Casting Machine Research Articles

A Flexible Mold for Facade Panel Fabrication

Architectural surface panelling often requires fabricating molds for panels, a process that can be cost-inefficient and material-wasteful when using traditional methods such as CNC milling. In this paper, we introduce a novel solution to generating molds for efficiently fabricating architectural panels. At the core of our method is a machine that utilizes a deflatable membrane as a flexible mold. By adjusting the deflation level and boundary element positions, the membrane can be reconfigured into various shapes, allowing for mass customization with significantly lower overhead costs. We devise an efficient algorithm that works in sync with our flexible mold machine that optimizes the placement of customizable boundary element positions, ensuring the fabricated panel matches the geometry of a given input shape: (1) Using a quadratic Weingarten surface arising from a natural assumption on the membrane's stress, we can approximate the initial placement of the boundary element from the input shape's geometry; (2) we solve the inverse problem with a simulator-in-the-loop optimizer by searching for the optimal placement of boundary curves with sensitivity analysis. We validate our approach by fabricating baseline panels and a facade with a wide range of curvature profiles, providing a detailed numerical analysis on simulation and fabrication, demonstrating significant advantages in cost and flexibility.

Numerical Simulation of Solute Transport Behavior During the Grade Transition of Round Billet Continuous Casting

Grade transitions in continuous casting can significantly improve casting machine productivity and reduce production costs. Accurate prediction of the mixing zone length is essential. A two‐dimensional transient model for grade transition in continuous casting is developed by integrating fluid flow, thermosolute transfer, and solidification. The model predicts the mixing zone changes at various casting speeds. The results indicate that positive segregation of the old steel (Q355NE) occurred at the billet's center, while the maximum negative segregation appears in the billet shell region. The process involves pausing the solidification of the grade transition connectors and the billet shell before casting is resumed with the introduction of a new steel (42CrMo). The extent of the mixing zone is determined by the carbon concentration at the centerline and 1/2 R. Numerical simulations of the temperature field and solute distribution trends are closely aligned with experimental data, validating the accuracy of the solute transport model. Although excessively slow speeds may disrupt the straightening process, reducing the casting speed and decreasing the mixing zone size. This study result provides theoretical guidance for the grade transition in large section round billet continuous casting.

Development of a High-Speed Precision Ultrasonic-Assisted Spindle for Ultra-Precision Optical Mold Machining.

Ultrasonic vibration-assisted grinding is a critical method for machining ultra-hard optical molds. However, current ultrasonic-assisted grinding spindles, as essential foundational equipment, face limitations in maintaining ultra-high rotational speed, high precision, and a compact structure during ultrasonic operation. This study presents a novel ultra-precision ultrasonic-assisted high-speed aerostatic spindle for grinding ultra-hard optical molds, developed through theoretical calculations, FEM, and CFD simulations. The spindle features a simple and compact design (φ60 mm outer diameter × 194 mm length), operates at an ultrasonic frequency of 41.23 kHz, and is driven by an impulse turbine providing torque up to 50.4 N•mm, achieving speeds exceeding 40,000 r/min. Aerostatic bearings provide axial and radial load capacities of 89 N and 220 N, respectively. The results demonstrate that the proposed high-speed precision ultrasonic spindle exhibits both feasibility and potential for practical application.

Production of improved quality steel in highscale basic oxygen furnaces using vacuum treatment

