Defective Castings Research Articles

Fatigue assessment of defective A357-T6 cast aluminum based on affected depth

Fatigue assessment of defective A357-T6 cast aluminum based on affected depth

Investigation on effect of carbon equivalent and inoculation on the solidification and shrinkage tendency of ductile cast iron using thermal analysis

PurposeThe foundry industry incurs additional costs as a result of defective castings. Shrinkage defects are a frequent problem in ductile iron castings. It is still essential to understand how shrinkage porosity varies in size when the ductile iron composition changes. This information can be used to produce high-quality cast parts and determine the best processing conditions. The objective of this research paper is to examine the effect of carbon equivalent and inoculation on the morphology of the shrinkage defect using thermal analysis.Design/methodology/approachThis study focuses on certain thermal analysis parameters, such as the angle of the first derivative curve at the solidus temperature, recalescence and its relationships to graphite nucleation and shrinkage tendency. The results of thermal analysis in terms of the cooling curve and its derivative parameters, and thorough characterizations of the shrinkage observed in cup castings produced with various melt compositions and inoculation are presented in the current study.FindingsThe proportion of caved surfaces and macro shrinkage porosity defects has been reduced as the carbon equivalent of melt increases from hypoeutectic to a hypereutectic composition. The composition that is slightly hypereutectic has the lowest shrinkage propensity. Although inoculation reduces shrinkage, the importance of this parameter differs depending on the carbon equivalent.Originality/valueThe percentage of macro shrinkage porosity and the angle that the cooling rate curve forms are strongly correlated. It is found that the macro shrinkage size decreases as the angle of the first derivative curve at the solidus temperature is reduced. Further, lower macroporosity is produced by a metal that has a higher nodule count in association with a greater cooling rate toward the end of the solidification process.

Quality Control of Semi-Solid Die Casting by Filling Pressure Based on Machine Learning Method

In the actual semi-solid die-casting production, the existence of several uncertain factors can impose an effect on the final product quality, which poses a challenge to semi-solid production. However, data analysis such as machine learning (ML) can help producers eliminate this problem. In order to quickly identify defective castings, a new model of predicting quality by real-time injection pressure data will be generated in terms of ML in this research. Quality assessment will be based on non-filling defect, density and tensile properties. The result of cross-validation shows that the classifier can achieve a confidence level of 0.95 for the quality classification. In addition, this research will find key intervals by the importance given by the model and analyze the effects of process on filling pressure. According to the result of feature screening, the surface quality problems are related to speed-pressure conversion and feeding displacement of plunger, the flowing state of slurry in filling affects the formation of defects and tensile properties. This work will make semi-solid die casting more automatically and efficiently, and thus provides support for semi-solid sustainable development.

Porous wax patterns for high-precision investment casting

Aerospace, manufacturing, and shipbuilding industries strive to enhance their competitiveness by optimizing material utilization and improving production processes. The investment casting process offers the capability to fabricate intricate and precise components using a diverse range of alloys. However, this method is not without its drawbacks, including high manufacturing costs and a significant rate of defective castings, which can reach up to 30 %. These defects primarily arise from the stresses imposed on the wax patterns and ceramic molds, leading to their distortion. To address this issue, efforts have been made to reduce stress by employing compacted wax powders for the production of investment patterns. However, stress relaxation in the wax patterns remains a concern as it can result in elastic deformation of the compacted material and subsequent alterations in the final product dimensions. To mitigate this issue, a series of tests were conducted with the objective of studying stress relaxation under constant compression strain, as described by the Kohlrausch equation. The obtained results provide valuable insights that enable the prediction of the ultimate dimensions of patterns created using different grades of wax.

An Insight into the Defects-Driven Plasticity in Ductile Cast Irons.

