Effect of SEN immersion depth on mold flow profile and slag entrapment during continuous casting of steel

Mold flux entrapment during continuous casting of steel contributes to both surface and sub-surface defects in the final product. Continuous casting operating parameters such as casting speed, SEN immersion depth, SEN port geometry, argon flow, and mold EMS significantly affect the mold flow conditions and flow profile. During continuous casting operation, SEN immersion depth is continuously varied to avoid localized erosion of SEN, and it impacts the flow dynamics in the mold. In the present work, water modeling studies were carried out for a wide range of mold widths (1200-1800 mm) and casting speeds (0.8-1.4 m/min) on a 0.5 scaled down water model to optimize casting speed for different combinations of SEN immersion depth and mold width. Results from water modeling were further validated using nail board studies in the actual plant. A safe operating matrix was identified from these experiments to avoid mold slag entrapment during continuous casting.

Analysis and Design of Lattice Structures for Rapid-Investment Casting

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.

Mold Flow Analysis of Motor Core Gluing with Viscous Flow Channels and Dipping Module

A motor core is formed by stacking iron sheets on top of each other. Traditionally, there are two stacking methods, riveting and welding, but these two methods will increase iron loss and reduce usage efficiency. The use of resin is the current developmental trend in the technology used to join iron sheets, which has advantages including lowering iron loss, smoothing magnetic circuits, and generating higher rigidity. The flow behavior of resin in gluing technology is very important because it affects the dipping of iron sheets and the stacking of iron sheets with resin. In this study, a set of analytical processes is proposed to predict the flow behavior of resin through the use of computer-aided engineering (CAE) tools. The research results are compared with the experimental results to verify the accuracy of the CAE tools in predicting resin flow. CAE tools can be used to predict results, modify modules for possible defects, and reduce the time and costs associated with experiments. The obtained simulation results showed that the filling trend was the same as that for the experimental results, where the error between the simulation results for the final dipping process and the target value was 0.6%. In addition, the position of air traps is also simulated in the dipping process.

Using Recognizable Fuzzy Analysis for Non-Destructive Detection of Residual Stress in White Light Elements

The phenomenon of residual stress in optical lens injection molding affects the quality of optical devices, with the refractive errors that are caused by geometric errors being the most serious, followed by the reduced accuracy and function of optical components; it is very important to ensure that the lens geometry remains intact and that the refractive index is reduced. This paper uses a photoelastic stress compensation method for measurement verification along with fuzzy theory to reorganize a set of processes that can be used to evaluate the residual stress of a product, whereby the use of corresponding theoretical formulas can effectively quantify and measure the residual stress of the product. A mold flow simulation is used to analyze the molded optical components and determine the feasibility of evaluating the quality of the lens. Through the measurement of the refractive stress value of the optical components, the molding quality of the lens can be improved, and its force distribution effects can be investigated. Geometric analysis and shear stress affect the performance of optical components, and these errors may also cause irreparable problems during secondary processing. Therefore, it is crucial to reduce the residual stress of optical components. When the stress distribution is uniform and the internal melting pressure is reasonably configured, the product’s shrinkage rate can be controlled; the method for determining the residual stress is the core theme of this research.

Study on Mold Flow Analysis and Injection Product Verification by Analysis of Variance and Response Surface Method - Taking Toothbrush as an Example

With the advancement of technology, plastic products are inseparable in our environment, and the impact of the plastics industry on us is gradually increasing. Although Taiwan's plastics industry has been progressively added to mold flow analysis and automation, there are still some areas in the manufacturing process that can be optimized. In the process of slit-shaped materials, bending and deformation have a very large impact on the finished product, which is a major issue at the technical level. In this study, a toothbrush was taken as an example to find the best combination of injection molding parameters. The research process was studied from CAD mold design, CAE mold flow analysis, injection molding parameter analysis, mold opening, product injection and measurement, and the results were verified. Among them, the injection pressure, dwell time and holding pressure are used as the Taguchi factor, and the CAE mold flow analysis is performed by the direct cross table L16 (45) combination to find a small amount of warpage, and the Taguchi method and the reaction surface method are used to find out the best combination of parameters. After the final product was shot and the dimensions and simulation were compared with each other, the data showed that the amount of warpage of the finished product was 0.0892 mm, and the error with the analog value was 0.0212 mm, which confirmed that the injection molding parameters were reliable.