The article presents the results of the converter steel technology development using ladle treatment including portion vacuum degassing at vessel UPVS-350 and pouring at continuous casting machine. In order to improve the quality of metal products, steels of grades 3sp, 08sp, 20k, 20sp, 09G2S, 10G2S1D, 09G2S, 08GT, 17G1SU, 17G1S, 17GS, 10HSND, 15HSND, E36, pipe steels of type 09G2FB were treated by vacuum. Steel was smelted in basic oxygen furnaces with a capacity of 350 ton using technical pure oxygen (99,2–99,5% О2). The article shows that with a UPVS-350 vacuum chamber dilution to133 Pa (1 mm Hg), a metal portion weight of 20–40 tons, the number of vacuum ing cycles less than 25 and a circulation coefficient from 2 to 5, a degree of oxygen removal of up to 40%and hydrogen up to 50% can be achieved. There is an improvement in the pouring ability of vacuum treated steel, a decrease in the axial discontinuity (stratification)at the central part of the slabs from 3 to 2–2.5 grades, decrease of the nonmetallic inclusions content in the billets by 0,2–2,3 grade and their distribution in the volume of metal is more uniform. When exhaustion in a vacuum chamber reach of 1–2 mm Hg level, the impact toughness and elongation of steel in crease. For carbon steel, the production of inappropriate quality metal according to the ultrasonic control decreased by about 3 times (from 0,39 to 0,12%), and the total degree of the rejected metal decreased from 1,06 to 0,65%. During vacuuming of 08GT steel using for chemical reactors, there is a more compact and greater uniformity of the ferrite-perlite structure with the value of the actual grain no. 7–9. The internal structure at the liquation central zone of the sheets produced of this steel is also improved

Fracture resistance of the deposited metal under dynamic and cyclic loading

Analyses of experimental data are presented that enable the fracture resistance assessment of dynamically and cyclically loaded materials used for the manufacture and surfacing of rollers in continuous casting machines for beam blanks and crimping mill rollers. It has been noted that steels for manufacturing and surfacing of crimping rolls with different carbon content and alloying elements, differ in the determination fraction of the crack nucleation work in the integral value of the impact strength. The value of that fraction is much higher for corrosion-resistant steels of the Cr13 type which are also distinguished by high fracture resistance to cyclic loading. It is shown that the properties of these steels make it possible, along with the use of CCM rollers for surfacing, to recommend them for hardening the rollers in crimping mills. The possibility of an additional increase in the efficiency of the crimping rolls by eliminating uneven wear along the length of the barrel by surfacing a layer of Cr13 steel with a variable carbon content (0.10-0.25 %) is considered.

General Industrial Process Optimization Method to Leverage Machine Learning Applied to Injection Moulding

ABSTRACTThe development of machine learning (ML) technologies is driving changes across many sectors. In industrial settings, this is called the fourth industrial revolution and encompasses several technologies pushing the boundaries of industrial automation. In this study, a general industrial process optimization (GIPO) methodology is formulated in the context of Industry 4.0 and tested on an industrial injection moulding machine (IMM). GIPO aims to encourage the practical inclusion of industrial artificial intelligence at all levels of the manufacturing process, while enabling industrial equipment to adapt to a changing processing environment. Special attention is given to the generality of the methodology so that it can be extended to other applications. In the example case study presented here, GIPO combines K‐nearest neighbours classification and nearest neighbours optimization methods to optimize an injection moulding process effectively. Practical implementation conducted on the IMM demonstrates a novel methodology to leverage data mining and ML methods in a real‐world setting to improve production quality, production time and energy cost.

Towards High-Quality Investment Casting of Ti-6Al-4V with Novel Calcium Zirconate Crucibles and Optimized Process Control

The investment casting of titanium and its alloys relies on a high resistance of the crucibles and shell molds in terms of temperature and reactivity. The availability of ceramic crucibles that offer sufficient resistance to the titanium melt enables vacuum induction melting (VIM). CaZrO3 prepared from a mixture of CaO and ZrO2 as a raw material for refractory ceramics shows a high corrosion resistance against metallic melts even under very high temperatures up to 1800 °C. Crucibles and shell molds of CaZrO3 were successfully produced and used in subsequent casting trials. This study is focused on the refractory crucibles suitable for casting Ti-6Al-4V (Ti-64) using a tilt casting machine. In order to evaluate the crucible reaction and, therefore, the quality of the castings, chemical analyses, investigations of the microstructures and hardness measurements were carried out. Careful control of the melting duration is mandatory to avoid crucible reactions that otherwise result in contamination of the cast with oxygen and zirconium. This was achieved by modified coil geometries. Under optimized casting conditions, the oxygen and zirconium impurity limits of ASTM B367-09 for titanium castings were met. Based on the correlations found, optimized casting parameters with regard to material quantity, coil geometry and heating power could be determined in order to provide guidance for a high-quality casting process with VIM.

