An automated constructing method of cloud manufacturing service is provided for a distributed system including a virtual machine and a service manager. The method includes: obtaining a library package which is locally built, analyzing the library package to obtain key information, and generating a library information file; automatically generating a project source code file according to the library information file, and generating a web service package according to the project source code file; and deploying, by the service manager, the web service package on the virtual machine.

This invention refers to a knife sharpening device (200), a knife replacement method and a knife replacement system (100). The knife sharpening device (200) comprises a control board (212) configured to connect an external network to the sharpening device (200). The method comprises the steps of: obtaining knife durability parameters (1002); obtain knife use information (1004); and defining compliance check data (1006). The knife replacement system (100) comprises the knife sharpening device (200) and a server (300) configured to obtaining knife durability parameters, obtain knife use information, and compare the knife use information with the knife durability parameters.

Provided is a temperature measurement device for a rotating member of a processing device that grips a rotating member made from a metal and capable of rotating around a rotational axis, and moves in coordination with and coaxially rotates with the rotating member. This temperature measurement device is equipped with: an ideal temperature setting means for setting an ideal temperature while the rotating member is rotating; a temperature measurement means for measuring an actual temperature while the rotating member is rotating; and a detection means for detecting whether or not the difference between the actual temperature measured by the temperature measurement means and the ideal temperature set by the ideal temperature setting means exceeds a pre-set threshold at the time the actual temperature is measured.

A scattering direction, a scattering range, a scattering speed, or the like of chip generated by machining is acquired by image pickup unit, and a state (such as wearing and fracture) of a tool is estimated from the acquired dynamic information. A machine learning device is used to perform the estimation and the machine learning device is caused to learn a state of a tool relative to the combination of a plurality of dynamic information on the vicinity of the tool, and the state of the tool is estimated based on a result of the learning.

A machining dimension prediction apparatus includes a trend acquirer that acquires, for each workpiece, trend information indicating a trend of a state of a machining tool during a machining period of machining performed by the machining tool, a feature calculator that calculates, based on the trend information, a feature using the trend of the state in each of sections included in the machining period, a measurement value acquirer that acquires a measurement value of a dimension of each workpiece after being machined, a section specifier that specifies, as a specific section of the sections, a section including a calculated feature having a greatest degree of relevance to the measurement value, and a predictor that predicts, when a new-target workpiece is machined, a dimension of the new-target workpiece after being machined based on the feature calculated using the trend of the state in the specific section.

Provided is a rotary machine tool with which it is possible to measure, in real time, the damage or extreme wear thereof. The rotary machine tool of the present invention is provided with at least: a sensor installation hole which has the rear end being open to the exterior at the rear end of the main body of the rotary cutting tool, and the tip being above the tip of the main body of the rotary machine tool and closed off from the exterior; a sensor that is positioned at the tip of the sensor installation hole and detects the state at the positioned position; and a sensor insertion hole that is connected to one end of the sensor and is coupled with the rear end of the rotary cutting tool.

A cutting insert for cutting, milling or drilling of metal includes a sensor for detecting a predetermined wear of the cutting insert caused by operation thereof on a metal work piece, wherein the sensor includes at least two contact regions through which the sensor is connectable to external measuring circuitry. The sensor has at least two leads, which are connected to a respective of the at least two contact regions, wherein each lead presents a respective free end positioned such that, upon the predetermined wear caused by the operation of the cutting insert on a metal work piece, the free ends will be connected to each other by the metal work piece or by a chip resulting from the operation of the cutting insert on the metal work piece.

To efficiently estimate and detect a tool life of a machine tool while lowering an occupation ratio in a data band of a communication line between a machine tool and an upper-level controller, a management apparatus or the like. A machine tool to be managed by a production management apparatus includes a motor for moving one of a workpiece to be machined and a tool for performing a machining operation, an amplifier for driving the motor, a servo controller for controlling the motor via the amplifier based on a notification of a predetermined machining operation, and an NC device for notifying the servo controller of the predetermined machining operation. The servo controller obtains servo data representing a load on the amplifier, performs a first processing for compressing the servo data, and transmits the compressed data to the NC device.

Provided is a tool life estimating device that enables estimation of a life of a tool used in a machine tool according to changes in machining conditions. The tool life estimating device includes a state observation unit that acquires machining information indicative of a status of the machining in a state where the life of the tool remains sufficiently, wherein the machining information is acquired from log data recorded while the machine tool is operated, and creates input data based on the machining information that has been acquired; a learning unit that constructs a learning model in which clusters of the machining information are created by unsupervised learning using the input data that has been created by the state observation unit; and a learning model storage unit that stores the learning model.

A cutting blade partially covered with one or more layers covering a part of the blade, with one of the layers being a wear layer which has a different visual appearance than the underlying material of the blade, and wears away more quickly than the core material when the blade is used, so that the underlying material of the blade is uncovered as soon as this wear layer is completely removed in partial areas, providing a clear visual signal that it needs to be replaced.