The microstructure and tensile behavior of two heavy section castings that had chemical compositions typical of GJS400 were investigated. Conventional metallography, fractography, and micro-Computer Tomography (μ-CT) were employed, enabling the quantification of the volume fractions of eutectic cells with degenerated Chunky Graphite (CHG), which was identified as the major defect in the castings. The Voce equation approach was exploited to evaluate the tensile behaviors of the defective castings for integrity assessment. The results demonstrated that the Defects-Driven Plasticity (DDP) phenomenon, which refers to an unexpected regular plastic behavior related to defects and metallurgical discontinuities, was consistent with the observed tensile behavior. This resulted in a linearity of Voce parameters in the Matrix Assessment Diagram (MAD), which contradicts the physical meaning of the Voce equation. The findings suggest that the defects, such as CHG, contribute to the linear distribution of Voce parameters in the MAD. Furthermore, it is reported that the linearity in the MAD of Voce parameters for a defective casting is equivalent to the existence of a pivotal point in the differential data of the tensile strain hardening data. This pivotal point was exploited to propose a new material quality index assessing the integrity of castings.

Behavior of Defective Cast in Place Piles

This paper deals with testing defected model piles in the soil in order to study their behavior. In this respect, the results of model pile tests are discussed either geotechnically or structurally according to the type of failure.
 
 Two parameters were studied in order to evaluate the general behavior of defective piles. These parameters include the defect location and the defect type for floating and end bearing pile. The results of the experimental work indicated that the critical case for floating pile is seen to be when the defect of (5%) at the first third of the pile length at which the decrease in the bearing capacity is about (21%), while the decrease in the bearing capacity is found to be (14%) and (10%), when the defect is at the middle and the lower third of the pile length, respectively. The decrease in the bearing capacity for floating pile is found to be (31%) and (21%) for void and neck defect, respectively, while the decrease in the bearing capacity for end bearing pile is found to be (43%) and (52%) for void and neck defect, respectively.

Nondestructive Defect Detection in Castings by Using Spatial Attention Bilinear Convolutional Neural Network

X-ray images of castings are widely used in manufacturing for quality assurance. This article investigates the X-ray-image-based defective detection. The main contributions in this article are twofold: first, a new full-image method is proposed to classify defective castings and nondefective ones; and second, by combining two technologies, spatial attention mechanism and bilinear pooling used in deep convolutional neural networks (CNNs), a new spatial attention bilinear CNN is proposed to enhance the representation power of CNN. To validate the above initiatives, extensive experimental studies have been carried out to show the advantages of the new method over a number of existing ones.

A probabilistic model to estimate visual inspection error for metalcastings given different training and judgment types, environmental and human factors, and percent of defects

Abstract Current methods for visual inspection of cast metal surfaces are variable in both terms of repeatability and reproducibility. Because of this variation in the inspection methods, extra finishing operations are often prescribed; much of this is over processing in attempt to avoid rework or customer rejection. Additionally, defective castings may pass inspection and be delivered to the customer. Given the importance of ensuring that customers receive high-quality castings, this article analyzes and quantifies the probability of Type I and II errors, where a Type I error is a false alarm, and a Type II error misses a present defect. A probabilistic model frequently used in risk analysis, called an influence diagram, is developed to incorporate different factors impacting the chances of Type I and II errors. These factors include: training for inspectors, the type of judgment used during the inspection process, the percentage of defective castings, environmental conditions, and the inspectors’ capabilities. The model is populated with inputs based on prior experimentation and the authors’ expertise. The influence diagram calculates the probability of a Type I error at 0.35 and the probability of a Type II error at 0.40. These results are compared to a naive Bayes model. A manufacturer can use this analysis to identify factors in its foundry that could reduce the probability of errors. Even under the best-case scenario, the probability of Type I error is 0.18 and the probability of Type II error is 0.30 for visual inspection. This indicates improvements to the inspection process for cast metal surfaces is required.