Thermal stability and anti-ablation performance of plasma spray coated-YSZ on Al2TiO5 modified novel ablative carbon-phenolic composites

Abstract Despite ongoing challenges, ablative thermal protection systems are among the most promising methods for safeguarding spacecraft during re-entry thermal protection systems (TPS). A novel aluminium titanate (Al2TiO5/AT) and a highly efficient thermal barrier of coating (TB/TBCs) made from yttria-stabilized zirconia (YSZ), powder, but deposited using the plasma spray technique on polyacrylonitrile (PAN)-based carbon fiber fabric(C)-reinforced with resorcinol phenol formaldehyde resin (RF) composites (C-RF)) would be a potential candidate for TPS applications. This study investigates the composites with varying wt.% of AT that were developed, namely 0 wt.% (YSZ-C-RF), 1 wt.%, 3 wt.%, and 5 wt.% (YSZ-AT-C-RF) by utilizing a hot press moulding machine. Thermal stability and ablation performance of unmodified C-RF with modified YSZ-C-RF and YSZ-AT-C-RF composites are examined through thermogravimetric analysis (TGA) and oxyacetylene torch test/OAT (4.0 MW/m2 for 60 sec). Also, the phase composition and microstructure of the ablated surface are determined by X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The TBC of YSZ has an obvious influence on the residual weight ratios at high temperatures in C-RF and also plays a positive role in increasing thermal stability under nitrogen atmosphere for enhancing ablation resistance concerning YSZ-C-RF. The mass and linear ablation rates (MAR and LAR) of the composites after modifying the surface by YSZ-coated particles are reduced by 82.98% and 15.65%, respectively. Similarly, the introduction of AT particles and TBC of YSZ results in evidence of improving the thermal stability and the ablation resistance in varying wt.% of YSZ-AT-C-RF composites. The primary optimum AT weight loading for enhancing ablation resistance in YSZ-C-RF composites is 1wt.%. The modification of 1wt.% AT particles and YSZ-Coated particles reduce MAR and LAR by 54.79% and 61.94%, respectively. This work offers a meaningful method to remarkably enhance the ablation performance of the modified C-RF and YSZ-AT-C-RF composites.

The behaviour of micro-injection moulding inserts produced with material jetting technology

The increasing interest in additive manufacturing and advancements in precision and production quality have sparked attention to its use in industrial prototyping. High-performance polymer resins enhance flexibility in mass production processes like micro-injection moulding. This flexibility allows for reconfigurable moulds using resin inserts, enabling the transition of devices, such as microfluidics, from labs to large-scale production. Despite progress, limitations exist in additive manufacturing, including the minimum size of microstructures and the brittle behaviour of resin inserts during moulding cycles, impacting overall production capacity. This study focuses on using a micro-injection moulding machine to reproduce PMMA thin plates with single straight microchannels (250 μm) and with different side wall angles (0°, 15°, and 30°), investigating the best compromise between capability and insert resistance to moulding cycles. A careful study of the dynamics leading to the insert failure and the resin limits was carried out. The results showed that it is possible to produce about 15 micro-structured thin plates with good accuracy using a resin insert realised with Material Jetting technology.

Multiple objectives optimization of injection-moulding process for dashboard using soft computing and particle swarm optimization

This research focuses on utilizing injection moulding to assess defects in plastic products, including sink marks, shrinkage, and warpages. Process parameters, such as pure cooling time, mould temperature, melt temperature, and pressure holding time, are carefully selected for investigation. A full factorial design of experiments is employed to identify optimal settings. These parameters significantly affect the physical and mechanical properties of the final product. Soft computing methods, such as finite element (FE), help mitigate behaviour by considering different input parameters. A CAD model of a dashboard component integrates into an FE simulation to quantify shrinkage, warpage, and sink marks. Four chosen parameters of the injection moulding machine undergo comprehensive experimental design. Decision tree, multilayer perceptron, long short-term memory, and gated recurrent units models are explored for injection moulding process modelling. The best model estimates defects. Multiple objectives particle swarm optimisation extracts optimal process parameters. The proposed method is implemented in MATLAB, providing 18 optimal solutions based on the extracted Pareto-Front.

