Abstract: To provide a system that collects data from each sensor (airflow, temperature, humidity, atmospheric pressure, illuminance, and air pollution) that measures an environmental factor and can evaluate an environment in a factory in a complex manner.

Abstract: A preventive maintenance system of a machine tool capable of making determination of presence of an abnormality mechanically and automatically, which has conventionally been performed on the basis of the feeling of an operator and detecting an abnormality more accurately in an earlier stage is provided.

Abstract: A tool management system of a machine tool includes: a detection unit to detect at least one of vibration, acoustic waves produced during operation of the machine tool, and current value of a server motor of a driving machine tool; a tool replacement determination unit that determines the necessity to replace the tool on the basis of information related to a detection value of at least one of the vibration, the acoustic waves, and the current value detected during operation of the machine tool; and a detection start/end command setting unit that adds commands for a detection start point and a detection end point of at least one of the vibration, the acoustic waves, and the current value of the servo motor to a machining program.

Abstract: To provide an analysis device, an analysis method, and an analysis program capable of analyzing a machining state while associating machine data output during operation of a machine tool and measured data containing the size of an actual machined part measured by a measuring machine with each other. An analysis device comprises: a collection unit that collects an aggregate of machine data output during operation of a machine tool and an aggregate of measured data containing measurement points where the size of a machined part machined by the machine tool has been measured by a measuring instrument; and a feature extraction unit that selects machine data corresponding to an arbitrary measurement point, in the aggregate of the measured data from the aggregate of the machine data, and extracts the selected machine data as a feature at the arbitrary measurement point.

Abstract: To provide a system that collects data from each sensor (airflow, temperature, humidity, atmospheric pressure, illuminance, and air pollution) that measures an environmental factor and can evaluate an environment in a factory in a complex manner.

Abstract: To provide a system that collects data from each sensor (airflow, temperature, humidity, atmospheric pressure, illuminance, and air pollution) that measures an environmental factor and can evaluate an environment in a factory in a complex manner.

Abstract: Provided is a defect occurrence prediction system for a machine tool that makes it possible to identify the factors causing the occurrence of defects efficiently and effectively, and predict the occurrence of the defects accurately with good precision.

Abstract: The present disclosure is intended to provide an automatic three-dimensional measurement-based inspection system for workpieces which enables three-dimensional measurement-based inspection to be performed more efficiently. An automatic three-dimensional measurement-based inspection system for workpieces includes: an automated warehouse having a measurement target repository for storing a workpiece to undergo measurement-based inspection performed by a three-dimensional measurement apparatus, and having a measurement-purpose repository for storing the workpiece conveyed from the measurement target repository by a stacker crane when the three-dimensional measurement apparatus is going to perform the measurement; and the three-dimensional measurement apparatus provided is a three-dimensional measurement region that is adjacent to the measurement-purpose repository.

Abstract: A machine tool for machining a workpiece includes a spindle configured to rotate a holder mounted with a tool used for machining, one or more moving shafts configured to move the holder and/or a work base on which the workpiece is placed, a torque measurement unit configured to measure driving torque of the spindle and/or the one or more moving shafts, a reference value calculation unit configured to use, as a reference value, the driving torque measured by performing a no-load operation by rotating the spindle in a normal state, a torque comparison unit configured to compare, to the reference value, the driving torque measured by performing a no-load operation by rotating the spindle before actual machining, and an alarm unit configured to determine whether to issue an alarm on the basis of results of the comparison.

Abstract: A machine tool for machining a workpiece includes a spindle configured to rotate a holder mounted with a tool used for machining, one or more moving shafts configured to move the holder and/or a work base on which the workpiece is placed, a torque measurement unit configured to measure driving torque of the spindle and/or the one or more moving shafts, a reference value calculation unit configured to use, as a reference value, the driving torque measured by performing a no-load operation by rotating the spindle in a normal state, a torque comparison unit configured to compare, to the reference value, the driving torque measured by performing a no-load operation by rotating the spindle before actual machining, and an alarm unit configured to determine whether to issue an alarm on the basis of results of the comparison.

Abstract: An abnormality occurrence presumption apparatus which presumes the occurrence of an abnormality in a telescopic cover attached to a machine tool performs supervised learning on the basis of a feature amount extracted from a physical quantity acquired during an operation of the machine tool and information related to an abnormality occurring in the telescopic cover, and stores the result of the learning. The abnormality occurrence presumption apparatus presumes an abnormality that may occur in the telescopic cover during the operation of the machine tool on the basis of the result of the learning and the feature amount extracted from the physical quantity.

Abstract: Provided is a defect occurrence prediction system for a machine tool that makes it possible to identify the factors causing the occurrence of defects efficiently and effectively, and predict the occurrence of the defects accurately with good precision.

Abstract: A tool management system of a machine tool capable of determining an appropriate time to replace a tool used by a machine tool is provided.

Abstract: The present disclosure is intended to provide an automatic three-dimensional measurement-based inspection system for workpieces which enables three-dimensional measurement-based inspection to be performed more efficiently. An automatic three-dimensional measurement-based inspection system for workpieces includes: an automated warehouse having a measurement target repository for storing a workpiece to undergo measurement-based inspection performed by a three-dimensional measurement apparatus, and having a measurement-purpose repository for storing the workpiece conveyed from the measurement target repository by a stacker crane when the three-dimensional measurement apparatus is going to perform the measurement; and the three-dimensional measurement apparatus provided is a three-dimensional measurement region that is adjacent to the measurement-purpose repository.

Abstract: A preventive maintenance system of a machine tool capable of making determination of presence of an abnormality mechanically and automatically, which has conventionally been performed on the basis of the feeling of an operator and detecting an abnormality more accurately in an earlier stage is provided.

Abstract: To provide a system that collects data from each sensor (airflow, temperature, humidity, atmospheric pressure, illuminance, and air pollution) that measures an environmental factor and can evaluate an environment in a factory in a complex manner.

Abstract: To provide an analysis device, an analysis method, and an analysis program capable of analyzing a machining state while associating machine data output during operation of a machine tool and measured data containing the size of an actual machined part measured by a measuring machine with each other. An analysis device comprises: a collection unit that collects an aggregate of machine data output during operation of a machine tool and an aggregate of measured data containing measurement points where the size of a machined part machined by the machine tool has been measured by a measuring instrument; and a feature extraction unit that selects machine data corresponding to an arbitrary measurement point, in the aggregate of the measured data from the aggregate of the machine data, and extracts the selected machine data as a feature at the arbitrary measurement point.

Abstract: To provide a diagnosis device, a diagnosis method, and a diagnosis program capable of identifying a factor for defective machining. A diagnosis device comprises: a collection unit that collects machine data output during operation of a machine tool; a feature extraction unit that classifies the machine data according to an input factor for defective machining, and extracts a feature quantity from an aggregate of the machine data according to the input factor; and a determination unit that compares a feature quantity in the machine data output during actual machining by the machine tool with the feature quantity according to the factor, and determines a factor for defective machining based on a degree of match.

Abstract: An abnormality occurrence presumption apparatus which presumes the occurrence of an abnormality in a telescopic cover attached to a machine tool performs supervised learning on the basis of a feature amount extracted from a physical quantity acquired during an operation of the machine tool and information related to an abnormality occurring in the telescopic cover, and stores the result of the learning. The abnormality occurrence presumption apparatus presumes an abnormality that may occur in the telescopic cover during the operation of the machine tool on the basis of the result of the learning and the feature amount extracted from the physical quantity.