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Additive manufacturing technology is highly regarded due to its advantages, such as high precision and the ability to address complex geometric challenges. However, the development of additive manufacturing process is constrained by issues like unclear fundamental principles, complex experimental cycles, and high costs. Machine learning, as a novel artificial intelligence technology, has the potential to deeply engage in the development of additive manufacturing process, assisting engineers in learning and developing new techniques. This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing, particularly in model design and process development. Firstly, it introduces the background and significance of machine learning-assisted design in additive manufacturing process. It then further delves into the application of machine learning in additive manufacturing, focusing on model design and process guidance. Finally, it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing. [ABSTRACT FROM AUTHOR]

Selective laser melting (SLM) has been widely used in the fields of aviation, aerospace and die manufacturing due to its ability to produce metal components with arbitrarily complex shapes. However, the instability of SLM process often leads to quality fluctuation of the formed component, which hinders the further development and application of SLM. In situ quality control during SLM process is an effective solution to the quality fluctuation of formed components. However, the basic premise of feedback control during SLM process is the rapid and accurate diagnosis of the quality. Therefore, an in situ monitoring method of SLM process, which provides quality diagnosis information for feedback control, became one of the research hotspots in this field in recent years. In this paper, the research progress of in situ monitoring during SLM process based on images is reviewed. Firstly, the significance of in situ monitoring during SLM process is analyzed. Then, the image information source of SLM process, the image acquisition systems for different detection objects (the molten pool region, the scanned layer and the powder spread layer) and the methods of the image information analysis, detection and recognition are reviewed and analyzed. Through review and analysis, it is found that the existing image analysis and detection methods during SLM process are mainly based on traditional image processing methods combined with traditional machine learning models. Finally, the main development direction of in situ monitoring during SLM process is proposed by combining with the frontier technology of image-based computer vision. [ABSTRACT FROM AUTHOR]

The coolant pump impeller casting is the only rotating component in the nuclear island of an AP1000 nuclear power station, and is required to have a 60- year service time, which requires advanced materials and processing technologies to guarantee. In this paper, the casting process was studied, designed and modified by means of numerical simulation. The gating system was distributed symmetrically and the runner diameter was a little bigger for avoiding sand wash and turbulence; the feeding system focused on the solution of blades feeding, as some parts of which should reach Severity Level 1 radioactive testing standard. Therefore, upper and lower plates cooperating with chillers acted as feeding method besides additional 2-3 times thickness; in addition, lowering sand core strength, decreasing pouring temperature and increasing dimension allowance would be adopted to avoid crack defects. Finally, the pilot impeller was cast. The results show that the casting process design is reasonable, as the liquid rises very smoothly when pouring, and no volume defects are found by means of 100% radioactive testing. Based on this casting process, 16 coolant pump impellers have been successfully produced and delivered to customers. [ABSTRACT FROM AUTHOR]

Seventy percent of new product cost is committed in the design phase. Therefore, the cost needs to be minimized. Incorporating accurate cost estimation capabilities into manufacturing processes can help industries to minimize the cost and optimize the design. The casting process has been employed as a key process to manufacture parts having the advantage of low cost and customized products in foundry industry. This paper presents a cost estimation system for the casting process based on the design features, which incorporates the casting information at the design stage of castings. It aims to deliver the best cost-effective choice for casting design features of a product. Two kinds of knowledge, namely economical knowledge (describing the relation between the casting design considerations and the cost) and technical knowledge (involving the material of the casting features) were structured in this research work. On the basis of the minimum product cost, casting material selection can be carried out in detail. The developed system has been validated through an industrial case study. [ABSTRACT FROM AUTHOR]

This paper presents the effects of chemical compositions of austempered ductile iron (ADI) on casting quality, heat treatment process parameters and mechanical properties of final products. Through experiment and production practice, the impacts of carbon equivalent on ADI and its mechanical properties have been studied. Proper content ranges for carbon and silicon have been obtained to avoid ADI casting shrinkage and graphite floatation, as well as to achieve the optimal mechanical properties. According to the impact of silicon content on austenite phase transformation, the existing form of carbon in ADI has been analyzed, and also the formula and diagram showing the relationship between austenitizing temperature and carbon content in austenite have been deduced. The chemical composition range for high performance ADI and its control points have been recommended, to serve as a reference for production process. [ABSTRACT FROM AUTHOR]

It has been demonstrated that heat absorption method by using the inorganic material rod to cool the molten steel can significantly reduce the macrosegregation level of the large steel ingot. However, owing to the opacity of the molten steel, the physical mechanism of the heat absorption method is not clear. In this work, a transparent hydraulic physical model with water and paraffin wax was built to simulate the melting and floating processes of inorganic materials in the molten steel. A mathematical simulation was also carried out to analyze the connection between the actual ingot and the physical model. Results show that it is feasible to simulate the molten steel and inorganic materials with water and paraffin wax. With the help of the physical model, the process of the melting of paraffin wax and its floating to the surface of water were clearly observed, during which the temperature of water at some characteristic positions in the mold was recorded. The visualization findings demonstrate that the melting and floating processes of paraffin wax can help to bring the heat from the center of the mold to the top surface more quickly, which reduces the superheat and significantly accelerates the cooling rate of water. The experimental results show that for the water with a certain superheat, the use of a larger mass of paraffin wax can accelerate the cooling of the water, but there is a risk of incomplete melting of the paraffin wax. A higher superheat of water will lead to a quicker melting rate for a given mass of paraffin wax, while a lower superheat leads to the incomplete melting of paraffin wax as well. [ABSTRACT FROM AUTHOR]

Aero-engine hollow turbine blades are work under prolonged high temperature, requiring high dimensional accuracy. Blade profile and wall thickness are important parameters to ensure the comprehensive performance of blades, which need to be measured accurately during manufacturing process. In this study, a high accuracy industrial computed tomography (ICT) measuring method was developed based on standard cylindrical pin and ring workpieces of different sizes. Combining ICT with cubic spline interpolation, a sub-pixel accuracy was achieved in measuring the dimension of component. Compared with the traditional and whole-pixel level image measurement method, the cubic spline interpolation algorithm has the advantages of high accuracy in image edge detection and thus high accuracy of dimensional measurement. Further, the technique was employed to measure the profile and wall thickness of a typical aerospace engine turbine blade, and an accuracy higher than 0.015 mm was obtained. [ABSTRACT FROM AUTHOR]