A spindle speed adjusting device in machining is provided, which may include a plurality of signal detection modules, a signal capturing module and a signal processing module. Each of the signal detection modules may keep measuring the vibration signals in machining. The signal capturing module may capture the vibration signals. The signal processing module may execute a transmissibility analysis to obtain the transmissibility between the signal detection modules, and execute a frequency response fitting according to the transmissibility to obtain a plurality of system dynamic parameters, and then execute a stability lobe diagram analysis to calculate the optimized spindle speed of the machining tool so as to make the machining tool operate at the optimized spindle speed. The signal processing module may repeatedly execute the transmissibility analysis, the frequency response fitting and the stability lobe diagram analysis to keep updating the optimized spindle speed until the machining process ends.

A machine tool includes a spindle retaining a tool, a spindle motor, a feed device relatively moving a workpiece and a tool with a feed motor, a spindle motor control unit, and a feed motor control unit. In a method of machining a workpiece with the machine tool, the spindle motor control unit continuously varies a rotational speed of the spindle in a periodic or non-periodic manner with a predetermined amplitude with respect to a target rotational speed. The feed motor control unit continuously varies a relative moving speed between the tool and the workpiece in synchronization with the spindle motor such that a ratio of the rotational speed of the spindle to the moving speed does not become constant at least in a predetermined time zone in which a spindle speed reaches a maximal value and a predetermined time zone in which the spindle speed reaches a minimal value.

A computerized method of machining a workpiece including, prior to machining the workpiece, establishing, based on empirical data obtained from machining activity at an earlier time, an historical mapping indicating pairings of depth of cut and rpm at which undesirable chatter (UDC) did not occur during machining activity at an earlier time using at least one given type of milling machine, at least one given type of cutting tool and at least one given type of workpiece material, prior to commencing machining of the workpiece, programming a machine tool to machine the workpiece using a given type of milling machine, a given type of cutting tool and a given type of workpiece material at at least one depth of cut and rpm, which, based on the historical mapping, avoid UDC and operating the machine tool in accordance with the programming to machine the workpiece.

A chatter database system, which includes a central chatter database, which is fed with data corresponding to the machining and chatter conditions of machining tools, particularly a milling, turning, drilling or boring machine. The data fed to the central chatter database is obtained and collected from at least two individual machining tools included in the chatter database system. The data is sent to the central chatter database via a data connection, preferably via a secured network, to generate chatter stability maps based on real encountered conditions.

A system, method and computer-readable medium for fine-tuning speed selection for reducing machine chatter. The system includes circuitry configured to determine a predetermined speed of the machine. The circuitry identifies a stability lobe based on the predetermined speed of the machine and selects a first set of fine-tuning speeds from a range of machine speeds corresponding to the determined stability lobe. Further, the circuitry causes the machine to operate at one or more of the first set of fine-tuning speeds.

A method for designing cutting conditions for cutting a workpiece with a cutting tool uses design parameters, including a feed speed, an axial direction cutting amount, a radial direction cutting amount, and a cutting speed of/by the cutting tool. A deflection amount of the cutting tool is calculated from the design parameters. Then a chattering vibration occurs or not in the cutting tool is determined. Depending on the determination result, a maximum cutting thickness of the workpiece is calculated. Then a cutting temperature of the cutting tool is calculated. Then whether a tool life of the cutting tool is satisfied or not is determined. Depending on the determination result, a cutting efficiency of the cutting tool is calculated and compared with data of a cutting efficiency stored in advance. When the calculated cutting efficiency is a maximum value among the data, the design parameters are used as the cutting conditions.

A spindle speed adjusting device in machining is provided, which may include a plurality of signal detection modules, a signal capturing module and a signal processing module. Each of the signal detection modules may keep measuring the vibration signals in machining. The signal capturing module may capture the vibration signals. The signal processing module may execute a transmissibility analysis to obtain the transmissibility between the signal detection modules, and execute a frequency response fitting according to the transmissibility to obtain a plurality of system dynamic parameters, and then execute a stability lobe diagram analysis to calculate the optimized spindle speed of the machining tool so as to make the machining tool operate at the optimized spindle speed. The signal processing module may repeatedly execute the transmissibility analysis, the frequency response fitting and the stability lobe diagram analysis to keep updating the optimized spindle speed until the machining process ends.

A numerical controller includes a machine learning device for performing machine learning of machining condition adjustment of a machine tool. The machine learning device calculates a reward based on acquired machining-state data on a workpiece, and determines an adjustment amount of machining condition based on a result of machine learning and machining-state data, and adjusts machining conditions based on the adjustment amount. Further, the machine learning of machining condition adjustment is performed based on the determined adjustment amount of machining condition, the machining-state data, and the reward.

A feedback control numerical machine tool and a method thereof are provided. The machine tool includes at least two spindles, an acoustic frequency detecting module, at least two spindle position detecting modules, and a control module. The spindles machine a workpiece. The acoustic frequency detecting module detects an acoustic frequency of the spindles when machining the workpiece. The spindle position detecting modules detects position information of the spindles when machining the workpiece. The control module acquires the acoustic frequency and the position information of the spindles, monitors whether any of the spindles chatters according to the acoustic frequency of the spindles, and performs chattering avoidance to the spindle that chatters according to the position information of the spindles. As such, the present disclosure performs chattering monitoring to a plurality of spindles and avoids the chattering immediately.

A computerized method of machining a workpiece including, prior to machining the workpiece, establishing, based on empirical data obtained from machining activity at an earlier time, an historical mapping indicating pairings of depth of cut and rpm at which undesirable chatter (UDC) did not occur during machining activity at an earlier time using at least one given type of milling machine, at least one given type of cutting tool and at least one given type of workpiece material, prior to commencing machining of the workpiece, programming a machine tool to machine the workpiece using a given type of milling machine, a given type of cutting tool and a given type of workpiece material at at least one depth of cut and rpm, which, based on the historical mapping, avoid UDC and operating the machine tool in accordance with the programming to machine the workpiece.