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Foundry produces cast metal components and parts for various industries and drives manufacturing excellence all over the world. Assuring quality of these components and parts is vital for the end product quality. The complexity in foundry operations increases with the complexity in designs, patterns and geometry and the quality parameters of the casting processes need to be monitored, evaluated and controlled to achieve expected quality levels.

The literature addresses quality improvement in foundry industry primarily focusing on surface roughness, mechanical properties, dimensional accuracy and defects in the cast parts and components which are often affected by numerous process variables. Primary data are collected from the experts working in sand and investment casting processes. The authors perform machine learning analysis of the data to model the quality parameters with appropriate process variables. Further, cluster analysis using k-means clustering method is performed to develop clusters of correlated process variables for sand and investment casting processes.

The authors identified primary process variables determining each quality parameter using machine learning approach. Quality parameters such as surface roughness, defects, mechanical properties and dimensional accuracy are represented by the identified sand-casting process variables accurately up to 83%, 83%, 100% and 83% and are represented by the identified investment-casting process variables accurately up to 100%, 67%, 67% and 100% respectively. Moreover, the prioritization of process variables in influencing the quality parameters is established which further helps the practitioners to monitor and control them within acceptable levels. Further the clusters of process variables help in analyzing their combined effect on quality parameters of casting products.

This study identified potential process variables and collected data from experts, researchers and practitioners on the effect of these on the quality aspects of cast products. While most of the previous studies focus on a very limited process variables for enhancing the quality characteristics of cast parts and components, this study represents each quality parameter as the function of influencing process variables which will enable the quality managers in Indian foundries to maintain capability and stability of casting processes. The models hence developed for both sand and investment casting for each quality parameter are validated with real life applications. Such studies are scarcely reported in the literature.

From an agency theory realm, this study aims to respond to the more recent calls to deeply analyze the indirect influence of professional shareholders, namely, institutional, blockholder and foreign owners, on the extent of compliance with International Financial Reporting Standards (IFRS) mandatory reporting requirements.

Multivariate regression analysis was applied. Moreover, quantitative static and dynamic panel data have been used. More plainly, ordinary least squares was run as a baseline estimator. Afterwards, one-step system generalized method of moment and two-stage least squares were conducted to control for the potential endogeneity dilemma. The analysis is based on a sample of nonfinancial listed firms on the Palestine Stock Exchange for the time span of 10 years, from 2010 to 2019.

After controlling for the detrimental effect of the endogeneity issue, the findings clearly reveal that the effect of the three types of professional shareholders (institutional, blockholder and foreign) on the extent of compliance with IFRS is more significant under a high proportion of independent nonexecutive directors.

To the best of the author’s knowledge, prior literature on the nexus between shareholding structure and compliance level with IFRS has restricted solely to analyzing the direct influence without casting the light on the moderation effect of independent nonexecutive directors. Hence, analyzing this sensitive configuration merits attention. In this vein, to ameliorate the compliance level with IFRS, regulators have to devote remarkable effort to updating both enforcement mechanisms and best practices of shareholding structure simultaneously.

When smelting Al-Li alloy, the material inevitably comes into contact with various oxide-refractories. These refractories are subjected to varying degrees of melt-corrosion at high temperatures. The purpose of this study is to find stable oxide refractories at casting temperature.

Four materials were selected for evaluation, and their corrosion by the Al-Li alloy at casting temperature and different holding times was measured. Subsequently, scanning electron microscopy and energy-dispersive spectroscopy were used to study the interfaces. Stable refractory materials were selected by comparing the thicknesses of the reaction layers.

The thickness of the Al-Li/ZrO₂ reaction layer varies linearly with the square root of the holding duration. Therefore, the growth of the reaction layer is controlled by diffusion. The reaction layer of Al-Li/Al₂O₃ is thinner, and its growth is also controlled by diffusion. However, there were no obvious reaction layers between the Al-Li alloy and MgO or Y₂O₃. By comparing these reaction-layer thicknesses, the order of stability was found to be ZrO₂ < Al₂O₃ < MgO and Y₂O₃.

These results provide a scientific basis for the optimal selection of refractory materials for Al-Li alloy smelting.

This study provides an up-to-date review of additive manufacturing (AM) technologies and guidance for selecting the most appropriate ones for specific applications, taking into account the main features, strengths, and limitations of the existing options.

A literature review on AM technologies was conducted to assess the current state-of-the-art. This was followed by a closer examination of different AM machines to gain a deeper insight into their main features and operational characteristics. The conclusions and data gathered were used to formulate a classification and decision-support framework.

The findings indicate the building blocks of the selection process for AM technologies. Furthermore, this work shows the suitability of the existing AM technologies for specific cases and points to opportunities for technological and decision-support improvements. Lastly, more standardization in AM would be beneficial for future research.

The proposed framework offers valuable support for decision-makers to select the most suitable AM technologies, as demonstrated through practical examples of its utilization. In addition, it can help researchers identify the limitations of AM by pinpointing applications where existing technologies fail to meet the requirements.

The study offers a novel classification and decision-support framework for selecting AM technologies, incorporating machine characteristics, process features, physical properties of printed parts, and costs as key features to evaluate the potential of AM. Additionally, it provides a deeper understanding of these features as well as the potential opportunities for AM and its impact on various industries.

Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process.

PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles.

PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one.

The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding.

This study aims to investigate the prediction of the nonlinear response of three-dimensional-printed polymeric lattice structures with and without structural defects. Unlike metallic structures, the deformation behavior of polymeric components is difficult to quantify through the classical numerical analysis approach as a result of their nonlinear behavior under mechanical loads.

