A method for predicting the remaining service life of a saw band in a bandsaw machine, in which a behavior or properties of the saw band clamped in the sawing machine are monitored by at least one sensor during operation of the sawing machine. Changes in the behavior or in properties of the saw band over time established on the basis of measurement signals of the sensor device are used for making a prediction about the time at which a band will break. The behavior or properties of the saw band are indirectly monitored using the at least one sensor device by way of detecting changes to components of the sawing machine which are operatively connected to the saw band.

An automatic system for inspecting a cutting edge of a ring shaped blade. An example system includes one supporting and moving group rotatably mounted around one rotation axis and configured to support the ring shaped blade between at least one parking position and at least one reading position, one first emitting unit configured to emit at least one first inspection light beam, one second emitting unit configured to emit at least one second inspection light beam, one first detecting unit configured to detect a first light beam reflected from the ring shaped blade, and one second detecting unit configured to detect a second light beam reflected from the ring shaped blade, and one control and processing unit configured to receive an input and process at least one detection signal and output at least one quality index of the cutting edge of the ring shaped blade.

A machine tool includes a tool and a workpiece machined by the tool, and sensors configured to detect a position of the tool and/or the tool holder holding the tool in a spatially and time resolved manner A method for offline and/or online identification of a state of the machine tool includes: a) detecting or providing positions p.sub.i of the tool and/or of the tool holder at a series of points in time i, i=1 . . . n; b) determining for the series of points in time i a series of position changes ?m.sub.i according to the formula ?m.sub.i=p.sub.i/p.sub.i-1 and a series of speed changes ?v.sub.i according to the formula ?v.sub.i=v.sub.i/v.sub.i-1 with $v_i=\frac{P_i-P_{i-1}}{t_i-t_{i-1}}$
and formula $v_{i-1}=\frac{P_{i-1}-P_{i-2}}{t_{i-1}-t_{i-2}};$
c) identifying the state of the tool, the tool holder, the machine tool and/or the workpiece machined in the machine tool based on the position changes ?m.sub.i and the speed changes ?v.sub.i.

A method includes acquiring an image of a cutter on a drill bit, determining a cutter dull condition based on the image of the cutter using a machine-learning method, wherein the machine-learning method is trained using a set of training images and a set of known cutter dull conditions, wherein each of the set of known cutter dull conditions is associated with one or more of a set of cutters depicted in the set of training images and determining a cutter degradation severity based the image of the cutter. The method also includes generating bit modification instructions based the cutter dull condition and the cutter degradation severity.

A magnetically attachable sensor assembly for sensing cutting tool operation. The magnetically attachable sensor assembly comprises an acoustic and vibration sensing apparatus, or sensor package, disposed in a housing having a portable, magnetic form factor for portability and easy clamping/attachment to a number of different surfaces.

A system and method for cutting at least one of a plurality of features in a workpiece with at least one of a plurality of cutting tools controlled by at least one of a plurality of cutting tool machines is disclosed. The method receives process information describing cutting parameters from cutting tool machines, retrieves predicted cutting tool wear information relating a predicted cutting tool wear value to the cutting parameters, retrieves cutting tool information that include measured cutting tool wear information for the one of the plurality of cutting tools, computes a predicted cutting tool wear value for the one of the plurality of cutting tools from the measured cutting tool wear information, and cuts the at least one feature according to the computed predicted cutter wear value.

A method is provided for assessing wear of a drill bit throughout its use for carrying out the drilling of elements to be drilled constituted by at least one layer and at least one material. The wear of the drill bit expresses its capacity to perform a drilling that meets at least one criterion of quality of a drilling. The method includes at least: measuring or detecting at least one parameter having an effect on the wear of the drill bit, the parameter being chosen from: the depth of drilling performed by the drill bit, and the entry of the drill bit into the element to be drilled; and determining at least one state of wear of the drill bit, each state of wear being determined as a function of one of the parameters and being characteristic of one of the criteria of quality of a drilling.

An intelligent detection cutting tool structure includes a cutting tool including a shank, a body and a detection device. The body is connected with the shank and has a cutting edge. The detection device is mounted on the shank and detects abnormal conditions during a working process of the cutting edge, and transmits a signal to a mobile device of an operator. Thus, when the cutting tool is mounted on the working machine to perform the working process, the detection device detects operation of the cutting tool during the working process and transmits the detected information to the mobile device, so that the operator can control the operating situation of the cutting tool, so as to calibrate, repair or replace the cutting tool according to the operating situation of the cutting tool.

A processing system having a function for appropriately maintaining processing accuracy, without depending on a degree of abrasion of a tool. An unused tool used in a machine tool is captured by using a camera mounted on a robot, so as to obtain a reference image of the tool. Next, an image of the tool is captured after a predetermined number of processing operations carried out. An average amount of tool abrasion per one processing operation is calculated based on the two images, so as to estimate a current amount of tool abrasion. Based on the estimation result and a previously input limit amount of abrasion, the number of remaining possible processing operations of the tool is calculated and output.

A machine tool (1) includes a tool information storage (9) storing therein used tool information for, when an NC program execution part (5) executes an NC program, specifying a tool used for machining, and a magazine operation panel (18) includes an announcement part (18b) for announcing an alarm to an operator. When receiving an operation signal from an input part (18a) while the NC program execution part (5) is executing an NC program, a tool change control part (11) checks the used tool information stored in the tool information storage (9), and in the case where a tool held by a tool pot (17a) corresponding to the operation signal is not used for machining, moves the tool pot (17a) to a tool attachment/detachment position (17c), and in the case where the tool is used for machining, causes the announcement part (18a) to announce an alarm indicating that it is unavailable.