Optimization of conventional spinning process parameters by means of numerical simulation and statistical analysis

Research in sheet metal spinning has increased due to a greater demand, especially in the transportation industries, for parts with very high strength-to-weight ratios with low cost. Spinning processes are efficient in producing such characteristics and there is great flexibility in the process with a relatively low tool cost. The objectives of this investigation are to define the critical working parameters in spinning, show the effects of these factors on product quality characteristics, and to optimize the working parameters. The example used is the conventional spinning of a cylindrical cup. Optimization of the process is undertaken through the use of statistical analysis tools applied to the data produced from three-dimensional finite element simulations of the process. This has been achieved by generating two ‘designs of experiments’.The first identifies the most critical parameters for product formability and the second shows how these critical parameters affect the product quality. The results show that feed rate,relative clearance, and roller nose radius are the most important working parameters and significantly affect average thickness, thickness variation, and springback of the cylindrical cup. An additional 22 per cent improvement in the product quality characteristic is gained through using the optimum working parameters

Entrained defects and mechanical properties of aluminium castings

The presence of entrained double oxide films, known as bifilms, has been identified as a contributing factor to the variability in mechanical properties observed in aluminium castings. These bifilms consist of folded-over oxide films containing gas-filled crevices and are formed due to turbulence on the liquid metal's surface during handling and pouring. Additionally, it has been suggested that hydrogen dissolved in the aluminium melt can permeate these defects, causing them to expand and leading to the formation of hydrogen porosity. This, in turn, exacerbates the detrimental effects on the mechanical properties of the castings. In this study, the ultimate tensile strength (UTS) and percentage elongation of sand cast bars were compared under various casting conditions. These parameters were chosen as indicators of casting reliability, which was expected to be influenced by the presence of oxide films. The results indicated that incorporating filters in the gating system and reducing the runner height led to a noticeable improvement in tensile strength and elongation. This improvement was attributed to enhanced mold filling conditions, which reduced the likelihood of oxide film entrainment. The findings of this research provide valuable insights into the factors that affect the properties of light metal alloy castings. By understanding these influences, it becomes possible to develop improved practices that result in healthier castings with enhanced mechanical properties

Effect of runner thickness and hydrogen content on the mechanical properties of A356 alloy castings

Earlier studies demonstrated the detrimental effect of entrained bifilm defects on aluminum cast alloys’ tensile and fatigue properties. It was suggested that hydrogen has a contributing role as it diffuses into the bifilms and swells them out to form hydrogen porosity. In this study, the effect of the runner height and hydrogen content on the properties of A356 alloy castings was investigated using a two-level full factorial design of experiments. Four responses, the Weibull modulus and position parameter of both the ultimate tensile strength (UTS) and % elongation, were assessed. The results suggested that decreasing the runner height and adopting procedures intended to decrease the hydrogen content of the casting caused a considerable enhancement of the Weibull moduli and position parameters of the UTS and % elongation. This was reasoned to the more quiescent practice during mold filling, eliminating the possibility of bifilm formation as well as the decreased hydrogen level that eliminated the amount of hydrogen diffused into the bifilms and accordingly decreased the size of the entrained defects. This, in turn, would allow the production of A356 cast alloys with better and more reproducible properties

Influence of bifilm defects generated during mould filling on the tensile properties of Al–Si–Mg cast alloys

Entrapped double oxide film defects are known to be the most detrimental defects during the casting of aluminium alloys. In addition, hydrogen dissolved in the aluminium melt was suggested to pass into the defects to expand them and cause hydrogen porosity. In this work, the effect of two important casting parameters (the filtration and hydrogen content) on the properties of Al–7 Si–0.3 Mg alloy castings was studied using a full factorial design of experiments approach. Casting properties such as the Weibull modulus and position parameter of the elongation and the tensile strength were considered as response parameters. The results suggested that adopting 10 PPI filters in the gating system resulted in a considerable boost of the Weibull moduli of the tensile strength and elongation due to the enhanced mould filling conditions that minimised the possibility of oxide film entrainment. In addition, the results showed that reducing the hydrogen content in the castings samples from 0.257 to 0.132 cm3/100 g Al was associated with a noticeable decrease in the size of bifilm defects with a corresponding improvement in the mechanical properties. Such significant effect of the process parameters studied on the casting properties suggests that the more careful and quiescent mould filling practice and the lower the hydrogen level of the casting, the higher the quality and reliability of the castings produced

Video-to-Video Pose and Expression Invariant Face Recognition using Volumetric Directional Pattern

Face recognition in video has attracted attention as a cryptic method of human identification in surveillance systems. In this paper, we propose an end-to-end video face recognition system, addressing a difficult problem of identifying human faces in video due to the presence of large variations in facial pose and expression, and poor video resolution. The proposed descriptor, named Volumetric Directional Pattern (VDP), is an oriented and multi-scale volumetric descriptor that is able to extract and fuse the information of multi frames, temporal (dynamic) information, and multiple poses and expressions of faces in input video to produce feature vectors, which are used to match with all the videos in the database. To make the approach computationally simple and easy to extend, key-frame extraction method is employed. Therefore, only the frames which contain important information of the video can be used for further processing instead of analyzing all the frames in the video. The performance evaluation of the proposed VDP algorithm is conducted on a publicly available database (YouTube celebrities’ dataset) and observed promising recognition rates

Optimisation of a novel hot air contactless single incremental point forming of polymers

