Search

Because of product miniaturization, demand for cups created by deep drawing has increased. However, because thin sheet materials exhibit poor deep drawing formability, using deep drawing on micro/meso cups is rather difficult. In this study, punch surfaces with microridges were used to enhance deep drawing formability. The concept was based on the observation that punch surfaces with microridges near the punch nose could disperse the drawing force of punches on sheet materials and delay the cracking of sheet materials. In this study, cylindrical cups composed of copper alloy were used. First, punch surfaces with microridges were designed and the Deform 2D software was used for analyzing the formability of deep drawing by using punch surfaces with and without microridges. Second, drawing dies were designed and produced, and an experiment was conducted to verify the results of the analysis. The study results indicated that commercial forming analysis software can be used to simulate the effect of microridges on deep drawability accurately. A comparison between the two punch surface types revealed that punch surfaces with microridges exhibited a slightly increased drawing force (3%) compared with those without microridges. Concurrently, the effect of punch surfaces with microridges increased forming height by at least 100%.

A flexible die forming process is proposed to form aluminum micro channels with channel widths not larger than 1 mm. Three micro channel dies and two different polyurethanes (40A and 90A) were used to form micro channels on the annealed and as-received aluminum foils (50 and 75 μm). For understanding the influences of size effects, polyurethane hardness and channel width on forming micro channels, a series of experiments were conducted. Through using different annealing conditions, different grain sizes were obtained such that different T/D, the ratio of thickness and average grain size, could be obtained. T/D ratio is used as a parameter to model the size effects in the two models proposed in this paper. These two models can predict the depths of the micro channels formed by the proposed process, so they can be used by industry as a design tool for product design, process design and development, annealing process, etc.

Springback will occur when the external force is removed after bending process in sheet metal forming. This paper proposed an adaptive-network-based fuzzy inference system (ANFIS) model for prediction the springback angle of the SPCC material after U-bending. Three parameters were selected as the main factors of affecting the springback after bending, including the die clearance, the punch radius, and the die radius. The training data were obtained from results of U-bending experiment. The training data with four different membership functions – triangular, trapezoidal, bell, and Gaussian functions – were employed in the ANFIS to construct a predictive model for the springback of the U-bending. After the comparison of the predicted value with the checking data, the results show that the triangular membership function has the best accuracy, which make it the best function to predict the springback angle of sheet metals after U-bending.

The design of progressive dies is a very knowledge-intensive, complex, and time-consuming process. This paper describes a computer-aided structural design system for progressive dies with drawing, bending, and punching operations. Taking advantage of a pre-built design knowledge and database, this system is able to output designs of the main and standard parts of a progressive die upon users inputting a minimum set of design information. Our system is implemented on top of CATIA V5 software and uses its built-in modules, including Part Design, Assembly Design, and Knowledge Advisor. Our system also consists of an inference engine and a user interface. The experimental results show that our system successfully reduced the design time from about seven working days to within 2 h for the structural design of the main and standard parts of a progressive die of an upper shell for a mobile phone, which can dramatically save on design time and cost and also provide excellent design quality.

The needs of stainless steel 304 micro cups have been increasing tremendously due to the trend of miniaturization in medical and electronic devices, etc. For application purpose, it is highly desired to have stainless steel micro cups with high CH/OD (cup height/outer diameter) ratios. Due to the constraints of the limit draw ratio (LDR) of stainless steel 304 sheets in micro deep drawing, forming a micro cup with high CH/OD ratio at room temperature cannot be achieved by using a single stage deep drawing die. A process consisting of one micro deep drawing and two ironing stages was proposed for achieving this goal; three micro dies were designed, fabricated and used for experimental validation. A series of experiments were conducted by using the stainless steel 304 sheets of 200 μm thickness annealed at four different temperatures to understand the influence of size effects on this process for generating knowledge, know-how and technologies to form high quality stainless steel micro cups with large CH/OD ratio. No lubricant was used in this study. It was proven that the proposed process is a robust process as long as the sheets are annealed at the temperature no less than 900 °C for more than 3 min.

Springback will occur when the external force is removed after bending process in sheet metal forming. This paper proposed an adaptive-network-based fuzzy inference system (ANFIS) model for prediction the springback angle of the SPCC material after U-bending. Three parameters were selected as the main factors of affecting the springback after bending, including the die clearance, the punch radius, and the die radius. The training data were obtained from results of U-bending experiment. The training data with four different membership functions – triangular, trapezoidal, bell, and Gaussian functions –were employed in the ANFIS to construct a predictive model for the springback of the U-bending. After the comparison of the predicted value with the checking data, we found that the triangular membership function has the best accuracy, which make it the best function to predict the springback angle of sheet metals after U-bending.

Most rotators and stators of motors or generators as well as the cores of transformers are produced by laminated plates of electric steel to reduce the energy loss caused by eddy current. Therefore, it is essential to predict as well as improve the shearing quality of the electric steel plates and thus help increase the efficiency of the machines. Most investigations overlook the planar anisotropy in the numerical analysis of the shearing process. The simplified 2-D analysis was adopted instead of the 3-D analysis. In this work, DEFORM 3D analysis is used which takes into account the anisotropy of the plate material. Normalized Cockcroft & Latham damage criterion is used in determining the occurrence of fracture during the shearing. The result shows that the 3-D analysis predicts well in the burnish depth while roughly in rollover due to insufficient resolution of the element size. The 2-D analysis tends to underestimate the burnish depth attributed to the improper selection of lower critical damage values and predicts scattered rollover.

The size effects including the downscaled thickness and grain size presented in the micro‐drawing process were investigated by both the experimental approaches and the finite element analysis. In the present study, experiments were conducted first to establish the stress‐strain relations and r‐values for 304‐O stainless steel sheets with various thicknesses and different grain sizes. The experiment results reveal that the flow stress and r‐value become smaller for downscaled thicknesses and larger grain sizes. The testing results also indicate that the anisotropic properties are dominated by the grain size as the sheet thickness is smaller than 0.2 mm. The micro‐drawing process for producing a vibration motor casing, which bears a circular cylindrical shape, was also examined in the present study. The finite element simulations were performed to evaluate the formability of the multi‐operation drawing process with the initial die design. The forming characteristics were identified and an optimum forming process was then developed. The actual micro‐drawing process based on the finite element analysis was also implemented, and the good agreement between the drawn cups and the finite element simulation results confirms the process design developed in the present study. In addition, the effect of grain size on the micro‐drawing was examined as well in the present study. The finite element analysis reveals that as the sheet thickness is smaller than 0.2 mm, the minimum thickness in the drawn cups was dominated by the r‐value rather than the yield stress.