Analysis of noise characteristics of metal processing equipment

The management and prevention of industrial injuries among workers are crucial in the work environment. Industrial injuries occur in various forms and have diverse causes, and noise-induced hearing loss accounts for a significant proportion of workplace injuries. Therefore, this study aimed to measure the factory noise during engine-component (metal) processing for automobiles, where substantial noise-induced hearing loss is prevalent. The measurement results revealed that the 24-h equivalent continuous noise level (Leq) was approximately 83.8 dB(A), and the noise at two points was higher than the noise exposure standard of 89 dB(A). These points were identified as locations where 2,200- to 3,500-ton casting machines were positioned on both sides to melt iron to produce components. The noise generated from each machine is assumed to have combined at these points, resulting in elevated noise levels. The results were plotted on a noise rating (NR) curve. The NR values ranged from 81 to 83, surpassing the standard NR range of 60 to 70 that is commonly used in typical workplaces. The frequency band that determined the NR was 2 kHz. Therefore, measures such as the use of porous sound-absorbing materials should be considered to attenuate the frequency range based on the noise characteristics.

STUDY OF THE SEAMLESS PIPES PROPERTIES OBTAINED FROM A HOLLOW BILLET

The article researched the influence on the pipes mechanical properties initial billet obtained by the traditional method and the proposed method, in which the piercing process is excluded. The proposed method involves casting the initial billet for the production of seamless pipes with a cavity obtained on a continuous casting machine. The production of hotrolled seamless pipes from a hollow billet is an urgent issue today, since central porosity and axial segregation after casting are excluded, affecting the quality of the pipes obtained in the subsequent stages of production: rolling on a mandrel mill and reducing. The possibility of producing seamless hot-rolled pipes from a hollow billet is substantiated, providing the necessary set of mechanical properties that are regulated by the standards GOST 632-80, GOST 633-80 and API 5CT. The result is a minimal deviation of the mechanical properties of steel samples obtained by double deformation of a hollow continuously cast billet from samples obtained according to the traditional scheme, including the piercing process. Keywords: hollow billet, steel, 09Mn2Si, seamless pipe, piercing process.

DETERMINATION THERMAL AND MECHANICAL PROPERTIES OF NANO CARBON, GRAPHITE AND GRAPHENE REINFORCED RECYCLING POLYPROPYLENE COMPOSITE SAMPLES

Polymer-based plastic materials occupy a major place in daily life. However, due to the nature of polymer materials, low thermal resistance and mechanical properties of these products, the need for new and sustainable materials in the industry has increased. With the rapid technological developments in advanced manufacturing industries such as aviation, marine, motor sports and defence industry, lightweight and high-strength composite products have become even more important. In this context, in this study, 1% carbon, graphene and graphite particle reinforced Polypropylene (PP) composite material mixed in a twin-screw extruder and MA/G series injection moulding machine standard tensile test sample produced. Melt Flow Index (MFI), Heat Deformation Test (HDT), tensile test, Shore-D hardness measurement and density tests performed on these test samples. According to the results obtained from these tests, the mechanical and thermal properties of the test samples produced from different composite materials were determined. The best mechanical and thermal properties occurred in the graphene particle. It formed in graphite and carbon, respectively.

The Integration of Advanced Mechatronic Systems into Industry 4.0 for Smart Manufacturing

In recent years, the rapid advancement of digital technologies has driven a profound transformation in both individual lives and business operations. The integration of Industry 4.0 with advanced mechatronic systems is at the forefront of this digital transformation, reshaping the landscape of smart manufacturing. This article explores the convergence of digital technologies and physical systems, with a focus on the critical role of mechatronics in enabling this transformation. Using technologies such as advanced robotics, the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, industries are developing intelligent and interconnected systems capable of real-time data exchange, distributed decision making, and automation. The paper further explores two case studies: one on a smart plastic injection moulding machine and another on soft robots. These examples illustrate the synergies, benefits, challenges, and future potential of integrating mechatronics with Industry 4.0 technologies. Ultimately, this convergence fosters the development of smart factories and products, enhancing manufacturing efficiency, adaptability, and productivity, while also contributing to sustainability by reducing waste, optimising resource usage, and lowering the environmental impact of industrial production. This marks a significant shift in industrial production towards more sustainable practices.

