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Casting process design is crucial in manufacturing; however, traditional design workflows are time-consuming and seriously reliant on the experience and expertise of designers. To overcome these challenges, database technology has emerged as a promising solution to optimize the design process and enhance efficiency. However, conventional database storing process cases often lack adequate parametric information, limiting their ability to support intelligent and automated design. Thus, this study has developed a casting process database based on parametric case modeling, enabling the rapid design of casting processes for new parts using case-based reasoning (CBR). The database framework was designed to organize process cases into four distinct information modules, allowing for structured and separated storage. Data unit associations were established between these modules to ensure the completeness and scalability of process information. The database stores sufficient parametric information to describe key process characteristics and multidimensional elements. This includes the detailed structural parameters of parts, calculated based on the accurate analysis of their structural features. A process cost estimation model was incorporated to calculate and record direct process costs, enabling the effective comparison and ranking of various process plans for the same part. Additionally, the parametric model of the gating system is stored to support the transfer of processes between similar parts. The functionality and effectiveness of the proposed database were visually validated through a case study on the process design of an actual casting part. The results indicate that the database significantly improves efficiency and ensures the accuracy of CBR-based process design while optimizing the reuse of design knowledge and expertise. The developed database achieved a 90% reduction in design time compared to conventional methods.

Additive manufacturing (AM) is accepted as a transformative technology for rapid production of parts based on digital models through direct printing of a range of materials (e.g., metals, polymers, and ceramics). Recent advancements in the binder-jetting AM process (i.e., 3D sand-printing (3DSP)) enables direct production of sand molds and cores for metal casting. AM has been attractive to manufacturers due to the ability to produce complex and customized parts in low batch production. Traditional mold design for gravity castings experience higher scrap rates due to challenges in controlling turbulence and air entrapment. In this research, mathematically designed sprue geometries that can be produced via 3DSP are presented along with their effect on mechanical and metallurgical properties of castings through numerical modeling, computational simulation, and experimental validation. The casting properties are contrasted to conventional straight sprue castings for two different alloys: aluminum alloy 319 and gray cast iron class 30. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), computed tomography scanning (CT), and 3-point bending tests are performed to characterize microstructure, casting defects, elemental composition, and mechanical properties for castings of each gating system design. For aluminum alloy 319, a statistically significant increase of 10% in flexural strength was found using the conical-helix sprue geometry as well as a reduction of 25% in casting defects. In gray cast iron class 30, no statistically significant differences are found between the flexural strength of the conical-helix and benchmark straight sprue as expected in a short freezing range alloy.

For the flat plastic parts with the size range of 200 to 1300 mm, the structural parameters decision model of injection mold gating system is established in this paper. Firstly, the relationship between the warpage and the structural parameters of gating system is fitted by Kriging model, and the minimum warpage is optimized by genetic algorithm (GA) to obtain the best structural parameters. Secondly, the best structural parameters of gating system corresponding to 16 groups of plastic parts are taken as samples, and the relationship between the structural parameters of gating system and the size parameters of plastic parts is established by Kriging model. In addition, K-means is used to reduce the number of the structural parameters of gating system from 5 to 2, in order to improve the accuracy of decision model. Finally, the size parameters of plastic parts are input to the decision model to obtain the structural parameters of gating system. Through the verification of mold flow analysis experiment, the structural parameters of gating system obtained by this method meet the design requirements and can effectively shorten the structural design cycle of injection mold.

Distribution of gasses to the cast volume and volume of pores can be maintained within the acceptable limits by means of correct setting of technological parameters of casting and by selection of suitable structure and gating system arrangement. The main idea of this paper solves the issue of suitability of die casting adjustment—i.e., change of technological parameters or change of structural solution of the gating system—with regards to inner soundness of casts produced in die casting process. Parameters which were compared included height of a gate and velocity of a piston. The melt velocity in the gate was used as a correlating factor between the gate height and piston velocity. The evaluated parameter was gas entrapment in the cast at the end of the filling phase of die casting cycle and at the same time percentage of porosity in the samples taken from the main runner. On the basis of the performed experiments it was proved that the change of technological parameters, particularly of pressing velocity of the piston, directly influences distribution of gasses to the cast volume.

The resulting quality of castings indicates the correlation of the design of the mold inlet system and the setting of technological parameters of casting. In this study, the influence of design solutions of the inlet system in a pressure mold on the properties of Al-Si castings was analyzed by computer modelling and subsequently verified experimentally. In the process of computer simulation, the design solutions of the inlet system, the mode of filling the mold depending on the formation of the casting and the homogeneity of the casting represented by the formation of shrinkages were assessed. In the experimental part, homogeneity was monitored by X-ray analysis by evaluating the integrity of the casting and the presence of pores. Mechanical properties such as permanent deformation and surface hardness of castings were determined experimentally, depending on the height of the inlet notch. The height of the inlet notch has been shown to be a key factor, significantly influencing the properties of the die-cast parts and influencing the speed and filling mode of the mold cavity. At the same time, a significant correlation between porosity and mechanical properties of castings is demonstrated. With the increasing share of porosity, the values of permanent deformation of castings increased. It is shown that the surface hardness of castings does not depend on the integrity of the castings but on the degree of subcooling of the melt in contact with the mold and the formation of a fine-grained structure in the peripheral zones of the casting.