Defect size map for nodular cast iron components with ellipsoidal surface defects based on the defect stress gradient approach

Abstract The impact of surface defects on the fatigue properties of cast iron material cannot be neglected in the fatigue design process. Allowable defect size maps are a practical tool for the quality control of surface defects on castings. These results present a compliance between the detrimental effect of surface inhomogeneities and the primary requirement of structural integrity during service life. The Defect Stress Gradient approach from Vincent et al. (2014) has been further improved by a general ellipsoidal geometry model for surface defects, and has been utilized for the fatigue assessment of defective nodular cast iron. After the study of defect size, shape and orientation effects calculations are compared with experimental results for high-strength ferritic nodular cast iron and 1045 steel. Two methods are proposed for an allowable defect size map based surface defect assessment using ellipsoidal description of the defect. The ellipsoidal description of the defect size, shape and orientation offers a more precise representation of real defects leading to more accurate results than the established hemispherical notch or surface crack methods.

Properties of Composite Electrolytic Coating Nickel–Cobalt–Aluminum Oxide–Fluoroplastic

The method of obtaining composite electrolytic coatings (CEC) based on the nickel–cobalt–aluminum oxide system possessing high performance properties is considered in the work, since in engineering, automotive, instrument making, and other industries much attention is paid to the development of new materials possessing increased physical and mechanical properties. The use of such CEC will not only increase the reliability and durability of new machine parts and mechanisms and restore old ones, but in many cases will also replace defective alloyed steel and cast iron with cheaper metals. The article suggests a chloride electrolyte for the application of wear- and corrosion-resistant CEC nickel–cobalt–aluminum oxide–fluoroplastic. The effect of electrolysis regimes on the composition of the electrolyte and the concentration of alloying components on the physical and mechanical properties (wear resistance, corrosion resistance, microhardness, internal stresses, porosity, adhesion) of nickel–cobalt–alumina–fluoroplastic coatings is studied. The use of such coatings will expand the scope of their use as a wear- and corrosion-resistant coating in various friction nodes.

Under-solidus austenite grain growth and transverse cracking in hypoperitectic carbon steel

Transverse cracks in the slabs made of hypoperitectic steel in the vertical bending continuous slab caster were analysed in the presented work. In-depth diagnostic has been applied to define the areas with the transversal area cracks and the transverse corner cracks and their generation factors. It has been done by data analysis from the production metallurgy records of defective cast slabs and the cracks were analysed by fractography and metallography. The results were processed utilizing cause-and-effect diagrams, too. It has been confirmed, there is a susceptibility of the hypoperitectic steel (with carbon content from 0.08 to 0.16%C) to coarse columnar austenite grain (CCG) growth, which forms the factors of transverse crack initiation and propagation.

Fatigue behaviour of defective cast iron

Abstract With the analysis example of a cast iron component a Finite Element Analysis (FEA) based modelling and post-processing methodology is proposed for the multiaxial high-cycle fatigue assessment of surface defects. Methods are proposed for the measurement and mechanical description of surface defects using an ellipsoid simplification and the well-known size parameter from Murakami (2002). Different methods are compared for the stress-computation near surface defects: elastic FEA, elastic-plastic FEA with nonlinear kinematic hardening material model, and analytical calculations with the Equivalent Inclusion Method from Eshelby (1957). The Defect Stress Gradient (DSG) approach from Vincent et al. (2014) is applied to predict crack initiation, whereby a new method is proposed for the estimation of the stress gradient, which allows the presentation of the DSG utilisation factor results field.

Bayesian inference-based investment-casting defect analysis system for industrial application

In spite of the best efforts of foundry engineers, many castings contain defects and need to be rejected, repaired, or recycled (remelted). This leads to an unnecessary wastage of production resources, reduced productivity, and delayed supply of parts to customers. The defects can be significantly reduced by identifying and controlling the relevant parameters (related to process and composition), through the application of comprehensive domain knowledge. This is, however, a challenging task since the above parameters vary within a wide range, and it is difficult to determine the specific range of values that should be avoided to prevent the defects. In this paper, we present a Bayesian inference-based methodology for analysis and reduction of casting defects. The data related to process parameters and chemical composition of alloy, as well as the number of defective castings, is collected from a foundry. The values of posterior probability of each input parameter are computed using Bayesian inference to identify the most influencing parameters and the avoidable range of their values. The system was successfully tested on real-life data obtained from an industrial investment-casting foundry, leading to significant reduction in rejection rate of cast parts. The proposed methodology, implemented using Microsoft Excel, was found to be easy to use by practicing engineers, without any training or customizing, and can therefore be applied to any investment-casting foundry.

