A wire electric discharge machine includes a machine learning device that learns an adjustment of an axis feed command of the wire electric discharge machine. The machine learning device determines an adjustment amount of the axis feed command by using data related to a movement state of an axis, and adjusts the axis feed command based on the determined adjustment amount of the axis feed command. Subsequently, the machine learning device performs machine learning of the adjustment of the axis feed command based on the determined adjustment amount of the axis feed command, the data related to the movement state of the axis, and a reward calculated based on the data related to the movement state of the axis.

A technique of removing material from metal parts referred to as OPECM and a corresponding OPECM processing machine are disclosed. A tool electrode is manufactured for removing material from a target workpiece, and the workpiece and tool electrode are fixed into a processing machine that imparts an oscillatory motion path or profile and applies a voltage through a flowing electrolyte solution. The disclosed technique and processing machine removes material from the surface of the target workpiece through proximal surface dissolution as the workpiece and tool electrode are brought within proximity of one another.

The invention relates to an ECM system comprising a holder for the arranging of at least one component to be machined and at least one machining station for the electrochemical machining of the at least one component at at least one machining position. The ECM system has a positioning apparatus, which is designed to mount, in a predefined position, a machining platform arranged on the positioning apparatus, and the machining platform comprises at least one machining station having at least one electrode arranged thereon, which electrode can be moved along a machining path in order to machine the at least one component that can be arranged on the holder.