A polishing apparatus is provided. The polishing apparatus includes: a polishing unit configured to polish a substrate by bringing a polishing tool into contact with the substrate and moving the substrate relatively to the polishing tool; a cleaning unit; and a first transfer robot configured to transfer the substrate before polishing to the polishing unit and/or configured to transfer the substrate after polishing from the polishing unit to the cleaning unit. The cleaning unit includes: at least one cleaning module, a buff processing module configured to perform a buff process to the substrate, and a second transfer robot configured to transfer the substrate between the cleaning module and the buff processing module, the second transfer robot being different from the first robot.

A double-sided or single-sided machine tool includes a first working disk and a counter-bearing element. The first working disk and the counter-bearing element can be driven rotationally relative to each other by means of a rotary drive. A working gap is formed between the first working disk and the counter-bearing element for the double-sided or single-sided machining of flat workpieces. The double-sided or single-sided machine tool comprises multiple sensors that record measurement data relating to tool and/or machining parameters of the double-sided or single-sided machine tool during operation. A control apparatus obtains the measurement data recorded by the sensors during operation. The control apparatus comprises an artificial neural network that is designed to create a state vector of the double-sided or single-sided machine tool from the measurement data and to compare said state vector with at least one target state vector.

A power tool includes a housing, a motor supported by the housing, a battery pack interface configured to receive a battery pack, a plurality of sensors configured to generate sensor data indicative of an operational state of the power tool, and an electronic controller. The electronic controller includes an electronic processor and a memory. The memory includes a machine learning control program for execution by the electronic processor. The electronic controller is configured to receive the sensor data indicative of the operational state of the power tool, process the sensor data using the machine learning control program to determine whether the power tool is experiencing a stall condition, and disable the motor when the power tool is determined to be experiencing the stall condition.

Provided is a high-precision substrate polishing system. An apparatus for polishing a substrate includes a platen on which a polishing pad is seated and which is rotatable, a substrate carrier configured to grip a substrate and rotatable on an upper side of the platen, an infrared sensor located inside the platen and configured to measure a temperature of the substrate, and a controller configured to determine a polishing state of the substrate using a value measured by the infrared sensor.

Provided is a high-precision substrate polishing system. An apparatus for polishing a substrate includes a platen on which a polishing pad is seated and which is rotatable, a substrate carrier configured to grip a substrate and rotatable on an upper side of the platen, an infrared sensor located inside the platen and configured to measure a temperature of the substrate, and a controller configured to determine a polishing state of the substrate using a value measured by the infrared sensor.

A polishing tool wear amount prediction device, machine learning device, and system capable of predicting a wear amount of a polishing tool unit of a polishing tool during polishing are provided. The polishing tool wear amount prediction device includes a machine learning device which observes polishing condition data indicating a processing condition of polishing as a state variable indicating a current environment state and performs, based on the state variable, learning or prediction by using a learning model which stores a correlation of the wear amount of the polishing tool with respect to the processing condition of polishing.

A polishing tool wear amount prediction device, machine learning device, and system capable of predicting a wear amount of a polishing tool unit of a polishing tool during polishing are provided. The polishing tool wear amount prediction device includes a machine learning device which observes polishing condition data indicating a processing condition of polishing as a state variable indicating a current environment state and performs, based on the state variable, learning or prediction by using a learning model which stores a correlation of the wear amount of the polishing tool with respect to the processing condition of polishing.

A machine tool includes a first support disk and a first working disk. The first working disk defines a clamping surface and is fastened to the first support disk. A counter bearing element is positioned relative to the first working disk such that a working gap is formed between the first working disk and the counter bearing element and is dimensioned to accept a flat workpiece. A first clamping arrangement clamps the clamping surface of the first working disk to the first support disk such that the clamping surface faces away from the working gap. At least one decoupling element is positioned to at least one decoupling element configured to reduce friction between the first support disk and the first working disk.

A machine tool includes a first support disk and a first working disk. The first working disk defines a clamping surface and is fastened to the first support disk. A counter bearing element is positioned relative to the first working disk such that a working gap is formed between the first working disk and the counter bearing element and is dimensioned to accept a flat workpiece. A first clamping arrangement clamps the clamping surface of the first working disk to the first support disk such that the clamping surface faces away from the working gap. At least one decoupling element is positioned to at least one decoupling element configured to reduce friction between the first support disk and the first working disk.

A machining machine includes an annular bottom working disk and a top counter bearing element. The bottom working disk and top counter bearing element are driven to rotate relative to each other. A working gap is defined between the bottom working disk and the top counter bearing to machine flat work pieces on at least one side. A means for generating a local deformation of the bottom working disk are also provided.