Updated Research Result on Transverse Corner Crack of Slab

To introduce feature and microstructure of edge crack of rolled coil, character and distribution of transverse corner crack of continuous cast slab (hereafter referred to as transverse corner crack), trace out rolling process of defective continuous cast slab, transverse corner crack of slab causes edge crack of rolled coil, the corner inclusions of slab and rolling process are also significant factors. To give some suggestions to resolve two dimensional heat transfer and high cooling intensity about control of transverse corner cracks. Inclusions cause stress concentration to lead to edge cracks of coils. Edge cracks of coils are related to transverse corner cracks of slabs, but not an exact one-for-one relation. Tiny transverse corner cracks may be removed by scarfing or furnace. Uneven or low temperature of the edge of rolled piece cause uneven extension of edge metal to form “fold”, namely “edge filament”. By research and practice, the quality of slab has been substantially improved in Shougang Qiangang.

Influence of inoculation on shrinkage defects in spheroidal graphite cast iron

Defective castings produce unnecessary costs for foundries. Common flaws in spheroidal graphite cast iron castings are shrinkage defects. The literature on the subject suggests that by controlling the precipitation of graphite, it is possible to suppress the shrinkage propensity of the melt. The most influential way of affecting the precipitation of graphite is inoculation. In this work, the effectiveness of different commercial inoculant products and inoculation methods in reducing the shrinkage defects for cast components were researched. Significant differences in performance were observed between ladle inoculation and stream inoculation methods in preference of stream inoculation. Differences were also observed for different inoculants and, when both ladle and stream inoculants were used, also for their behaviour as a combination. It was observed that not all of the combinations were beneficial. In order to decrease the cost caused by shrinkage defects, a proper selection of inoculation method and inoculant is of importance.

Enhancing Knowledge Hyper Surface Method for Casting Diagnosing

The diagnosis of defective castings has always been a centre of attention in the manufacturing industry. This is mainly because the cause and effect relationship in a casting process is complex and non-linear. Furthermore, a large number of parameters are needed to be coordinated with each other in an optimal way to minimise the occurrence of defective castings. An intelligent diagnosis system is needed to diagnose effectively the causal representation and also justify its diagnosis. A previous method, known as the Knowledge Hyper-surface method which used Lagrange Interpolation polynomials has gained more popularity in learning cause and effect analysis in casting processes. The current method show that the belief value of the occurrence of cause with respect to the change in the belief value in the occurrence of effect can be modeled by linear, quadratic or cubic relationships and the method retained the advantages of neural networks and overcomes their limitations in learning the input-output mapping function in the presence of noisy, limited and sparse data. However, the methodology was unable to model exponential increase/decrease in belief values in cause and effect relationships . This paper proposed an enhancement to the current Knowledge Hyper-surface method by introducing midpoints in the existing shape formulation which further constrains the shape of the Knowledge hyper-surfaces to model an exponential rise in belief values but without exposing the dataset to the limitations of ‘over fitting’. The ability of the proposed method to capture the exponential change in the belief variation of the cause when the belief in the effect is at its minimum is compared to the current method on real casting data. DOI: http://dx.doi.org/10.11591/ij-ai.v2i1.584

Semi-Friction Stir Processing the Method for Improvement of the Product Surface Layer

The paper deals with the application of semi-Friction Stir Processing (s-FSP) to the improvement of surface contact within the flange joints used in casings of high-voltage switchgears which are filled with electroinsulating SF6 gas. The goal of the research was to design the appropriate tool (shape and size) as well as to select parameters for this s-FSP process which results in the removal of casting defects from the surface layer of the final product. The characteristics of the proposed process is the redesign of a tool shape, which is not equipped with an element penetrating and stirring the material (pin). Moreover, the process does not require the usage of sophisticated devices or tilting the tool relative to the treated surface during the process. The elaborated process is useful for repairing the defective castings, and in the case of high-voltage switchgears, it allows to achieve the required tightness of the joints.

