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Advanced methods for manufacturing high quality parts should be used to ensure the production of competitive products for the world market. Investment casting (IC) is a process where a wax pattern is used as a sacrificial pattern to manufacture high precision casting of solid metal parts. Rapid casting is in turn, a technique that eases the IC process by combining additive manufacturing (AM) technologies with IC. The use of AM technologies to create patterns for new industrial products is a unique opportunity to develop cost-effective methods for producing investment casting parts in a timely manner. Particularly, stereolithography (SLA) based AM is of interest due to its high dimensional accuracy and the smooth surface quality of the printed parts. From the first appearance of commercially available SLA printers in the market, it took a few decades until desktop SLA printers became available to consumers at a reasonable price. Therefore, the aim of this review paper is to analyze the state-of-the-art and applicability of SLA based 3D printing technology in IC manufacturing, as SLA based AM technologies have been gaining enormous popularity in recent times. Other AM techniques in IC are also reviewed for comparison. Moreover, the SLA process parameters, material properties, and current issues are discussed.

This paper aims to design lattice structures for rapid-investment casting (RIC), and the goal of the design methodology is to minimize casting defects that are related to the lattice topology. RIC can take full advantage of the unprecedented design freedom provided by AM. Since design for RIC has multiple objectives, we limit our study to lattice structures that already have good printability, i.e., self-supported and open-celled, and improve their castability. To find the relationship between topological features and casting performance, various lattice topologies underwent mold flow simulation, finite element analysis, casting experiments, and grain structure analysis. From the results, the features established to affect casting performance in descending order of importance are relative strut size, joint number, joint valence, and strut angle distribution. The features deemed to have the most significant effect on tensile and shear mechanical performance are strut angle distribution, joint number, and joint valence. The practical application of these findings is the ability to optimize the lattice topology with the end goal of manufacturing complex lattice structures using RIC. These lattice structures can be used to create lightweight components with optimized functionality for various applications such as aerospace and medical.

Purpose High-performance wrought aluminum alloys, particularly AA6061, are pivotal in industries like automotive and aerospace due to their exceptional strength and good response to heat treatments. Investment casting offers precision manufacturing for these alloys, because casting AA6061 poses challenges like hot cracking and severe shrinkage during solidification. This study aims to address these issues, enabling crack-free investment casting of AA6061, thereby unlocking the full potential of investment casting for high-performance aluminum alloy components. Design/methodology/approach Nanotechnology is used to enhance the investment casting process, incorporating a small volume fraction of nanoparticles into the alloy melt. The focus is on widely used aluminum alloy 6061, utilizing rapid investment casting (RIC) for both pure AA6061 and nanotechnology-enhanced AA6061. Microstructural characterization involved X-ray diffraction, optical microscopy, scanning electron microscopy, differential scanning calorimetry and energy dispersive X-ray spectroscopy. Mechanical properties were evaluated through microhardness and tensile testing. Findings The study reveals the success of nanotechnology-enabled investment casting in traditionally challenging wrought aluminum alloys like AA6061. Achieving crack-free casting, enhanced grain morphology and superior mechanical properties, because the nanoparticles control grain sizes and phase growth, overcoming traditional challenges associated with low cooling rates. This breakthrough underscores nanotechnology's transformative impact on the mechanical integrity and casting quality of high-performance aluminum alloys. Originality/value This research contributes originality and value by successfully addressing the struggles in investment casting AA6061. The novel nano-treating approach overcomes solidification defects, showcasing the potential of integrating nanotechnology into rapid investment casting. By mitigating challenges in casting high-performance aluminum alloys, this study paves the way for advancements in manufacturing crack-free, high-quality aluminum alloy components, emphasizing nanotechnology's transformative role in precision casting.

Rapid investment casting is a casting process in which the sacrificial patterns are fabricated using additive manufacturing techniques, making the creation of advanced designs possible. One of the popular 3D printing methods applied in rapid investment casting is stereolithography because of its high dimensional precision and surface quality. Printing parameters of the used additive manufacturing method can influence the surface quality and accuracy of the rapid investment cast geometries. Hence, this study aims to investigate the effect of stereolithography printing parameters on the dimensional accuracy and surface roughness of printed patterns and investment cast parts. Castable wax material was used to print the sacrificial patterns for casting. A small-scale prosthetic biomedical implant for total hip replacement was selected to be the benchmark model due to its practical significance. The main results indicate that the most significant stereolithography printing parameter affecting surface roughness is build angle, followed by layer thickness. The optimum parameters that minimize the surface roughness are 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and across the front base orientation. As for the dimensional accuracy, the optimum stereolithography parameters are 0.025 mm layer thickness, 30° build angle, 0.6 support density index, and diagonal to the front base orientation. The optimal printing parameters to obtain superior dimensional accuracy of the cast parts are 0.05 mm layer thickness, 45° build angle, 0.8 support density index, and diagonal to the front model base orientation. With respect to the surface roughness, lower values were obtained at 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and parallel to the front base orientation.

