Property Optimization of Impeller Casting Using GRA (original) (raw)
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Journal of The Institution of Engineers (India): Series D, 2018
Ductile irons are important engineering materials because of its high strength to weight ratio and castability. The ductile iron castings are used widely for automobile applications due to their wide spectrum of property range. Weight reduction is important in automobile to improve its fuel efficiency which can be achieved by thinning down the casting sections without altering its functionality. Generally, automobile castings are having varying section thickness. Varying thickness castings offers different cooling rates while solidification of the casting. The solidification cooling rate decides the final microstructure of the cast components. Cooling rate was found to affect directly the amount of pearlite and ultimately the as cast properties in varying thickness ductile iron castings. In view of this, the automobile impeller casting is selected for study in the present work as it consists of varying section thickness in which small sections are connected to central hub. The casting solidification simulations were performed and analyzed. The solidification cooling rates were analyzed further to correlate the experimental processing parameters. The samples from poured castings were analyzed for microstructure and hardness at different section thickness. Multiple response optimization of microstructure and hardness was carried out by combined Taguchi and Grey Relational Analysis (GRA). Contribution of input variables on the output variables is attained using ANOVA.
Quality and yield improvement of ductile iron casting by simulation technique
Foundries contribute to production of major automotive parts. These foundries now a days suffering from poor quality and productivity due to different parameters of the casting process. Casting quality depends on the solidification process after pouring. Computerized casting modeling and solidification simulation is being extensively used by foundries to design the casting process for manufacturing of castings before castings are prepared or before equipment is constructed or improved. The basic objective of using computerized casting modeling and solidification simulation is to increase the quality of the casting manufactured, both in the existing produced casting and first ever castings made and to reduce cost expenses. The shop floor trials can be reduced effectively by casting solidification simulation and defect free castings can be assured. The casting simulation approaches are based on finite element method (FEM), finite difference method (FDM), finite volume method (FVM). In this paper an attempt has been made to use finite difference method (FDM) and finite volume method (FVM) for casting solidification simulation and optimization of casting gating system to assure maximal yield. Modeling and simulation of Flange is analyzed in this study. The material for the flange is ductile iron and produced using shell molding process. Ductile iron has wide range of mechanical properties suitable for production of automotive parts. The 3D model of flange and gating system is created using CATIA and it is simulated using Solid CAST and Auto CAST-X software's. The simulation software results will predict the location and level of shrinkage. Optimization of gating system will improve casting yield. This will suggest the modifications needed in gating system.
Quality Improvement of a Casting Process Using Design of Experiments
Prospectiva, 2016
In order to minimize the castings which do not meet the customer acceptance specifications, it is not only necessary to identify the process parameters related to the specific defects, but also it is necessary to identify the levels of these parameters to produce acceptable castings. This research study, was aimed to optimize the production of grey cast pump impellent castings using Response Surface Methodology (RSM) approach in a foundry producing grey cast iron components. Process factors like clay percentage, moisture percentage and mold hardness were found to be dominant factors for production process control. Three different levels of each factor were considered for experimentation. Statgraphics Centurion Statistical Software was used to analyze and optimize process parameters for further confirmatory experiments. Significant parameters were identified by means of an Analysis of Variance (ANOVA) test. Parameter optimal settings obtained, and validated from confirmatory experiments, produced a high per cent of defect free pump impeller castings. The research concluded that careful adjustment of process dominance parameters is necessary, since they have significant effects on quality improvement of castings produced.
Grey Relational Analysis of Thin Wall Ductile Iron Casting
2014
Development of thin wall ductile iron is essential to permit designers for energy consuming equipment to choose the most appropriate material based on material properties, and not solely on weight or density. This paper analyzes various significant process parameters of the casting process. An attempt has been made to develop thin wall casting in order to obtain good mechanical properties. In the present work, ductile iron castings with varying thickness from 2 to 6mm were cast with suitable casting design to assure accurate mold filling. The process parameters considered are: Chemical composition (% Cu variations), Pouring Temperature, Type of inoculants and section thickness. The effect of selected process parameters and its levels on the Tensile Strength, Vickers hardness and percentage Elongation and the subsequent optimal settings of the parameters have been accomplished using Taguchi’s parameter design approach. The result indicates that the selected process parameters signifi...
Improvements in Productivity and Quality for Ductile Iron Flange Castings Using Simulation Technique
Journal of Production and Industrial Engineering, 2022
An important element of the automobile manufacturing process involves the utilization of foundries. Today's foundries' quality and output are low because of variations in the casting process's many variables. The solidification procedure following pouring is crucial to the final quality of the casting. In order to plan the casting process for making castings before castings are produced or before new or better equipment is built, foundries are increasingly turning to computerized casting modelling and solidification simulation. With the use of computerized casting modelling and solidification simulation, manufacturers may improve the quality of their castings at a lower cost, without sacrificing quantity. As a result of casting solidification simulation, the number of trials performed on the shop floor may be cut significantly, and defectfree castings can be guaranteed. Finite element method (FEM), finite difference method (FDM), and finite volume method (FVM) are the theoretical basis of the casting simulation methods (FVM). In this study, we explore the application of the finite difference method (FDM) and the finite volume method (FVM) to simulate the solidification of a casting and to optimise the casting gating system for maximum yield. This research looks at how modelling and simulation can help improve our understanding of Flange. Flanges are made of ductile iron using a shell moulding method. Mechanically, ductile iron may be used to make a variety of vehicle components.