다이캐스팅 스케줄링의 결품 방지 기법

다이캐스팅 스케줄링은 각 쉬프트마다 생산되는 주조제품의 개수를 결정하여 주어진 성능지수를 최적화하는 작업이다. 본 논문은 다이캐스팅 스케줄을 실제 주조공정에 적용할 때 불량주물 등의 이유로 발생하는 결품을 방지하는 새로운 기법을 제안한다. 선형계획법으로 모델링된 기존의 다이캐스팅 스케줄링은 용탕에 대한 용융로의 평균효율을 최대로 하지만 주조공정에서 불량품이 발생하는 문제에는 대처하지 못한다. 제안된 기법에서는 이전 쉬프트에서 불량주물이 발생하는 경우, 이를 대체할 수 있도록 현재 쉬프트에서 주조공정이 끝나고 남은 용탕의 잔여량을 이용하여 추가로 생산한다. 이 방법은 이미 최적화된 투입 용탕의 양이나 스케줄링 결과를 변경하지 않고도 불량이 발생한 주조제품의 생산량을 최대한 보상할 수 있는 장점을 지닌다. 사례 연구를 통하여 새로 제안된 기법의 우수성과 응용 가능성을 검증한다. Scheduling of die casting is a procedure of determining quantities of cast products so as to optimize a predetermined performance criterion. This paper presents a novel scheme of preventing product shortage raised by defective castings when die casting scheduling is applied to real casting operations. The previously developed linear programming (LP) model for die casting scheduling maximizes the average efficiency of melting furnaces in regard of the usage of molten alloy. However, the LP model is not able to cope with the problem of defective products occurring in the casting process. The proposed scheme is that whenever defective products are found in a shift, the foundryman produces additional cast products using the residue of molten alloy left at the end of the next shift. Neither the calculated amount of molten alloy nor the scheduling result of the LP model does not have to be altered for this method. The simulation result demonstrates the superiority and applicability of the newly proposed scheme.

New sol–gel refractory coatings on chemically-bonded sand cores for foundry applications to improve casting surface quality

Foundry refractory coatings protect bonded sand cores and moulds from producing defective castings during the casting process by providing a barrier between the core and the liquid metal. In this study, new sol–gel refractory coating on phenolic urethane cold box (PUCB) core was examined. The coating density, viscosity, moisture content and wet and dry weight of the coating were evaluated on cores that had been coated at three different dip-coating times. The coating coverage, surface appearance and depth of penetration into the cores were examined with a Stereomicroscope. Gray iron castings were produced with sol-gel coated and uncoated cores and the results were related to the coating properties. The casting results were also compared with castings made with cores coated with commercial alcohol-based and water-based foundry coatings. The analyses show that castings produced with sol–gel coated cores have better surface quality than those from uncoated cores and comparable surface quality with the commercial coatings. Therefore, the new sol–gel coating has a potential application in the foundry industry for improving the surface finish of castings thereby reducing the cost of fettling in the foundry industry since the raw materials and technology are easily affordable.

Investigation of the Stability of Melt Flow in Gating Systems

Melt flow in four different gating systems designed for the production of brake disks was analyzed experimentally and by numerical modeling. In the experiments, molds were fitted with glass fronts and melt flow was recorded on video. The video recordings were compared with the modeling of melt flow in the gating systems. Particular emphasis was on analyzing local pressure and formation of pressure waves in the gating system. It was possible to compare melt flow patterns in experiments directly with modeled flow patterns. Generally, there was good agreement between flow patterns and filling times. However, the description of free liquid surfaces proved to be incorrect in the numerical model. The modeled pressure fields served to explain how specific parts of the gating systems cause instability and are a good tool to describe the quality of a gating system. The results show clearly that sharp changes in the geometry of the gating system causes pressure waves to form that eventually lead to defective castings. It is clear that sharp corners and dead ends in gating systems should be avoided, and that more streamlined, organic, or naturally pressurized designs based on fluid dynamic principles will are necessary to design gating systems for the production of high-quality castings.