Metal Casting Process Research Articles

Data Models for Casting Processes – Performances, Validations and Challenges

Abstract Data-driven models with their associated data learning and training schemes can be utilised for the light metal casting processes. This paper presents the basis of data model building processes along with data training and learning exercises for vertical direct chill casting and high pressure die casting (HPDC) applications. The concepts of efficient database building, data translations and sampling, as well as real-time model building and validations are briefly discussed. Rigorous performance studies were additionally carried out for two real-world case studies. Different combinations of data solvers and interpolators are adapted for the model building techniques, while machine learning schemes are used for data trainings.

A GPU based accelerated solver for simulation of heat transfer during metal casting process

The metal casting process, which is one of the key drivers of the manufacturing industry, involves several physical phenomena occurring simultaneously like fluid flow, phase change, and heat transfer which affect the casting yield and quality. Casting process modeling involves numerical modeling of these phenomena on a computer. In recent decades, this has become an inevitable tool for foundry engineers to make defect-free castings. To expedite computational time graphics processing units (GPUs) are being increasingly used in the numerical modeling of heat transfer and fluid flow. Initially, in this work a CPU based implicit solver code is developed for solving the 3D unsteady energy equation including phase change numerically using finite volume method which predicts the thermal profile during solidification in the metal casting process in a completely filled mold. To address the computational bottleneck, which is identified as the linear algebraic solver based on the bi-conjugate gradient stabilized method, a GPU-based code is developed using Compute Unified Device Architecture toolkit and was implemented on the GPU. The CPU and GPU based codes are then validated against a commercial casting simulation code FLOW-3D CAST® for a simple casting part and against in-house experimental results for gravity die casting of a simple geometry. Parallel performance is analyzed for grid sizes ranging from 10 × 10 × 10 to 210 × 210 × 210 and for three time-step sizes. The performance of the GPU code based on occupancy and throughput is also investigated. The GPU code exhibits a maximum speedup of 308× compared to the CPU code for a grid size of 210 × 210 × 210 and a time-step size of 2 s.

ANALISA KEKUATAN TARIK PADA HASIL PROSES PENGECORAN NOZZLE UNTUK BRAKE COUPLING MENGGUNAKAN METODE CETAKAN PASIR JOLT SQUEEZE

Sand casting is one of the metal casting methods that has been developed and is still being improved. Sand casting is a type of metal casting that use sand molds. There are several ways to make sand casting, However, this study use the jolt squeeze technique to create complex product forms such as the nozzle component of the air brake coupling. FCD 500 nodular cast iron alloy castings are used in the production of brake coupling nozzles. The goal of this research focuses on the metal casting technique for nozzle products for brake coupling, and then continue with the tensile testing procedure. Tensile testing utilizing JIS Z 2201 standards with two sampels with different diameters, specifically 12,46 mm and 12,79 mm, and material types FCD 500-1 and FCD 500-2. The research results show the sequence of the nozzle metal casting process for brake couplings, through the stages of designing, constructing models and cores, making molds, melting, pouring, fettling and finishing, and quality control. Tensile stress values of 525 N/mm2 and 546,189 N/mm2 were obtained for each FCD 500-1 and FCD 500-2 sampels, with force loads of 64000 N and 70130,66 N, respectively.

Quality circle implementation to reduce defects in cast steel products in the heavy equipment industry

Steel products produced from the metal casting process or commonly called cast steel are still very much needed in the industrial world, as components for production machines, power plants, automotives, heavy equipment and other needs. PT KX is a company that produces cast steel products, the products produced are targeted to be able to meet customer needs both for domestic needs and for export needs abroad. One of the problems currently faced by this company is the high defect ratio in several products currently produced. The defects that occur are porosity, gas holes, sand inclusions, cracks, and misruns. This company's good culture in implementing continuous improvement is well developed in all lines and all members of the organization so that this company continuously makes efforts to reduce defects that occur in products. The aim of this research is to analyze the causes of problems and make improvements to reduce the defect ratio. The method used by Quality Circle (QC) is as a method for making continuous improvements in reducing defects. One of the ways in which the verification process is carried out is by utilizing Electron Probe Micro Analyzer (EPMA) machine technology. This aims to make the analysis results more in-depth so that ultimately the defects that occur in a product can be reduced significantly.

Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings

Shrinkage porosity poses a significant challenge in metal casting processes, impacting both productivity and energy efficiency, especially when dealing with components that are not accepted or reprocessed. Addressing this issue requires proactive measures, and predictive techniques play a crucial role in minimizing its occurrence. Among these methods, the Criterion Function stands out as a valuable empirical model extensively explored in the literature. By intricately linking solidification processes to the development of shrinkage porosity, the Criterion Function leverages key process parameters, including thermal gradient, molten metal velocity during solidification, and cooling rate, to offer predictive insights into the location and presence of porosity. However, a criterion function is needed that also considers the effect of geometric variations as well as the size of the defect (shrinkage porosity). In this study, a casting with three T-joints was taken as a benchmark shape to develop a geometry-based quantitative prediction model for plain carbon steel castings. Real experimental results were combined with solidification simulation results to produce reliable data, which were then used to extrapolate the results. The developed quantitative prediction model, which includes the effect of geometric changes, has been validated and proven effective in predicting shrinkage porosity.

Process control and energy saving in the ladle stage of a metal casting process through physics-based and ANN-based modelling approaches

The process and temperature control of metal casting applications is of utmost importance both to guarantee the good quality of the final product and also to pursue an energy saving policy. For this purpose, in this paper two different modelling approaches have been proposed to predict the liquid steel temperature inside a ladle for metal casting, shortly before the casting process. The first is a physics-based grey-box model relying on equations for the characterization of the heat transfer mechanisms inside the ladle structure, whereas the second approach relies on artificial neural networks (ANNs). Both methods have been calibrated with experimental data of a case study plant, and subsequently assessed and compared in terms of prediction accuracy. Results show that the physics-based approach is able to predict the casting temperature with a higher mean absolute error (MAE) of 14 °C, whereas the ANNs predictions result to be better, with MAEs around 6 °C. On the other hand, it has been demonstrated that the ANNs approach may lack of reliability, especially if input data strongly differ from the calibration dataset, whereas the physics-based approach results to be more consistent and trustworthy. Finally, an energy analysis is conducted to demonstrate the feasibility of the model in evaluating the potential energy saving compared with situations in which decisions are taken by operators without the aid of a model predictive control.

Analysis of gaseous emission and particle number size distributions in metal casting processes with binder jetting moulds

The impact on indoor air quality during metal casting processes using the 3D printing (3DP) binder jetting technique to manufacture moulds is analyzed in this research. This study investigates the particle size distribution and gas concentration during the manufacturing stages of 3DP moulds, with focus on particle deposition in the human respiratory system. The goal is to understand the risks associated with particle and gas emissions in binder jetting 3D printing, and thus improve worker safety. The results indicate that particle emission rates are lowest during printing (0.01 1011particles min−1) but increase during post-processing and melting-pouring phases (3.07 1011 particles min−1). During melting and pouring, the emission of particles was mainly in the range 7.9–71 nm, with values 10 times higher than in the previous phases. The study calculates the deposition of inhaled particles in different parts of the respiratory tract and reveals a 2.39 times higher extrathoracic mass deposition during 3DP mould manufacturing stages compared to melting-pouring stages. Additionally, alveolar mass deposition is higher during melting-pouring stages due to an increase in ultrafine emission rates. The study emphasizes the importance of insulation equipment and workplace ventilation in indoor spaces, particularly during heating processes that generate ultrafine particles through nucleation, so that health risks can be mitigated.

Preliminary Study on the Potential of Krueng Mane River Sand for Metal Casting Use

Sand casting is a metal casting process to make a component by pouring molten metal into the sand mold. The casting process, the sand is the fundamental material used for mold making. The sand used is generally silica sand, river sand, mountain sand, and beach sand. The sand for molding must have requirements such as having formability, suitable permeability, good distribution of sand grain size, resistance to high temperatures, suitable binder composition, and sand must be cheap. This study investigated to determine the potential of Krueng Mane river sand in Aceh Indonesia for its possible use for metal casting. The important properties studied are moisture content, total clay content, grain fineness number, and grain shape. Tests are carried out following the standards and procedures defined by the American Foundrymen’s Society (AFS). Results obtained revealed that the river sand has average moisture content of 7.78 %, clay content of 3.20%, and grain fineness number (GFN) of 46. Krueng Mane river sand will be suitable for casting of casting of light steel, heavy grey steel, medium grey iron, and non-ferrous metals, with the addition of binding agent in suitable proportion.