Quality Improvement of Ductile Iron Casting by Thermal Analysis
Solidification of ductile Iron is complex & often leads to shrinkage. Melt Chemistry of charge prepared is insufficient to explain the way ductile iron shrinkage occurs in castings. The variations in melting, holding, treating and inoculating processes during the manufacturing of ductile iron impacts ductile iron solidification. Experimental results of thermal analysis in the casting where changes in cooling curves explained metallurgical characteristics to quality (shrinkage) of castings. Thermal Analysis of castings reduces quality issues such as shrinkage. Thermal Analysis (TA) is recording, analyzing the data & then interpret on the basis of temperature variation with respect to time of cooling or heated material. In ductile iron castings, the cooling curve gets recorded while solidifying metal in a mold and further analysis of this data is done. Interpretation is done on the basis of belief that during solidification, different events occurring leave their mark on the shape of cooling curves. With the help of this theory, the quality problems especially sinking or shrinkage problems faced for this casting are resolved.
Review of Optimization Aspects for Casting Processes
2015
In today’s global competitive environment there is a need for the casting set ups and foundries to develop the components in short lead time. Defect free castings with minimum production cost have become the need of this indispensable industry. Rejection of casting is caused due to defective components. These defects depend on various process parameters which need to be improved using various methods in optimization. The IT industry with the help of manufacturing industry have developed various software packages which simulate the casting process which help to identify the parameters affecting the quality of castings. The simulated results can be used to predict the defects, optimize the factors and take corrective steps to minimise these defects. This paper provides comprehensive literature review about optimization aspects of casting process and shows shear necessity of investigation of the process parameters and process optimization.
The International Journal of Advanced Manufacturing Technology, 2018
This paper presents a new approach to analyze the quality of ductile iron castings through simulations and experiments. Standard tensile test specimens are considered as simple cast products for which a multi-cavity mold is designed, simulated, and optimized to minimize porosity using MAGMASoft. X-ray imaging, hardness measurement, and tensile testing are done for selected specimens produced using optimized mold design. Next, finite element simulation of tensile testing until fracture is done in ABAQUS using elastic-plastic material model and porous metal plasticity model. Simulation results for sound specimen are found to be in good agreement with the experimental results. Since mold design optimization is solely based on porosity minimization, no porosity is observed in the final mold design. However, if multi-criteria optimization of mold is done, the specimens may show some porosity which can be integrated in the developed finite element model of tensile testing. It is concluded that simulation-based mold design optimization can produce nearly defect-free castings and at the same time exhibit the similar mechanical properties as their sound counterparts produced with other manufacturing processes.
Optimizing the Mechanical Properties of Thin-Wall Ductile Iron Castings
2012
The use of Ductile Iron for light weight automotive components has been limited in the past by the capability of the foundries to produce as-cast, carbide free, thin wall (2-3 mm) parts. For almost a decade, the Ductile Iron industry has invested significant amounts of money and time to develop a technology that would allow the manufacture of such castings. A key parameter for the production of thin-wall casting is to control the nodule count in a range of 500-700 for which the mechanical properties and the microstructure are optimum. This is obtained by controlling the cooling rate of the parts and by optimizing the inoculation process. This paper presents the results of a study carried out in an experimental foundry in which the following parameters were studied: I) optimization of the addition of an insulating material to the mould to control the heat exchange at the mould/metal interface and then, the undercooling level to avoid carbide formation; ii) selection of the appropriate inoculation practice to control the nodule count in the selected range; iii) to determine a minimum silicon content required to optimize properties and cost.
ASSESSMENT ON MECHANICAL PROPERTIES OF DUCTILE CAST IRON BY FORMULATING EMPIRICAL EQUATIONS
TJPRC, 2014
In this work an attempt is made to assess the mechanical properties of SG iron by formulating empirical equations to determine the ingot diameter (solidification cooling rate) and vice versa for a given chemical composition. Five samples were produced by taking different ingot diameter to cover wide range of solidification cooling rate. The mechanical properties are noted. It was observed that, the mechanical properties such as Ultimate Tensile Strength and Yield Strength are decreasing as the ingot diameter is increasing. The % elongation is increases as the ingot diameter increases. It was also observed that the hardness value decreases as the ingot diameter increases. By using these relations an attempt is made to formulate empirical equations, which can give the desired ingot diameter (solidification cooling rate) for a given mechanical properties and vice versa. By applying these equations, the manufacturer can easily assess what should be ingot diameter to obtain the desired mechanical properties and vice versa. Hence the time required for the manufacturer to decide the manufacturing process parameters can be reduced.