Geometric models of periodic lattice structures were designed via PTC Creo. Imperfections in the form of missing unit cells are introduced in the replica of the lattice structure. The perfect and imperfect lattice structures have the same dimensions – 10 mm × 14 mm × 30 mm (w × h × L). The fused deposition modelling technique is used to fabricate the parts. The fabricated parts were subjected to physical compression tests to provide a measure of their transverse compressibility resistance. The ensuing nonlinear response from the experimental tests is deployed to develop a support vector machine surrogate model.

Results from the surrogate model’s performance, in terms of correlation coefficient, rose to as high as 99.91% for the nonlinear compressive stress with a minimum achieved being 98.51% across the four datasets used. In the case of deflection response, the model accuracy rose to as high as 99.74% while the minimum achieved is 98.56% across the four datasets used.

The developed model facilitates the prediction of the quasi-static response of the structures in the absence and presence of defects without the need for repeated physical experiments. The structure investigated is designed for target applications in hierarchical polymer packaging, and the methodology presents a cost-saving method for data-driven constitutive modelling of polymeric parts.

This study aims to present the optimization of parameters and effects of annealing and vapor smoothing post-processing treatments on the surface roughness and tensile mechanical properties of fused deposition modeling (FDM) printed acrylonitrile butadiene styrene (ABS).

Full-factorial test matrices were designed to determine the most effective treatment parameters for post-processing. The parameters for annealing were temperature and time, whereas the parameters for the vapor smoothing were volume of acetone and time. Analysis of surface roughness and tensile test results determined influences of the levels of parameters to find an ideal balance between mechanical properties and roughness.

Optimal parameters for vapor smoothing and annealing were determined. Vapor smoothing resulted in significantly higher improvements to surface roughness than annealing. Both treatments generally resulted in decreased mechanical properties. Of all treatments tested, annealing at 100 °C for 60 min provided the greatest benefit to tensile properties and vapor smoothing with 20 mL of acetone for 15 min provided the greatest benefit to surface roughness while balancing effects on properties.

Vapor smoothing and annealing of FDM ABS have typically been studied independently for their effects on surface roughness and material properties, respectively, with varying materials and manufacturing methods. This study objectively compares the effects of each treatment on both characteristics simultaneously to recommend ideal treatments for maximizing the balance between the final quality and performance of FDM components. The significance of the input variables for each treatment have also been analyzed. These findings should provide value to end-users of 3D printed components seeking to balance these critical aspects of manufacturing.

There is a rising demand for high-performance 3D printed objects that have established potential applications in the sector of dental, automotive, electronics, aerospace, etc. Thus, to meet the requirements of high-performance 3D printed objects, this study has synthesized, formulated and applied a resorcinol epoxy acrylate (REA) oligomer to a stereolithography (SLA) 3D printer.

Different formulations were developed by blending reactive diluents in the concentration of 10%, 15% and 20%, along with the fixed quantity of photo-initiators in the REA oligomer. The structure of synthesized REA oligomer was confirmed using 13 C nuclear magnetic resonance (NMR) and 1H NMR spectroscopy, and the rheological properties for prepared REA formulations were also evaluated. The ultraviolet (UV)-cured specimens of all REA formulations were thoroughly examined based on physical, chemical, optical, mechanical and thermal properties. The best suitable formulation was selected for SLA 3D printing.

As perceived, UV cured REA specimens exhibit superior mechanical, chemical and thermal properties, portraying the ability to use as a high-performance material. The increase in the concentration of reactive diluents indicated a significant improvement in the properties of REA resin. The 20% diluted formulation achieved excellent compatibility with a SLA 3D printer; thus, 3D objects are cast with good dimensional stability and printability.

Resorcinol-based resins have always been a key additive used to enhance properties in the coating and tire industry. In a new attempt UV, curable REA has been applied to a SLA 3D printer to cast high-performance 3D printed objects.

Different technologies may currently be used to produce dental prostheses, such as additive manufacturing and traditional milling. This study aims to evaluate and improve the fabrication process for hot-pressed porcelain dental prostheses and compare the use of masked stereolithography apparatus (MSLA) casting to computer-aided design/computer-aided manufacturing (CAD/CAM) casting. The cost-benefit analysis of producing dental prostheses through various technologies, including additive manufacturing and traditional milling, has not been fully explored. The cost of materials and processes used to produce prostheses varies based on complexity of design and materials used, and long-term effects, such as durability and wear and tear, must be taken into account.

Using key elements of part costs and estimation cost models, a multivariable approach was used to evaluate the practicality of the recommended strategy and process improvement.

The research found that MSLA casting provides a higher return on investment than CAD/CAM casting, and the optimized production process could be more suitable for the size and annual demand for prostheses.

Overall, this study highlights the need for a more comprehensive understanding of the cost-benefit analysis of different dental prosthesis production methods and emphasises the importance of evaluating long-term effects on the cost-benefit analysis.

Anecdotal evidence suggests that casting actors with similar facial features in a movie can pose challenges in foreign markets, hindering the audience's ability to recognize and remember characters. Extending developments in the literature on the cross-race effect, we hypothesize that facial similarity – the extent to which the actors starring in a movie share similar facial features – will reduce the country-level box-office performance of US movies in East and South-East Asia (ESEA) countries.

We assembled data from various secondary data sources on US non-animation movies (2012–2021) and their releases in ESEA countries. Combining the data resulted in a cross-section of 2,616 movie-country observations.

Actors' facial similarity in a US movie's cast reduces its box-office performance in ESEA countries. This effect is weakened as immigration in the country, internet penetration in the country and star power increase and strengthened as cast size increases.

This first study on the effects of cast's facial similarity on box-office performance represents a novel extension to the growing literature on the antecedents of movies' box-office performance by being at the intersection of the two literature streams on (1) the box-office effects of cast characteristics and (2) the antecedents, in general, of box-office performance in the ESEA region.