A Deep Reinforcement Learning Approach to Injection Speed Control in Injection Molding Machines with Servomotor-Driven Constant Pump Hydraulic System

The control of the injection speed in hydraulic injection molding machines is critical to product quality and production efficiency. This paper analyzes servomotor-driven constant pump hydraulic systems in injection molding machines to achieve optimal tracking control of the injection speed. We propose an efficient reinforcement learning (RL)-based approach to achieve fast tracking control of the injection speed within predefined time constraints. First, we construct a precise Markov decision process model that defines the state space, action space, and reward function. Then, we establish a tracking strategy using the Deep Deterministic Policy Gradient RL method, which allows the controller to learn optimal policies by interacting with the environment. Careful attention is also paid to the network architecture and the definition of states/actions to ensure the effectiveness of the proposed method. Extensive numerical results validate the proposed approach and demonstrate accurate and efficient tracking of the injection velocity. The controller’s ability to learn and adapt in real time provides a significant advantage over the traditional Proportion Integration Differentiation controller. The proposed method provides a practical solution to the challenge of maintaining accurate control of the injection speed in the manufacturing process.

Selection of internal design of crystallizer sleeves for continuous casting of 200 mm billets

The crystallizer is the most critical and most important functional unit of a continuous casting machine (hereinafter referred to as CCM). It is the main technological unit of the CCM, an assembly for removing heat during the solidification of the solidifying metal and the formation of the ingot. The main requirement for the crystallizer is to provide maximum heat removal from the solidifying steel to the cooling water, and to obtain a strong ingot shell with a good surface at the outlet of the crystallizer, which would not be destroyed by the heat of the liquid phase and the ferrostatic pressure. During the reconstruction of the CCM by the contractor company, drawings of crystallizers and crystallizer sleeves with a double‑cone internal geometry for casting 200 mm continuous cast billets were developed. The 200 mm continuous cast billet is a billet for the production of hot‑rolled seamless steel pipes. During the operation of the crystallizer sleeves with a double‑cone internal geometry, an accelerated wear of the protective coating in the lower part of the sleeve was noted, as well as an increased rejection of hot‑rolled pipes due to defects on the outer surface of the pipes. In order to identify the cause of the defect formation, complex metallographic studies of the outer surface of the pipes were carried out. As a result of the metallographic study, surface defects classified as steel mill scale on the outer surface of the pipes were identified. To minimize the “steel mill scale” defect and reduce the wear of the protective coating of the crystallizer sleeves, work was carried out to select the optimal conditions for the crystallization of the continuous cast billet: the use of crystallizer sleeves with a three‑cone internal geometry compared to a double‑cone was investigated; maintaining the temperature difference of the water at the inlet and outlet of the crystallizer within specified limits (ΔT) was tested. It was found that the use of a crystallizer sleeve with a three‑cone internal geometry for casting 200 mm billets and the stable behavior of the ΔT parameter made it possible to ensure the required quality of the surface of seamless pipes, reduce the wear of the protective coating of the crystallizer sleeves and increase the productivity of the CCM.