Influence of partial replacement of calcined red clay by gypsum-bonded casting investment waste on geopolymerization reaction of red clay-based geopolymer

The main objective of this research is to study the influence of partial replacement of calcined red clay by gypsum-bonded casting investment waste (GCIW) from precious metal casting process on geopolymerization reaction of a red clay-based geopolymer. Calcined red clay was partially replaced by GCIW powder with different contents before mixing with sodium-based alkali activator solution to produce the geopolymers. The results indicate that the GCIW significantly impacted the reaction of flesh geopolymers detected by Differential scanning calorimetry (DSC). The reaction products (hydration products and others) of 28-day geopolymers detected by Fourier transform Infrared spectroscopy (FTIR) and X-ray diffractometry (XRD) were employed to support the reaction results. Moreover, the relation between reaction products and compressive strength was discussed. This work concluded that the calcium sulfate compounds contained in GCIW play an important role on geopolymerization reaction, reaction products, and mechanical properties of geopolymer. Furthermore, the results could be employed to propose a reaction mechanism that occurred in geopolymers. The potential use of GCIW as an additive for red clay-based geopolymer bricks preparation was confirmed in this research.

Lost Wax Casting

The lost wax production process is an intermediate step in converting a design idea that has been 3D printed from Polylactic Acid (PLA) plastic into a functional part via metal casting processes. This work offers an experimental assessment of the benefits accompanied by the lost-wax method, from both energy and economic-related aspects. The methodology of this work is represented by a sequence of steps that involve converting a 3D modeled and printed part (an investment casting tree), into a metal part, which in this case is made out of Aluminum. Aluminum was obtained from recycled products (i.e., beverage cans). The first couple of steps revolve around obtaining a 3D printed part of the desired 3D model, that can be created using a multitude of readily available Computer Aided Design (CAD) software. The 3D printed part is then utilized to create a plaster mold, which is followed by a firing step to get rid of the temporal 3D printed part to leave room for the casting metal. An energy assessment was carried out to compare the lost wax method and conventional machining (i.e., computer numerical control (CNC) machining). It was shown that to obtain the exact same functional part using the lost wax method, 12.124 kWh of energy is required, versus that of 17.297 kWh for CNC machining. Moreover, normalized costs of 0.067$/g and 0.096$/g were attributed to the lost wax and CNC machining, respectively, showing an almost 70% reduction in price when opting for the lost wax method.

Analisis Pengendalian Risiko Keselamatan dan Kesehatan Kerja (K3) dengan Metode Failure Mode and Effect Analysis (FMEA) pada PT. ABC

PT. ABC is engaged in metal casting such as drinking water pipe connections and quality drainage components. Existing manufacturing processes involve direct interaction of workers with equipment in production situations that have sufficiently high safety risks. The research aims to identify the type or source of hazard, determine the value of high risk, and appropriate risk control measures. Using the Failure Mode and Effect Analysis (FMEA) method to identify failures from facilities, systems or equipment that have an impact on work accidents. The results of the study found 48 hazards with identifying the risk of work accidents with categories are very low (7), low (48), medium (17), high (10) and there is no risk of work accidents with very high categories. Work accidents that have a high risk in the metal casting process at PT. ABC is at the die-making, smelting and pouring, roughing, and finishing work stations. Potential risks to work safety include dust from mixing, being crushed by solid iron, exposed to sparks, exposed to molten liquids, electrocuted, and exposed to odors from paint. Risk control measures are proposed in the metal casting process at PT. ABC is carried out with engineering control and the use of PPE according to the source of danger.

Investigating the Effect of Pouring Temperature Variations on Casting Defects of Making Camshaft Covers for Yamaha Jupiter Motorcycles Using Sand Casting Method

Casting using the sand-casting method is one of several methods in the metal casting process. The pouring temperature in the casting process is critical because it affects the casting results. This study aims to determine the effect of variations in pouring temperature on porosity defects in used aluminum metal castings and the impact of variations in pouring temperature on casting defects. The aluminum is melted and poured into the molds used are clay molds; In general, the mold is divided into two parts, namely the top (cup) and the bottom (drag), so that after the mold is finished, the melted aluminum is poured into the mold with variations in pouring temperature of 660˚C, 690C, and 720˚C. The method used is the observation method which is done by direct observation of the object of research. From the analysis of porosity defects data, the higher the casting temperature, the lower the porosity defects; a temperature of 660 C with a percentage value of 36.8%, a temperature of 690 C with a percentage value of 34.8%, and a temperature of 720˚C with a percentage value of 34.5%. This shows that casting temperature affects casting defects and porosity.

