Abstract: A prediction control development device according to one aspect of the present invention generates a prediction model of a control amount by analyzing first time-series data of the control amount and provides the generated prediction model to a controller. The prediction control development device acquires second time-series data showing transition of a value of the control amount during prediction control using the prediction model, and evaluates prediction accuracy of the prediction model based on a difference between a prediction value by the prediction model and a value of the second time-series data. When the prediction accuracy of the prediction model is not allowable, the prediction control development device analyzes the second time-series data to newly generate a prediction model of the control amount, and provides the newly generated prediction model to the controller.

Abstract: The present invention reduces the probability of malfunction occurrence when performing predictive control of a device being controlled. In this control device of one aspect of the present invention, a prediction model for a control variable is used to calculate a prediction value from a measured value of the control variable, and a desired command value of the control variable is determined by correcting a desired basic value in accordance with the calculated prediction value. The degree of correction is determined on the basis of weight. The control device controls the operation of the device being controlled according to the determined desired command value. The control device assesses whether the device being controlled is operated appropriately on the basis of monitoring data relating to the operation result of the device being controlled, and optimizes the weight of the correction to make appropriate control possible based on the assessment result.

Abstract: An acquiring section acquires a plurality of observed data that are observed data observed from an object of control and that express combinations of explanatory variables and objective variables. A teacher learning section, on the basis of the plurality of observed data acquired by the acquiring section, trains a model for outputting the objective variable from the explanatory variable, and generates a learned teacher model. A learning data generating section, by inputting a predetermined explanatory variable to the teacher model generated by the teacher learning section, acquires a predetermined objective variable with respect to the predetermined explanatory variable, and generates a combination of the predetermined explanatory variable and the predetermined objective variable as learning data for training a decision tree model.

Abstract: An acquisition unit (11) acquires an explanatory variable that is to be input to a model (37) configured to output an objective variable for the explanatory variable, a specification unit (12) associates a frequency at which an explanatory variable included in each of a plurality of areas, which are obtained by dividing an explanatory variable space, is acquired by the acquisition unit (11) with each of the plurality of areas, and specifies an area to which an explanatory variable included in learning data used to learn the model (37) belongs and in which a frequency of an explanatory variable acquired by the acquisition unit (11) is a predetermined value or less, and an update unit (14) updates the model (37) in such a manner that learning data including an explanatory variable belonging to an area specified by the specification unit (12) is forgotten.

Abstract: An information management system includes a storage unit configured to store a database including a bill of materials, a bill of process, and a bill of equipment. Each of the bills includes designation of an approver for included information. An information management system includes: a search module configured to search an item corresponding to a change content that is a content of a change from the database in response to generation of a change to a production site or generation of a change to be reflected in the production site, and search the approver of the searched item; an approval request module configured to request the searched approver to approve the reflection of the change content in the database; and an update module configured to reflect the change content in a corresponding item of the database in response to the approval from the approver.

Abstract: A prediction control development device according to one aspect of the present invention generates a prediction model of a control amount by analyzing first time-series data of the control amount and provides the generated prediction model to a controller. The prediction control development device acquires second time-series data showing transition of a value of the control amount during prediction control using the prediction model, and evaluates prediction accuracy of the prediction model based on a difference between a prediction value by the prediction model and a value of the second time-series data. When the prediction accuracy of the prediction model is not allowable, the prediction control development device analyzes the second time-series data to newly generate a prediction model of the control amount, and provides the newly generated prediction model to the controller.

Abstract: The present invention reduces the probability of malfunction occurrence when performing predictive control of a device being controlled. In this control device of one aspect of the present invention, a prediction model for a control variable is used to calculate a prediction value from a measured value of the control variable, and a desired command value of the control variable is determined by correcting a desired basic value in accordance with the calculated prediction value. The degree of correction is determined on the basis of weight. The control device controls the operation of the device being controlled according to the determined desired command value. The control device assesses whether the device being controlled is operated appropriately on the basis of monitoring data relating to the operation result of the device being controlled, and optimizes the weight of the correction to make appropriate control possible based on the assessment result.

Abstract: The disclosure provides an additional learning device, an additional learning method, and a storage medium. The additional learning device includes: an acquisition unit acquires information based on data observed in a control object which is controlled by an instruction in accordance with an output from a previously learned model outputting an objective variable with respect to an explanatory variable. A determination unit determines whether or not the explanatory variable corresponding to the information acquired by the acquisition unit exists as learning data of the model, that is, whether or not the explanatory variable is unknown. When the explanatory variable is determined to be unknown by the determination unit, an additional learning unit acquires the objective variable corresponding to the unknown explanatory variable, correlates the unknown explanatory variable and the acquired objective variable, and additionally learns the model.