Dimensional accuracy and geometric characteristics of the manufactured parts bear significant importance in product assembly. In Rapid Investment Casting, these characteristics can be affected by the printing parameters of the Additive Manufacturing method used in the pattern production process. Stereolithography is one of the important AM techniques mostly exploited in RIC due to its accuracy, smooth surface, and precision. However, the effect of SLA printing parameters on the dimensional accuracy and geometric characteristics have not been studied thoroughly. This study considers an experimental approach to study the effect of SLA printing parameters such as layer thickness, build angle, support structure density, and support touchpoint size on the dimensional accuracy and geometrical characteristics of the Castable Wax printed patterns and the Al cast parts. Taguchi’s Design of Experiment was used to define the number of experimental runs. SolidCast simulation was used to design the orientation of casting feeder to achieve directional solidification. Coordinate Measuring Machine measurements of deviations in the printed and cast parts were analyzed using the “Smaller-the-better” scheme in the two-step optimization method of Taguchi experiments. Build angle and Layer thickness were identified to be the first and the second most impactful parameters, respectively, affecting both the dimensional and geometric accuracy of Castable Wax patterns and Al cast parts, with optimal values of 0 deg and 0.25 μm, respectively. Both printed and cast parts had twice as many deviations in geometry as in dimensions. The sphere roundness and angularity were found to be the most and least accurate geometric characteristics, respectively. The dimensions in the Z direction were more accurate than in the X-Y directions, showing the smallest size deviations for height measurements and large deviations in the length, width, and diameter of the hole.

Purpose Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively. Design/methodology/approach The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process. Findings To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages. Originality/value This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

Rapid casting (RC) is a phrase that refers to a specific casting process technique that reduces total production lead time. The technique for achieving it is Additive Manufacturing (AM) or Rapid Prototyping (RP). AM techniques were employed for RC to create complex shapes and sand a 3D mould from a CAD model. This article aimed to examine the performance of Rapid Ice Investment Casting (RIIC) compared with other RC processes such as Direct Wax Investment Casting (Direct Wax IC) , Lost Foam Casting (LFC), Lost PLA Casting (LPC) , and Rapid Sand Casting (RSC) . This investigation examines the part which has various geometric features. Each casting route's procedure is described in detail; pattern development, slurry preparation and mould making. Comparison of RIIC with other RC processes is studied based on the cast specimen's dimensional accuracy and surface finish. According to the findings, RIIC is preferable in terms of smooth surface finish, whereas Direct Wax IC and LFC are superior in dimensional accuracy. The article also addresses, the shortcomings of RIIC are discussed in this article, as well as proposed methods to overcome them.

Shrinkage porosity is a common issue in nickel-based superalloy 718 turbine blade investment castings, potentially compromising the mechanical properties of the final component. This study utilized finite element simulation to explore the impact of mold dwell time preceding the melt pouring process on the filling, solidification, and shrinkage defects in Inconel 718 superalloy turbine blade investment casting. The simulation results indicate that as the mold dwell time increases from 0 to 420 s, the shell temperature decreases from 1000 to 860 °C, while the total shrinkage volume and frequency rise from 2.6154 to 2.9398 cm 3 . This phenomenon mainly arises from the decrease in shell temperature and the evolution of solid fraction within the superalloy casting. For mold dwell times of 180 s, 300 s, and 420 s, the shell temperature directly declines to 900–950 °C, 850–940 °C, and 830–890 °C, respectively, before ascending to around 1200 °C during melt pouring. Subsequently, the microstructure of both as-cast and heat-treated superalloy 718 castings underwent observation and comparison.

Investment casting process is a well-recognized manufacturing process to produce industrial castings with tight, narrow tolerances, good surface finish, as well as higher complexity for many diversified sectors. However, complexity of investment castings is mostly represented by qualitative manner, and quantitative representation of complexity is not fully explored. In this work, efforts have been put to identify distinguished attributes contributing complexity involved in manufacturing investment castings and in quantifying it. In total, different 52 attributes that further characterize 212 meta-attributes were identified through rigorous survey conducted in one of the largest investment casting clusters representing nearly 25% of total investment casting foundries in India. These 52 attributes represent 19 elements that further signify 3 factors (geometry, features and manufacturability) contributing in overall complexity index. Analytic hierarchy process (AHP) has been adopted for computing relative weight for factors, elements, attributes as well as meta-attributes that further used in computation of complexity index. Developed complexity index was tested with several industrial castings and found it very useful. This will really help the designer to assist in the selection of the investment casting process for manufacturing industrial castings, and will contribute to the philosophy of design for manufacturing, and in turn, to design for investment casting (DFIC).

Purpose This study aims to evaluate the effectiveness of three-dimensional (3D) printed foam polylactic acid (PLA) patterns in reducing ceramic shell stresses and cracking during burnout in the rapid investment casting (RIC) process to improve casting yield and dimensional tolerances. Design/methodology/approach Cylindrical and step-wedge patterns were 3D printed using foam PLA feedstock and compared with patterns from plain PLA and Polyvinyl Butyral (PVB). The patterns were shelled using ceramic slurry and investment cast in A356.1 aluminum alloy. Shell cracking and dimensional tolerances of resulting castings were assessed. Additionally, a complex component was 3D printed, laser-scanned, then cast and rescanned to evaluate dimensional accuracy. Finite Element Analysis (FEA) was conducted on cylindrical geometries to analyze internal mold pressure because of thermal stresses during burnout. Findings The foam PLA for all patterns produced no shell cracking during both ramp and flash burnouts. Castings made from foam PLA patterns showed improved dimensional tolerances and a narrower error distribution in GD&T analysis compared to those made from PLA and PVB. FEA results indicated that the thermomechanical properties of foam PLA reduce internal mold pressure by over 90%, which decreased internal shell stresses. Originality/value This research introduces a novel application of 3D printed foam PLA feedstock in the RIC process as a pattern material. This study demonstrates that foam PLA patterns effectively eliminate shell cracking during burnout and enhance dimensional accuracy. The findings of this study offer a new approach for improving dimensional tolerances and casting yield in RIC, which has not been previously explored.