Abstract: In a sheet lamination three-dimensional modeling method and apparatus, a three-dimensional object is formed in a stacked body by the repetitive operations of stacking and gluing a material sheet on an intermediate stacked body and cutting the material sheet in a cutting plane along the contour of each section shape at the cutting plane of the three-dimensional object. A remainder portion of each material sheet which portion does not constitute any section shape of the three-dimensional object is cut along plural intersecting division lines whose positions are shifted in turn in dependence on the position of each material sheet in a direction of stacking the material sheet so that an unnecessary portion of the stacked body except the three-dimensional object can be divided into plural pieces also in the direction of stacking the material sheet thereby to become small solid blocks and can be removed easily and speedily from the formed three-dimensional object.

Abstract: A numerical controller includes a control section for controlling operation of a machine, an application section which is separated from the control section and adapted to input data into the control section and to monitor a control status, and a communication network for connecting the control section and the application section. This structure makes it possible to reduce the overall size of the numerical controller. A program for a new function or an abnormality diagnosis program is also transmitted from the application section to the control section when required.

Abstract: An apparatus for detecting a residual grinding amount includes first and second feelers adapted to contact the peripheral surface of a workpiece such that they move, in accordance with a variation in the diameter of the workpiece, in opposite directions each perpendicular to the direction of deflection of the workpiece, and a first displacement detector for detecting relative displacement between the first and second feelers. The apparatus also includes a third feeler adapted to contact the peripheral surface of the workpiece such that it moves, in accordance with the variation in the diameter of the workpiece as well as a variation in the deflection of the workpiece, in the direction of deflection of the workpiece, and a second displacement detector for detecting displacement of the third feeler. The residual grinding amount is calculated based on the displacements detected by the first and second displacement detectors.

Abstract: In a method and apparatus for grinding a workpiece, a rotating workpiece and a rotating grinding wheel are relatively moved toward and away from each other, and at least first and second grinding steps are performed at high and low infeed rates, respectively. Further, back-off grinding is performed between the first and second grinding steps. A target workpiece diameter to be obtained at the end of the back-off grinding is first provided. During the rough grinding, prediction is repeatedly performed to obtain a workpiece diameter which would be obtained at the end of the back-off grinding if the back-off grinding were started instantaneously. The workpiece diameter is predicted taking account of a delay in the movement of the grinding wheel. The back-off grinding is started when it is judged that the predicted workpiece diameter becomes equal to the target workpiece diameter.

Abstract: An intelligent machining system employs a neural network for calculating machining conditions on the basis of attribute data or a workpiece and a grinding machine. The system comprises a reference machining condition calculating unit, a neural network which receives the attribute data and provides corrections, and a correcting unit for correcting the reference machining conditions by using the corrections. Corrections which cannot be determined by means of empirical expressions or theoretical expressions are determined appropriately by the neural network previously learned. The system determines corrections for the machining conditions on the basis of machining errors decided by a neural network. The system also detects time-series machining phenomena by sensors, processes the output detection signals of the sensors by a neural network to obtain machining circumstance data. The feed rate of the tool is controlled by a fuzzy inference on the basis of the machining circumstance data.

Abstract: An apparatus capable of automatically determining grinding wheel dressing timing for dressing a grinding wheel. The apparatus estimates the abrasion of the grinding wheel in a grinding cycle on the basis of machining data and grinding conditions, and divides the grinding cycle into a plurality of stages according to the estimated abrasion to carry out grinding wheel dressing after the completion of every stage of the grinding cycle. In grinding a workpiece having a plurality of ground sections, the abrasion of the grinding wheel in grinding each ground section is estimated, and the abrasion is accumulated in accordance with grinding sequence. A ground section after grinding which grinding wheel dressing is to be carried out is determined on the basis of the cumulative abrasion. Similarly, the abrasions are accumulated for each of workpieces. A grinding wheel dressing is carried out after the completion of grinding a workpiece so that the cumulative abrasion may not exceed a predetermined value.