Kabushiki Kaisha Toshiba

Toshiba Digital Solutions Corporation

Toshiyuki Katou

Shintarou Takahashi

Toru Ito

Takashi Morimoto

Rumi Hayakawa

Hidemasa Itou

A manufacturing condition output apparatus of an embodiment is a manufacturing condition output apparatus which outputs a manufacturing condition of a product. The manufacturing condition output apparatus outputs change degree information which is information regarding degrees of change of values regarding defect probabilities for a plurality of variables relating to manufacturing of the product from model information of a model generated through machine learning on a basis of manufacturing data of the product and inspection result data of the product, as a manufacturing condition.

Manufacturing condition output apparatus, quality management system, and storage medium

An anomaly detection device according to the embodiment includes a prediction unit and an anomaly score calculation unit. The prediction unit performs a process to obtain, at each time step of the time series data of m dimensions, distribution parameters required to express a continuous probability distribution representing a distribution state of predicted values that can be obtained at a time step t of the time series data of m dimensions. The anomaly score calculation unit performs a process to calculate, using distribution parameters obtained by the prediction unit, an anomaly score corresponding to an evaluation value representing evaluation of a magnitude of anomaly in an actual measurement value at the time step t of time series data of m dimensions.

Anomaly detection device, anomaly detection method and storage medium

An abnormality detection device of an embodiment includes an encoder, a first identifier, a decoder, and a second identifier. The encoder is configured to compress input data using a compression parameter to generate a compressed data. The first identifier is configured to determine whether a distribution of the compressed data input by the encoder is a distribution of the compressed data or a prior distribution prepared in advance, and inputs a first identification result to the encoder. The decoder is configured to decode the compressed data using a compressing parameter to generate reconstructed data. The second identifier is configured to determine whether the reconstructed data input by the decoder is the reconstruction data or the input data and outputs a second identification result to the encoder and the decoder.

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Yokohama, Japan

Toshiyuki Katou