CALPHAD Optimization of the Composition of EN AC-46000 Secondary Alloys for Semi-Solid Casting Processes

In semi-solid metal casting processes a slurry, obtained operating in the temperature window between the liquidus and the solidus curve of the phase diagram of the alloy (32.7 °C for AlSi8, 11.3 °C for AlSi11), is injected into the mould. Since the control over the process parameters becomes more complicated as the involved quantities increase, to apply these processes on an industrial scale it is necessary to widen as much as possible this narrow temperature window. This goal can be obtained by tailoring the concentration of elements constituting the alloy. A EN AC-46000 secondary alloy was selected for this study, because of its wide use in foundries. Using a CALPHAD approach, various Al-Si-based pseudo-binary phase diagrams containing main constituents of the alloy (Cu, Zn, Fe, Mg, Mn, Ni, Cr and Ti) were studied, keeping the Si content fixed from 8 to 11 wt.% and the Al content as a complement. The composition limits of acceptability of the commercial alloy EN AC-46000 were used as extremes of the simulation field. The study was then proceeded investigating the pseudo-ternary diagrams, keeping silicon and a second element fixed and a third element variable for all possible combinations. Further constituent elements of the alloy were progressively added, considering all main constituents of the alloy, and evaluating how the concentration of these elements can extend the temperature window. Mg, Fe, Mn and Ti are the most promising candidates for achieving this goal. The results of this study can provide foundries with a prediction tool to define more restrictive ranges of acceptability than those of the commercial alloy, allowing them to estimate through a simple chemical analysis whether scrap of variable composition entering the plant are suitable for the SSM process or they need preliminary corrections of composition.

Computational studies of impurity migration during induction stirring of molten uranium

Understanding and controlling impurity behavior in actinide metal casting processes are foundational for efficient part production yet remain major challenges for researchers and industry. To help provide insight regarding impurity distribution during actinide metal casting, we have developed computational fluid dynamics (CFD) models for a laboratory-scale system using commercial and open-source codes. This article describes multiple experiment-informed models designed to simulate a specific laboratory system in which uranium melt, containing a known starting concentration of carbon impurity, is electromagnetically stirred in an induction furnace. The goal of the simulations is to predict the motion of impurity particles in the form of uranium monocarbide in the velocity field of the melt. Prior to simulating the uranium–carbon system, numerical models were validated using a previously published nonradioactive experimental system. Effects of the size and shape of impurity particles in the models were investigated and agree with experimental findings. Simulation of smaller particles (less than 50 μm) shows more homogenous distribution throughout the stirred melt. With increased particle size (100 μm), the body forces, which include the buoyancy force, dominate over the drag force, causing larger particles to move toward the crucible walls and upward in the system.

PROSES PENGECORAN ADAPTOR PADA BUCKET TEETH UNTUK EXCAVATOR DENGAN MENGGUNAKAN METODE PEMBUATAN CETAKAN FURAN

The following paper was made to understand the process, and defects from metal casting of Low Carbon Steel GS-25 CrMo 4 Bucket Teeth Adaptor for Excavator with furan molding method and how the results of the Chill Test on the product. Metal casting process of making objects by melting metal and pouring it into a mold cavity. Metal casting has been discovered and continues to be developed, one of which is Sand Casting, where there are various types of methods in making molds including the Furan, Disamatic, and Jolt Squeeze methods. The method used in this research is the Furan method which can be used to make objects with complex shapes such as the Adaptor component used in the Bucket Teeth for Excavators. The casting material used in this casting is GS-25 CrMo 4 steel which has strong and tough properties. All manufacturing processes are carried out through several stages, namely; design, model and core making, mold making, smelting, pouring, fettling and finishing, and quality control. From the results of the research that has been carried out, it can be seen that several rejections from these products include: cold shut, missrun, inoculant inclusion, slag inclusion, and sand inclusion.

Thermoelectric Generator Design and Characterization for Industrial Pipe Waste Heat Recovery

Thermoelectric technology is an effective strategy to convert low–grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels of heat and wide distribution, yet there is limited research on TEGs for use in these pipes. The challenge in designing a TEG lies in the heat collector, which is complicated by the distinct structural differences between pipe and plate–shaped TEMs. Ultimately, we propose an arch bridge–shaped heat collector for the pipe to recover wasted thermal energy. The effects of some key factors, such as topology of TEMs, heat source temperature, cooling water temperature and velocity, on the generating performance are studied. The TEG achieved a temperature difference of 65.98 °C across the two ends of the TEM, resulting in an output power of 17.89 W at an open–circuit voltage of 133.35 V. This provides evidence that the designed heat collector is a feasible solution for recovering waste heat from pipes using TEG technology. This work provides reliable experimental data and efficient design for the application of TEGs in industrial pipes.

