Replacing the material of automobile body panels from steel sheets to aluminum alloy sheets is an approach to reducing the automobile weight. In the press forming of panel parts with aluminum alloy sheets, it is necessary to smooth stepped linear marks of about 5 μm to 50 μm generated during press forming to satisfy the surface quality of the panel parts. These linear marks are called shock lines, which are generated when the blank sheet slides on the die corner radius during press forming. In this research, the protrusion shape of forming dies that enables us to smooth a shock line is investigated using a 1.2-mm-thick 6000 series aluminum alloy sheet. The shock line is smoothed by applying a trapezoidal surface pressure to the blank sheet near the shock line at the bottom dead center. We propose a method of using finite element analysis to calculate the protrusion shape from the amount of elastic displacement of the dies that occurs when the target surface pressure is applied to the dies surface. The protruding shape calculated by the proposed method has been applied to the forming dies for the door inner panel of the 6000 series aluminum alloy sheet. As a result, in our experiments, the shock line has been smoothed by using these forming dies.

Intelligent slide motion control was achieved by using a hydraulic press capable of controlling slide motions in combination with artificial intelligence. Computer-aided engineering (CAE) was used to clarify the factors that cause extrusion defects and slide motions with a high ratio of good products for impact extrusion. Next, experiments were conducted to verify the effect of slide motions with a high ratio of good products, and the results obtained by CAE were confirmed to be correct. Then, a convolutional neural network was constructed with a capability of using the elastic strain of the punch in the extrusion initial stage obtained in the experiments as input data for machine learning to predict the extrusion quality, and this network was implemented in a press machine. We confirmed that when a defect was predicted, the machine automatically switched to a slide motion with a high ratio of good products. By using this intelligent slide motion control, we can change the extrusion of a predicted defective product to that of a good product by adjusting the slide motion to reduce the incidence of defective products.

Electromagnetic crimping is a crimping method for applying uniform crimping force to metal parts in a shorter forming time than conventional press crimping. It is difficult to measure and determine the crimping force acting on metal parts because the crimping force affected by the magnetic field and Lorentz force induced by current in a forming coil is invisible. Additionally, current is affected by the circuit characteristics of an electromagnetic forming instrument and the shape of a forming coil. Hence, it is difficult to design a forming coil. In this study, simulation procedures were developed for designing a forming coil. First, the circuit characteristics of an electromagnetic forming instrument were identified to predict current in a forming coil accurately. Second, electromagnetic crimping was simulated by the coupled analysis of a circuit simulation to consider the effects of circuit characteristics and the finite element method to consider shape of a forming coil. Finally, a forming coil for electromagnetic crimping was designed by using the developed simulation procedures. Required current in the designed coil was determined. The shape of the crimped workpiece in the simulation was similar to an experimentally crimped sample. These results indicate that the developed simulation procedures are useful for designing the shape of a forming coil.