Comparative Analysis of the use of Band Heaters and Infrared Heaters to Save Energy on Injection Molding Machines Type Borche Bi 320T

This study aims to compare the energy efficiency between the use of a heater band and an infrared heater on an injection molding machine type borche bi 320T. The injection molding machine is one of the main pieces of equipment in the manufacturing process of plastic products and plays an important role in shaping various consumer and industrial products. One of the critical aspects of the operation of injection molding machines is the significant energy consumption, especially related to heating. This study was conducted by measuring the energy consumption of both types of heaters under the same operational conditions. The results showed that the energy consumption of using a band heater was 46.9 kW, while the infrared heater was 38.9 kW, significantly more energy efficient by 17.1% compared to the band heater. Although the initial installation cost of the infrared heater is 87% higher than that of the band heater, the energy savings generated from the infrared heater can reduce operating costs by approximately $39 million per year. Higher energy efficiency means lower electricity costs and, thus, more efficient total production costs. The use of infrared heaters also has a positive impact on the environment. Reduced energy consumption means reduced greenhouse gas emissions from power generation. Therefore, besides the economic benefits, the use of infrared heaters is also in line with sustainability and environmentally friendly practices.

Multi-grooved channel design in continuous casting mold for enhancing heat transfer efficiency considering pressure drop and flow rate loss

An efficient, speedy, multi-grooved (ESMG) mold was designed and manufactured for optimization to address issues such as low heat transfer rate, slow casting speed, and quality defects in traditional continuous casting molds. The flow resistance mechanism of multi-grooved channels with varying parameters was investigated by considering the ESMG geometric model, the convective heat transfer characteristic variation trends were revealed with different channel designs. Considering constraints of the dimensional chain and supply pressure, variation trends and mechanisms of the pressure drop, flow rate loss, and convective heat transfer coefficient of the ESMG mold were explored using multiple channel variables. Based on the numerical model of the ESMG channel, temperature variation trends in the copper mold were verified by comparison with relevant literature data, supporting the convective-heat-transfer model and variation trends of the ESMG mold. A high-efficiency heat-transfer ESMG assembly that casts U71Mn high-carbon large rectangular billets was fabricated, achieving a closed-loop dimensional chain and replacing traditional molds. Experimental validation on the continuous casting machine (CCM) proved directly that redesigning the ESMG mold cooling channel improved heat transfer efficiency and reduced CO2 emissions. After 504 h on the CCM, the ESMG mold casting speed increased from 1.1 to 1.6 m/min, the heat transfer efficiency was 17.6% higher than that of traditional molds and CO2 emissions were estimated to decrease by 31.2%. The billets produced by the ESMG mold had no quality defects in shape or surface with the original casting conditions, which provided enhanced support for accelerating continuous casting lines.

Improved Design and Fabrication of a Compression Moulding Machine with Performance Evaluation

This study explores the advancements in the design and performance of an improved compression moulding machine aimed at efficiently recycling various plastic wastes, with an emphasis on Polyethylene Terephthalate (PET). With global plastic waste accumulation posing severe environmental challenges, enhancing recycling technologies is imperative. The re-designed machine was tested at operating temperatures of 200°C, 250°C, and 300°C, highlighting the critical role of temperature and processing duration in determining product quality. Theoretical heating times were found to be shorter than actual times due to real-world inefficiencies such as heat loss and thermal conductivity variations. Weight loss during heating, attributed to the evaporation of volatile components and thermal degradation, was observed. The formation of air pores in samples with extended heating times underscored the necessity for precise process control. The PET melting process initiated effectively at approximately 250°C. The improved machine demonstrated significant potential in enhancing recycling efficiency and versatility.

Fault diagnosis method for continuous casting machine’s sector segment based on SG-PCA-LSTM

Abstract To address challenges such as the high variability of variables and difficulties in feature extraction during the casting process of the continuous casting machine’s sector segment, a fault diagnosis method based on SG-PCA-LSTM is proposed. This method aims to overcome the issue of fault features obscured by noise in the total tension time series by employing the SG smoothing algorithm for filtering and denoising. By leveraging the inter-segment data correlation and the advantage of PCA in extracting fault feature information, combined with the powerful learning capability of LSTM in modeling, a Principal Component Analysis - Long Short-Term Memory (PCA-LSTM) fault diagnosis model is established. Through comparative analysis against different diagnostic methods in terms of recognition rate, false positive rate, etc., the results obtained by this method are compared against those obtained by using other algorithms. Experimental results demonstrate that the proposed method exhibits good overall performance in terms of accuracy and training time.