Abstract: A smart adjustment system is provided, which may include a cloud computing device and a data acquisition device. The cloud computing device may include a neural network model saving the model data of machine tools, and the estimated increase percentages of each machine tool in different cutting parameters. The data acquisition device may receive the model data of a target machine tool. The could computing device may compare the model data of the target machine tool with the model data of the machine tools via the neural network model in order to calculate an estimated cutting parameter with an estimated increase percentage and control the target machine tool to perform a machining process by the estimated cutting parameter.

Abstract: A portable machine health monitoring system, applied for diagnosing a machine in operation, includes an installation device and a portable monitoring box. The installation device includes a plurality of sensing assemblies and a plurality of connecting assemblies. Each of the plurality of sensing assemblies is connected with the corresponding connecting assembly. Each of the plurality of connecting assemblies mounts the corresponding sensing assembly in a non-destructive manner onto a detected position on the machine. Each of the plurality of sensing assemblies is used for detecting a motion signal at the corresponding detected position on the machine in operation. The portable monitoring box, connected with the installation device, includes an analysis module for receiving the motion signal and further for calculating a health status information according to the detected motion signal.

Abstract: A cutting machine supplying & marketing DLT-based system is provided, which includes a plurality of sensors, a cloud analysis device, a cloud data ledger module and a cloud supplying module. The sensors are connected to a plurality of components of a target cutting machine implementing a cutting operation and each sensor provides the operation data of one of the components. The cloud analysis device analyzes the operation data of the components to generate analysis results and generates the healthy statuses of the components according to the analysis results. The cloud data ledger module records the healthy statuses of the components. The cloud supplying module transmits a component purchase reminder signal to a user device according to the healthy statuses of the components for the user device to make an order.

Abstract: A smart adjustment system is provided, which may include a cloud computing device and a data acquisition device. The cloud computing device may include a neural network model saving the model data of machine tools, and the estimated increase percentages of each machine tool in different cutting parameters. The data acquisition device may receive the model data of a target machine tool. The could computing device may compare the model data of the target machine tool with the model data of the machine tools via the neural network model in order to calculate an estimated cutting parameter with an estimated increase percentage and control the target machine tool to perform a machining process by the estimated cutting parameter.

Abstract: A bandsaw machine health monitoring system includes a sensing module, a signal processing module, a human-machine interface module and a control module. The sensing module may include a plurality of sensing devices and these sensing devices can collect a plurality of signals from a bandsaw machine in operation. The signal processing module can be electrically connected to the sensing module and the signal processing module can process the signals collected by the sensing module. The control module can analyze the processing result transmitted from the signal processing module. The human-machine interface module can receive the analysis result of the control module and display the health status value of the bandsaw machine.

Abstract: A handsaw machine health monitoring system includes a sensing module, a signal processing module, a human-machine interface module and a control module. The sensing module may include a plurality of sensing devices and these sensing devices can collect a plurality of signals from a handsaw machine in operation. The signal processing module can be electrically connected to the sensing module and the signal processing module can process the signals collected by the sensing module. The control module can analyze the processing result transmitted from the signal processing module. The human-machine interface module can receive the analysis result of the control module and display the health status value of the handsaw machine.