Mitsubishi Electric Corporation

Tetsushi Ishida

Osamu Nasu

Takaaki Nakamura

Noriyasu Fukatsu

Yoshiyuki Hattori

Kyohei Suzuki

Kiyofumi Takeuchi

Mariko Nishino

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.

Machining dimension prediction apparatus, machining dimension prediction system, machining dimension prediction method, and recording medium

A machine tool machining dimensions prediction device () includes: a data collector () to acquire driving state information of a machine tool; a feature amount extractor () to extract a feature amount from the driving state information; a data analyzer () to analyze the extracted feature amount; and a machining quality prediction model generator () to generate, from the analyzed information, a prediction model of a machining dimension of a workpiece. The machine tool machining dimensions prediction device () applies the feature amount and the driving state information to the prediction model during machining of the workpiece to predict a machining quality and refers to a machining dimension quality regulation to determine whether the machining quality satisfies a standard.

Machine tool machining dimensions prediction device, machine tool equipment abnormality determination device, machine tool machining dimensions prediction system, and machine tool machining dimensions prediction method

A vibration analysis apparatus includes: a storage unit storing a regression equation indicating correspondence between rotation speed change of a rotation mechanism and a peak occurrence frequency of acceleration of vibration, for each acceleration peak; an analysis unit extracting a peak occurrence frequency of acceleration of vibration for each acceleration peak, based on vibration data of the rotation mechanism and calculating, for each acceleration peak, a waveform area of the acceleration peak by integrating the acceleration peak over a specific frequency section; and an anomaly determination unit determining whether operational anomaly occurs in the rotation mechanism for each acceleration peak. The analysis unit tracks, in accordance with the regression equation, change in peak occurrence frequency due to rotation speed change when vibration of the rotation mechanism is analyzed, and calculates, for each second acceleration peak, the waveform area of the second acceleration peak corresponding to the second vibration frequency tracked.

Vibration analysis apparatus and vibration analysis method

A diagnostic apparatus () diagnoses the existence of an abnormality in a tool for processing of a processing target by each of multiple working machines. The diagnostic apparatus () includes an acquirer () and a diagnoser (). The acquirer () acquires program identification information identifying a program executed in each of the working machines, tool information indicating a type of the tool applied to processing, and transition information indicating transition of load in the working machine from the start to the end of the processing executed by execution of the program, at execution of the processing in the working machine. The diagnoser () diagnoses whether an index value of the load obtained from the transition information is out of a predetermined range corresponding to a combination of the program identification information, the tool information, and machine information identifying the working machine that transmits the transition information.

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Tokyo, Japan

Tetsushi Ishida