A system and method for improving additive manufacturing, including additive manufacturing toolpaths, is provided. The system and method includes a toolpath generator that obtains initial toolpaths of an object, identifies isolated paths in the toolpaths, and adds bridge connections between neighboring isolated paths in each layer to improve the toolpaths. The bridge connections facilitate the continuous and non-stop deposition of each layer according to improved toolpaths during additive manufacture, which can reduce total deposition time and improve the resultant additive manufacture.

A machine tool includes three mutually independent data transmission mechanisms. The data transmission mechanisms include respective transmission units which assign codes for detecting errors to data acquired from the output of sensors, and which transmit the data. A machine controller includes an operation judgment unit which judges whether operation of a feed axis motor is continued. The operation judgment unit judges that operation is continued when there are two pieces of data for which a relationship between the data and the code matches a rule, and the two pieces of data are within a predetermined judgment range. The operation judgment unit judges that the feed axis motor is stopped when at least one of the pieces of data for which the relationship matches the rule deviates from the judgment range.

A system and an apparatus capable of independently driving movers are described herein. The system and apparatus includes: a track that forms a path for movers; a plurality of movers movably mounted on the track for moving along the path; and a plurality of drive elements fixedly arranged along the track. The drive elements each have a surface that is oriented to contact a driven member of the movers. The drive elements are configured to sequentially engage the driven member of a plurality of the movers to provide controlled independent motion of the movers along the track. The drive elements may be driven by rotary motors. A method of independently driving movers is also described herein.

A system and an apparatus capable of independently driving movers are described herein. The system and apparatus includes: a track that forms a path for movers; a plurality of movers movably mounted on the track for moving along the path; and a plurality of drive elements fixedly arranged along the track. The drive elements each have a surface that is oriented to contact a driven member of the movers. The drive elements are configured to sequentially engage the driven member of a plurality of the movers to provide controlled independent motion of the movers along the track. The drive elements may be driven by rotary motors. A method of independently driving movers is also described herein.

A simulation method for milling by use of a dynamic position error includes the steps of: (a) generating a milling surface from a numerical control code, the milling surface having a plurality of grid points, the numerical control code having a position command; (b) calculating a normal vector for each of the plurality of grid points on the milling surface; (c) feeding back a position feedback of each of the plurality of grid points by the controller of the machine tool, and deriving a corresponding three-axis dynamic position error of the milling surface according to the position command and the position feedback; (d) calculating a component of the normal vector for the three-axis dynamic position error so as to obtain a normal-vector error value of the corresponding grid point; and, (e) displaying undercutting information of the normal-vector error value of the corresponding grid point on the milling surface.

In described examples of methods and control systems to control a position and/or velocity of a machine, control circuitry is coupled to receive and dither a control signal, and to compute a control output value according to the dithered control signal and a control function. An inverter is coupled to the control circuitry, to control the position and/or velocity according to the control output value.

A servo controller calculates an alternative movement amount, in a control cycle (n) in which a command cannot be received from the host controller, according to jerk calculated with reference to amounts of movement used for controlling the servomotor in former control cycles before the control cycle (n) and the movement amount used for controlling the servomotor in the previous control cycle before the control cycle (n). The servo controller controls movement of the servomotor by use of the alternative movement amount in the control cycle (n) in which the command cannot be received from the host controller.

A machine learning device, performing machine learning for adjusting a position and a length of a welding part when a core is welded to a workpiece in a wire electric discharge machine, acquires the position and the length of the welding part as state data; sets reward conditions; calculates a reward based on the state data and the reward conditions; performs the machine learning of the adjustment; determines and outputs an adjustment target and its adjustment amounts based on the state data and a result of the machine learning; performs the machine learning of the adjustment based on the output adjustment action, the state data acquired based on the recalculated position and the recalculated length of the welding part, and the reward based on the state data; and outputs an optimum position of the welding part, the reward conditions being set as a positive or negative reward.

A machine learning device, performing machine learning for adjusting a position and a length of a welding part when a core is welded to a workpiece in a wire electric discharge machine, acquires the position and the length of the welding part as state data; sets reward conditions; calculates a reward based on the state data and the reward conditions; performs the machine learning of the adjustment; determines and outputs an adjustment target and its adjustment amounts based on the state data and a result of the machine learning; performs the machine learning of the adjustment based on the output adjustment action, the state data acquired based on the recalculated position and the recalculated length of the welding part, and the reward based on the state data; and outputs an optimum position of the welding part, the reward conditions being set as a positive or negative reward.

A servo movement control method, device, and terminal device are provided. The method includes: controlling an output shaft of the servo to rotate according to a first motion instruction; detecting whether a second motion instruction is received within a first preset time period, and re-planning a second target motion curve to a second target end position from a corresponding target position on a first target motion curve when receiving the second motion instruction; and controlling the output shaft to rotate from an actual position when receiving the second motion instruction to the second target end position according to the second target motion curve. When the second motion instruction is received, the servo is controlled to rotate from the target position to the second target end position according to the second motion instruction, so that the servo is switched from the first motion instruction to the second motion instruction smoothly.