The research presented in this paper aimed to change the existing gating system that would enable the engine body casting, from a new EV31A magnesium alloy, of the required quality. For this reason, the casting process simulations used the MAGMASoft software, followed by the experimental validation of the achieved results. The results achieved in the first stage of the cast computer simulation enabled the identification of potential problems and factors that reduce the casting quality. However, the proposed design modifications eliminated the inadequate delivery of liquid metal to the casting’s critical areas by adequately controlling the mold cavity filling and solidification process. The experiment validated the simulations of the computer casting defects at the various stages. The results enabled the new EV31A magnesium alloy to be implemented in industrial production.

The filling stage is a critical phenomenon in sand casting for making reliable castings. Latest research has demonstrated that for most liquid engineering alloys, the critical meniscus velocity of the melt at the ingate is in the range of 0.4–0.6 m s−1. The work described in this research paper is to use neural network (NN) technology to propose digital twin approach for gating system design that allow to understand and model its performances faster and more reliable than traditional methods. This approach was applied in the case of sand casting of liquid aluminum alloy (EN AC-44200). The approach is based first on a digital representation of filling process to perform the melt flow simulations using a combination of the gating system design parameters, selected as a training cases from Taguchi orthogonal array (OA). The second step of the approach is the data capture of functional gating design system to train up the feed-forward back-propagation NN model. The validation of the well-trained NN model is assessed by interrogating predicted ingate velocity to it and making reliable predictions with high accuracy. The claim is that such digital twin approach is an effective solution to recognize the functional design parameters from the entire filling systems used during casting process.

Current practices in the industry require significant involvement of die-casting experts who have to consider industry best practices and knowledge of process physics besides reference to a number of databases is also required making it very time consuming and cumbersome exercise. The die-casting industry therefore requires a system that could help relieve the die-casting expert from manual and time consuming tasks to design a good gating system. A computer-aided system for multi-gate gating system design for die-casting die is presented in this paper. The working of the system is supported by part, process, machine, and material information which is called input information. The system works in three major steps called modules of the system. The first module deals with the determination of die-casting process parameters. This module helps the user in determination of cavity fill time, gate velocity, and selection of die-casting machine automatically from the input information. The second module deals with the computer-aided determination of gating system parameters like gate thickness, gate length, runner length etc., by using input information. The last module of the system uses the parameters obtained from the second module to generate CAD models of the gating system by updating gating system features from feature library. The system was implemented in MATLAB. The proposed system is capable of designing gating system for die-casting parts requiring multiple gates. The system has been tested on example die-casting parts, and the results obtained from the system are as per industry practice.

Quality properties of castings produced in a die casting process correlate with porosity that is conditioned by a number of factors, which range from input melt quality to setup of technological factors of the die casting, and through structural design of the gating system. One of the primary parameters conditioning the inner soundness of the casting is the liquid metal dose per single operation of die casting. This paper examines the issue of metal dose. The experiments are performed with casting a gate system of an electromotor flange. The gating system examined was die cast with a variable volume of metal dose per single operation. The metal dose was adjusted to reach the height of a biscuit of 10, 20, and 30 mm. The examination of the inner homogeneity of the castings of the individual variants of gating systems with variable height of the biscuit proved that decreasing biscuit height results in an increase of porosity share in the casting volume. The programme MagmaSoft 5.4 revealed the main causes of changes in porosity share. The simulations detected that the change in biscuit height and volume of liquid metal directly influence thermal conditions of the melt in the filling chamber, and in the mould by means of the period in which the holding pressure action is influenced. Simultaneously, the melt flow mode in the sprues and gas entrapment in the melt volume are affected as well. Correlation of the factors consequently influences the final porosity of castings.

This study presents a novel hybrid simulation-optimization framework to minimize defects in sand castings of aluminum A356 alloy for textile machinery components. The methodology integrates Finite Element Method (FEM) simulations in ProCAST with the Taguchi method and a Chaotic Binary Quantum Particle Swarm Optimization (CBQPSO) algorithm to systematically design the gating system. The Taguchi method efficiently screened initial parameters, which were then optimized globally by the CBQPSO algorithm using FEM-derived defect metrics. A response surface methodology (RSM) model validated the results and provided a predictive tool. Applied to a case study at Bahirdar Textile Foundry, the approach yielded an optimized gating design with a tapered sprue, dual runners, and four ingates. This design achieved substantial improvements: a 68.14% reduction in filling time, a 50.56% decrease in solidification time, and a 20.20% lower oxide ratio. FEM analysis confirmed enhanced thermal balance, superior directional solidification, reduced shrinkage porosity, and more stable flow dynamics. The research demonstrates the efficacy of integrating FEM with intelligent algorithms for multi-objective casting optimization, offering a robust, data-driven pathway for high-integrity castings that contributes to the digital automation and sustainable goals of Industry 4.0 in foundry operations.