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JP-7854922-B2 - Systems and methods for supporting manufacturing

JP7854922B2JP 7854922 B2JP7854922 B2JP 7854922B2JP-7854922-B2

Inventors

  • 奥村 忠嗣
  • 小高 貴浩
  • 礒部 敦

Assignees

  • 株式会社日立ハイテクソリューションズ

Dates

Publication Date
20260507
Application Date
20221111

Claims (13)

  1. Multiple sensors for measuring the state or operation of manufacturing equipment, A data acquisition and management unit that collects and stores time-series data of multiple variables measured by the multiple sensors, A variable definition unit defines the variables to be analyzed from the retained data and online measured variables, A data formatting processing unit and a principal component analysis processing unit that preprocess the variables defined in the variable definition unit and perform principal component calculations, A variable correlation display unit that performs multivariate analysis according to data for a predetermined period at predetermined cycles, updates the analysis values based on the multivariate analysis for the predetermined period at predetermined cycles and displays them as time-series information, and displays the time-series information that serves as the target indicator in accordance with the time-series principal component values, A state change definition unit defines state changes that are the target of factor variable extraction from the time series information based on the multivariate analysis, A change factor variable calculation processing unit that performs a process to extract factor variables that have a high correlation with the state change defined by the state change definition unit, A change factor variable display unit that displays the factor variables related to the state change extracted by the factor variable extraction process, A manufacturing support system characterized by comprising the following features.
  2. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized by updating analytical values based on multivariate analysis over a predetermined period at predetermined cycles and displaying them as time-series information, as well as displaying the relationships between variables as a factor plot.
  3. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized by displaying numerical data of time-series information that serves as the target indicator as a class classified by clustering, in accordance with the time-series principal component values.
  4. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized in that, when defining state changes to be targeted for factor variable extraction from the time series information based on the multivariate analysis, two arbitrary points are selected from the analysis values based on the multivariate analysis for a predetermined period for each predetermined cycle.
  5. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized in that, when defining state changes that are the target of factor variable extraction from the time series information based on the multivariate analysis, the analysis values based on the multivariate analysis for a predetermined period are updated at predetermined cycles, and the direction of the state change is input on the screen displayed as time series information, thereby defining the state change.
  6. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized by performing a factor variable extraction process that is highly correlated with state changes, by calculating the dot product of the factor vector representing the variable relationship in the principal component space and the state change vector that is the target of factor variable extraction defined from the time series information, for each variable.
  7. A system for supporting the manufacturing described in claim 6, A manufacturing support system characterized by multiplying the dot product of a factor vector representing the variable relationship in the principal component space and the state change vector that is the target of factor variable extraction defined from the time series information by the amount of change of the preprocessed variable, in a process for extracting factor variables that are highly correlated with state changes.
  8. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized in that, for time-series information in which analytical values based on multivariate analysis for a predetermined period are updated at each predetermined cycle, the analytical values based on multivariate analysis are displayed as the Euclidean distance between the plot of principal component analysis at the current time and the time one cycle prior.
  9. A system for supporting the manufacturing described in claim 8, A manufacturing support system characterized by issuing an alert when the Euclidean distance is greater than a predetermined value.
  10. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized by displaying factor variables that have a high correlation with the extracted state changes.
  11. A system for supporting the manufacturing described in claim 1, A manufacturing support system characterized in that the time-series information used as the target indicator is either actual productivity indicator data or predicted values based on predictive diagnostics.
  12. A system for supporting the manufacturing described in claim 2, A manufacturing support system characterized by converting the magnitude of the correlation of the extracted state change factors, based on principal component analysis, and the defined state change amount into physical quantities of sensor-detected values and displaying them.
  13. A method for supporting manufacturing using a manufacturing support system , (a) A step in which multiple sensors measure the state or manipulated quantity of the manufacturing equipment, (b) The data collection and management unit collects and stores time-series data of multiple variables measured by the multiple sensors, (c) The variable definition unit defines the variables to be analyzed from the retained data and the online measured variables, (d) The data formatting processing unit and the principal component analysis processing unit preprocess the variables defined in the variable definition unit and perform principal component calculations, (e) The variable correlation display unit performs multivariate analysis according to the data for a predetermined period at predetermined cycles, updates the analysis values based on the multivariate analysis for the predetermined period at predetermined cycles and displays them as time series information, and displays the time series information that serves as the target indicator in accordance with the time series principal component values. (f) The state change definition unit defines state changes that are the subject of factor variable extraction from the time series information based on the multivariate analysis, (g) The change factor variable calculation processing unit performs a process to extract factor variables that have a high correlation with the state change defined in the state change definition unit , (h) The change factor variable display unit displays the factor variables related to the state change extracted by the factor variable extraction process , A method for supporting manufacturing, characterized by including the following.

Description

This invention relates to a system and method for providing guidance and support to users who operate manufacturing equipment and machinery when adjusting the equipment and machinery conditions. Patent Document 1 discloses a technology that processes multidimensional time-series data obtained based on detection signals output by numerous sensors placed on manufacturing equipment and machinery (hereinafter simply referred to as "manufacturing equipment") using principal component analysis, and notifies the status of the manufacturing equipment in a visually easy-to-understand output format. Furthermore, a predictive diagnostic system that detects signs of anomalies based on the analysis of multidimensional time-series data is known, for example, from Patent Document 2. These systems utilize multivariate analysis, such as principal component analysis, to diagnose conditions by combining information from numerous sensors. By comprehensively and holistically monitoring the state of manufacturing equipment, they can detect early signs of malfunctions and notify users. This reduces the proportion of corrective maintenance and provides advanced support for the operation of manufacturing equipment. Furthermore, principal components influencing the output variables are extracted, and a large amount of normal data is collected for learning purposes. Statistics are then used to determine thresholds for abnormality and normality in order to predict manufacturing equipment malfunctions. Furthermore, a system for displaying factor variables strongly related to the analysis results of principal component analysis is known from Patent Document 3. Japanese Patent Publication No. 2001-67117Japanese Patent Publication No. 2019-204342Japanese Patent Publication No. 2014-178844 This figure shows an example of time-series data for the productivity of manufacturing equipment.This is a block diagram showing a schematic configuration of a chemical plant management system according to Embodiment 1 of the present invention.This figure shows an example of a manufacturing facility 200 and a sensor group 300.This is a functional block diagram showing the configuration and processing flow of the plant monitoring and control support system 100.This figure shows an example of the display of the status change display unit 108.This figure shows an example of the display of the status change display unit 108.This figure shows an example of the display of the status change display unit 108.This figure shows an example of the display of the status change display unit 108.This figure shows an example of operation in the state change definition unit 110.This figure shows an example of displaying the dot product of all variables in the order of the process steps.This figure shows an example of displaying items sorted by the size of their dot products.This figure shows an example of data from each part of the chemical plant management system according to Embodiment 2 of the present invention.This figure shows an example of a predictive diagnostic system and anomaly detection system 600.This figure shows the change in sensor values.This diagram conceptually illustrates the differences in user behavior expected depending on whether or not the present invention is applied. The embodiments of the present invention will be described below with reference to the drawings. The embodiments are illustrative examples for explaining the present invention, and have been omitted and simplified as appropriate for clarity of explanation. The present invention can also be implemented in various other forms. Unless otherwise specified, each component may be singular or plural. Furthermore, the position, size, shape, and scope of each component shown in the drawings may not represent the actual position, size, shape, and scope, in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the position, size, shape, and scope disclosed in the drawings.