This study presents a new contactless sheet forming method that utilises hot air as a forming tool to address tool wear challenges in single-point incremental forming. Experiments were conducted on a 3-axis CNC machine equipped with a hot air nozzle on a polycarbonate sheet. A design of experiment (DOE) approach was employed, evaluating five control factors: air pressure, air temperature, feed rate, tool offset, and step down. The evaluation criteria for the formed sheets are profile variation, thickness variation, and surface roughness. The results indicate that air temperature and feed rate have the most significant influence on the deformation process. Additionally, air pressure and feed rate substantially impact both thickness variation and surface roughness of the formed material. To optimise the process parameters for high-quality forming, a prediction model is developed. The optimised process shows good agreement with the predicted model regarding profile and thickness variations. However, it does not align with surface roughness due to the stepwise nature and inherent waviness of the contactless forming technique. This study offers a promising approach for developing innovative contactless forming techniques using hot pressurised air as a forming tool. The proposed technique has the potential to significantly reduce tool wear and lubrication requirements

Porosity, cracks, and mechanical properties of additively manufactured tooling alloys: A review

Additive manufacturing (AM) technologies are currently employed for the manufacturing of completely functional parts and have gained the attention of high-technology industries such as the aerospace, automotive, and biomedical fields. This is mainly due to their advantages in terms of low material waste and high productivity, particularly owing to the flexibility in the geometries that can be generated. In the tooling industry, specifically the manufacturing of dies and molds, AM technologies enable the generation of complex shapes, internal cooling channels, the repair of damaged dies and molds, and an improved performance of dies and molds employing multiple AM materials. In the present paper, a review of AM processes and materials applied in the tooling industry for the generation of dies and molds is addressed. AM technologies used for tooling applications and the characteristics of the materials employed in this industry are first presented. In addition, the most relevant state-of-the-art approaches are analyzed with respect to the process parameters and microstructural and mechanical properties in the processing of high-performance tooling materials used in AM processes. Concretely, studies on the additive manufacturing of ferrous (maraging steels and H13 steel alloy) and non-ferrous (Stellite alloys and WC alloys) tooling alloys are also analyzed

Hot-air contactless single-point incremental forming

Single-point incremental forming (SPIF) has emerged as a time-efficient approach that offers increased material formability compared to conventional sheet-metal forming techniques. However, the physical interaction between the forming tool and the sheet poses challenges, such as tool wear and formability limits. This study introduces a novel sheet-forming technique called contactless single-point incremental forming (CSPIF), which uses hot compressed air as a deformation tool, eliminating the requirement for physical interaction between the sheet and a rigid forming tool. In this study, a polycarbonate sheet was chosen as the case-study material and subjected to the developed CSPIF. The experiments were carried out at an air temperature of 160 °C, air pressure of 1 bar, a nozzle speed of 750 mm/min, and a step-down thickness of 0.75 mm. A Schlieren setup and a thermal camera were used to visualize the motion of the compressed hot air as it traveled from the nozzle to the sheet. The results showed that the CSPIF technique allowed for the precise shaping of the polycarbonate sheet with minimal springback. However, minor deviations from the designed profile were observed, primarily at the starting point of the nozzle, which can be attributed to the bending effects of the sample. In addition, the occurrence of sheet thinning and material buildup on the deformed workpiece was also observed. The average surface roughness (Ra) of the deformed workpiece was measured to be 0.2871 micron

Design optimisation of additively manufactured titanium lattice structures for biomedical implants

A key advantage of additive manufacturing (AM) is that it allows the fabrication of lattice structures for customised biomedical implants with high performance. This paper presents the use of statistical approaches in design optimisation of additively manufactured titanium lattice structures for biomedical implants. Design of experiments using response surface and analysis of variance were carried out to study the effect design parameters on the properties of the AM lattice structures such as ultimate compression strength, specific compressive strength, elastic modulus, and porosity. In addition, the lattice dimensions were optimized to fabricate a diamond cellular structure with properties that match human bones. The study found that the length of a diamond-shaped unit cell strut is the most significant design parameter. In particular, the porosity of the unit cell increases as the strut length increases, while it had a significant reverse effect on the specific compressive strength, elastic modulus and ultimate compression strength. On the other hands, increasing the orientation angle was found to reduce both the specific compressive strength and modulus of elasticity of the lattice structure. An optimised lattice structure with strut diameter of 0.84 mm, length of 3.29 mm and orientation angle of 47° was shown to have specific compressive strength, elastic modulus, ultimate compression strength and porosity of 37.8 kN.m/kg, 1 GPa, 49.5 MPa and 85.7%, respectively. A cellular structure with the obtained properties could be effectively applied for trabecular bones replacement surgeries

Words into Action: Learning Diverse Humanoid Robot Behaviors using Language Guided Iterative Motion Refinement

Humanoid robots are well suited for human habitats due to their morphological similarity, but developing controllers for them is a challenging task that involves multiple sub-problems, such as control, planning and perception. In this paper, we introduce a method to simplify controller design by enabling users to train and fine-tune robot control policies using natural language commands. We first learn a neural network policy that generates behaviors given a natural language command, such as "walk forward", by combining Large Language Models (LLMs), motion retargeting, and motion imitation. Based on the synthesized motion, we iteratively fine-tune by updating the text prompt and querying LLMs to find the best checkpoint associated with the closest motion in history. We validate our approach using a simulated Digit humanoid robot and demonstrate learning of diverse motions, such as walking, hopping, and kicking, without the burden of complex reward engineering. In addition, we show that our iterative refinement enables us to learn 3x times faster than a naive formulation that learns from scratch