Artifacts from the Perspective of Effutu Masquerade Performance: An Aesthetic Album

Artifacts from the Perspective of Effutu Masquerade Performance: An Aesthetic Album

Experience of designing and implementing integrated system of technological preparation of productionfor manufacturing new aircraft engines

The technological preparation of production (TPV) is one of the key stages of the product life cycle (LPL) when designing and developing new aircraft engines. The TPV system foresees the use of the following instruments: CAD/CAM/CAE systems to ensure the implementation of the following operations: automated design, production and engineering calculations; Product Data Management systems (PDM) to ensure product data management; Enterprise resource planning (ERP) systems for the corporate resource planning. Note that the instruments above are combined into PLM-systems to provide information support for the TPV system. The paper reviews the experience of designing and implementing the integrated TPV system at Motor Sich JSC for the purpose of manufacturing new aircraft engines. The author presents a structural diagram of the implemented integrated system containing a complex of interdependent subsystems along with a description of the system of automated design of process documents, which provides for the on-line design of production processes. The paper gives a description of subsystem of automated preparation of programs for CNC machine tools, which is designed to calculate the trajectory of the cutting tool when machining geometrically complex parts of aircraft engines. The paper specifies the subsystem of automated design of technological equipment, which is in compliance with requirements for modern tool production. The author underlines that the system of automated design of production equipment saw the following design subsystems reaching the highest level of development: subsystems for designing cutting and gear machining tools; subsystems for designing machine tools; subsystems for designing the monitoring and metering instrument; subsystems for designing foundry and stamping equipment; subsystems for designing control of gear cutting tools as per electronic standards. It is noted that the automated subsystems of analyzing production processes allow for performing the following analyses: analyzing metal casting processes; analyzing stamping processes; analyzing cutting processes; analyzing gear-cutting processes. The author provides the following results of implementing the integrated system of technological preparation of production at Motor Sich JSC: i) The TPV period was increased by 1.2–1.5 times, and ii) The efficiency of design and construction works was raised by 3–3.5 times.

Hyper Parameter Optimization for Transfer Learning of ShuffleNetV2 with Edge Computing for Casting Defect Detection

A casting defect is an expendable abnormality and the most undesirable thing in the metal casting process. In Casting Defect Detection, deep learning based on Convolution Neural Network (CNN) models has been widely used, but most of these models require a lot of processing power. This work proposes a low-power ShuffleNet V2-based Transfer Learning model for defect identification with low latency, easy upgrading, increased efficiency, and an automatic visual inspection system with edge computing. Initially, various image transformation techniques were used for data augmentation on casting datasets to test the model flexibility in diverse casting. Subsequently, a pre-trained lightweight ShuffleNetV2 model is adapted, and hyperparameters are fine-tuned to optimize the model. The work results in a lightweight, adaptive, and scalable model ideal for resource-constrained edge devices. Finally, the trained model can be used as an edge device on the NVIDIA Jetson Nano-kit to speed up detection. The measures of precision, recall, accuracy, and F1 score were utilized for model evaluation. According to the statistical measures, the model accuracy is 99.58%, precision is 100%, recall is 99%, and the F1-Score is 100 %.

The Pre-Existing Microcrack Population in Metals A Personal Overview

The author describes his view of how the metal casting process is often carried out turbulently, generating doubled-over oxide films (bifilms) in most metals (with interesting exceptions). The double films act as cracks, whose oxide films resist bonding, enabling the crack population to survive plastic working such as forging and rolling. Experimental evidence reveals their action in initiating tensile and fatigue failures, and reducing ductility and creep resistance. The bifilm cracks are mainly located at grain boundaries, where they encourage the precipitation of inclusions and second phases as a result of the savings of strain energy (far exceeding the normal driving force from interfacial energies). The precipitates force open the bifilms rather than otherwise plastically deforming the matrix to accommodate the changes of size and shape. It is reasonable to suppose that the opening of bifilms at grain boundaries would increase hydrogen permeation and embrittlement, and permit the ingress of corrodents leading to etch pitting and stress corrosion cracking. It seems the pre-existing population of microcracks is a phenomenon explaining the initiation of many of our failure mechanisms in metals. It is strongly recommended to reduce the microcrack population by the application of improved melting and casting technology.