Preparation and Application of Biochars for Organic and Microbial Control in Wastewater Treatment Regimes

2019 ◽  
pp. 19-34 ◽  
Author(s):  
Victor Odhiambo Shikuku ◽  
Wilfrida N. Nyairo ◽  
Chrispin O. Kowenje
Keyword(s):  
Organic Pollutants ◽  
Organic Contaminants ◽  
Activated Carbons ◽  
Low Cost ◽  
Microbial Control ◽  
Chemical Compositions ◽  
Preparation Methods ◽  
Factors Affecting ◽  
Surface Areas ◽  
Control Factors

Biochars have been extensively applied in soil remediation, carbon sequestration, and in climate change mitigation. However, in recent years, there has been a significant increase in biochar research in water treatment due to their stupendous adsorptive properties for various contaminants. This is attributed to their large surface areas, pore structures, chemical compositions, and low capital costs involved making them suitable candidates for replacing activated carbons. This chapter discusses the preparation methods and properties of biochars and their removal efficacy for organic contaminants and microbial control. Factors affecting adsorption and the mechanisms of adsorption of organic pollutants on biochars are also concisely discussed. Biochars present environmentally benign and low-cost adsorbents for removal of both organic pollutants and microbial control for wastewater purification systems.

Simulation of Skulduggery in a Multi-Agent System

2015 ◽  
Vol 7 (1) ◽  
pp. 17-31
Author(s):  
Rasoul Ramezanian ◽  
Akram Emdadi
Keyword(s):  
Utility Function ◽  
Test Session ◽  
Testing Session ◽  
Multi Agent System ◽  
Agent System ◽  
Factors Affecting ◽  
Artificial Society ◽  
Control Factors ◽  
Multi Agent ◽  
Level Of Knowledge

In a testing session, students may want to use the information of other students, which is cheating. The authors of this paper develop an artificial society to model and simulate this situation. They consider two control factors to increase the incentive of students to not cheat. The first factor is the penalty for similarity between responses (as much as two answer-sheets of two students are the same, their final grades decrease). The second factor is the observers who look into the students and do not allow the observed students to cheat. In this model, agents participate in a test based on their level of knowledge, location and two above factors, deciding whether or not to cheat. These components are used to formulate the utility function. Taking advantage of the developed artificial society, the authors now study the above factors affecting the amount of cheating in a test session.

Simulation Analysis of the Pressure Carrying Capacity of X80 Pipe with Plain Dents

2019 ◽  
Vol 944 ◽  
pp. 835-840
Author(s):  
Peng Song ◽  
Zheng Long Li ◽  
Yu Ran Fan ◽  
Lei Guo ◽  
Xi Xi Zhang ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Internal Pressure ◽  
Carrying Capacity ◽  
Formation Process ◽  
Simulation Analysis ◽  
Hydraulic Test ◽  
Factors Affecting ◽  
Element Simulation ◽  
Simulation Based

In order to study the pressure carrying capacity of X80 pipe with plain dents, the formation process and the hydraulic test were analyzed by finite element simulation. Based on this, the sensitivity analysis of the factors affecting the pressure carrying capacity of the pipeline, such as the internal pressure, the confinement state and the material performance, is carried out. Research results show that springback amount of the pipeline decreases due to the initial internal pressure, and constraint state has little effect on the pressure carrying capacity while increases with the increasing of the material tensile properties. When the depth of the dent is less than 6% pipe diameter or the strain of the dent is less than 6%, the dent has little impact to the pressure carrying capacity of the pipe.

scholarly journals Multiobjective Optimization of Injection Moulding Process Parameters on Mechanical Properties Using Taguchi Method and Grey Relational Analysis

2018 ◽  
Vol 7 (3.7) ◽  
pp. 14 ◽  
Author(s):  
Mohd Amran Md Ali ◽  
Noorfa Idayu ◽  
Raja Izamshah ◽  
Mohd Shahir Kasim ◽  
Mohd Shukor Salleh ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Injection Moulding ◽  
Cooling Time ◽  
Mould Temperature ◽  
Plastic Part ◽  
Melt Temperature ◽  
Relational Analysis ◽  
Grey Relational

This study presents an optimization of injection moulding parameters on mechanical properties of plastic part using Taguchi method and Grey Relational Analysis (GRA) approach. The orthogonal array with L9 was used as the experimental design. Grey relational analysis for ultimate tensile strength, modulus and percentage of elongation from the Taguchi method can convert optimization of the multiple performance characteristics into optimization of a single performance characteristic called the grey relational grade (GRG). It is found that mould temperature of 62oC, melt temperature of 280oC, injection time of 0.70s and cooling time 15.4s are found as the optimum process setting. Furthermore, ANOVA result shows that the cooling time is the most influenced factor that affects the mechanical properties of plastic part followed by mould temperature and melt temperature.  

Sign in / Sign up

Export Citation Format

Share Document