Factor analysis device, factor analysis method, and factor analysis program

Patent metadata

Field	Value
Publication number	US-10496730-B2
Application number	US-201415125302-A
Country	US
Kind code	B2
Filing date	Dec 15, 2014
Priority date	Mar 14, 2014
Publication date	Dec 3, 2019
Grant date	Dec 3, 2019

Abstract

This factor analysis device is provided with a feature extraction unit ( 1021 ) that extracts feature quantities from an explanatory time series, a feature conversion unit ( 1022 ) that converts said feature quantities to a feature time series, a feature-time-series influence-degree computation unit ( 1031 ) that uses said feature time series and a response time series to compute an influence degree indicating the degree to which the feature time series influences the change over time represented by the response time series, and an explanatory-time-series influence-degree computation unit ( 1032 ) that uses said influence degree to compute an influence degree indicating the degree to which the explanatory time series influences the change over time represented by the response time series.

First claim

The invention claimed is:

1. A factor analysis device comprising:
a memory that stores a set of instructions; and
at least one processor configured to execute the set of instructions to:
extract feature quantities from an explanatory time series representing conditions under which an analysis target device operates, the explanatory time series being sensor observation values measured by the analysis target device;
convert the feature quantities into a feature time series;
compute, from the feature time series and a response time series representing evaluation indexes of the analysis target device operating under the conditions represented by the explanatory time series, an influence degree of the feature time series on a change in value of the response time series, the response time series being observation values measured by the analysis target device; and
compute, based on the influence degree, an influence degree of the explanatory time series on the change in value of the response time series;
wherein the analysis target device is a device used in manufacturing process,
wherein the explanatory time series represent production conditions measured by the analysis target device, and
wherein the response time series represent the evaluation indexes of products manufactured under the production conditions.

2. The factor analysis device according to claim 1 , wherein
the at least one processor is configured to:
extract a feature quantity for a partial time series within a region of a window that has a predetermined time range, the partial time series being a part of an explanatory time series, and
convert, when the feature extraction unit extracts the feature quantities at positions by shifting the window by a predetermined number of time points from start time to end time of the explanatory time series and the window reaches the end time, the extracted feature quantities into a feature time series.

3. The factor analysis device according to claim 1 , wherein
the at least one processor is configured to:
output a feature quantity corresponding to a feature time series with a large influence degree on a change in value of the response time series and an explanatory time series with a large influence degree on a change in value of the response time series.

4. The factor analysis device according to claim 1 , wherein
the at least one processor is configured to:
extract one or more kinds of feature quantities from one or more explanatory time series, and
convert the feature quantities into a plurality of feature time series corresponding to the kinds of the feature quantities.

5. The factor analysis device according to claim 1 , wherein
the at least one processor is configured to:
compute influence degrees of a feature time series on a change of value of the response time series using one or more multivariate analysis methods.

6. The factor analysis device according to claim 5 , wherein
the at least one processor is configured to:
use L1 regularized logistic regression as one of the multivariate analysis methods.

7. The factor analysis device according to claim 5 , wherein
the at least one processor is configured to:
use a random forest classifier as one of the multivariate analysis methods.

8. A factor analysis method comprising:
extracting feature quantities from an explanatory time series representing conditions under which an analysis target device operates, the explanatory time series being sensor observation values measured by the analysis target device;
converting the feature quantities into a feature time series;
computing, from the feature time series and a response time series representing evaluation indexes of the analysis target device operating under the conditions represented by the explanatory time series, an influence degree of the feature time series on a change in value of the response time series, the response time series being observation values measured by the analysis target device; and
computing, based on the influence degree, an influence degree of the explanatory time series on a change in value of the response time series;
wherein the analysis target device is a device used in manufacturing process,
wherein the explanatory time series represent production conditions measured by the analysis target device, and
wherein the response time series represent the evaluation indexes of products manufactured under the production conditions.

9. A factor analysis device comprising:
a memory that stores a set of instructions; and
at least one processor configured to execute the set of instructions to:
extract feature quantities from an explanatory time series representing conditions under which an analysis target device operates, the explanatory time series being sensor observation values measured by the analysis target device;
convert the feature quantities into a feature time series;
compute, from the feature time series and a response time series representing evaluation indexes of the analysis target device operating under the conditions represented by the explanatory time series, an influence degree of the feature time series on a change in value of the response time series, the response time series being observation values measured by the analysis target device; and
compute, based on the influence degree, an influence degree of the explanatory time series on the change in value of the response time series;
wherein the analysis target device is an internet technology (IT) system,
wherein the explanatory time series represent operation information of the IT system, the operation information being use rate or use amount of computer resources, and
wherein the response time series represent the evaluation indexes that are performance indexes, the performance indexes being consumption power amount of number of times of arithmetic operations.

Assignees

• Nec Corp

Inventors

• Mizoguchi Takehiko

Classifications

• G06F2218/00

  Aspects of pattern recognition specially adapted for signal processing · CPC title

• G06F17/18 Primary

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06N5/045

  Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence · CPC title

• G07C3/14

  Quality control systems · CPC title

• Y02P90/22

  Cross-Sectional Technologies · mapped topic