A data processing device includes: a collector that collects setting values in operating elements that control a production process for a product at prescribed intervals and collects brand information indicating a brand of the product; a first processor that performs a statistical process for the setting values, obtains representative values for the setting values as operation performance values while the product of the brand indicated in the brand information is being produced, and generates a performance value database; a second processor that performs a statistical process for operation performance values associated with brand information indicating a next brand to be produced in the production process among the operation performance values included in the performance value database, and obtains optimal setting values in the operating elements for producing the product of the next brand; and an outputter that outputs the obtained setting values.

A trace assistance device includes a memory section, an acquisition section, and an output section. The memory section stores a manipulation log and an operation log. When a predetermined trigger event occurs during the board work, the acquisition section acquires at least one target manipulation history related to the trigger event, a target operation history associated with the target manipulation history, a comparison manipulation history that is the same as or similar to the target manipulation history, and a comparison operation history associated with the comparison manipulation history from the manipulation log and the operation log stored in the memory device. The output section is configured to output an operation of the board production line recorded in the target operation history and an operation of the board production line recorded in the comparison operation history, which are acquired by the acquisition section, in a comparable manner.

Systems, methods, and computer program products for remaining useful life prediction. Operational data is collected from a test machine until a component fails, and a training dataset generated from the operational data. The training dataset is used to define and validate a prediction model. Operational data received from one or more field machines is provided to the prediction model. The prediction model then predicts the remaining useful life of the component of the field machine. To reduce the time-to-failure of the component in the test machine, the component may be repeatedly subjected to an accelerated wear cycle. The prediction model may be defined by extracting features from the training dataset. Like features may be extracted from the field dataset and provided to the prediction model as part of the prediction process. The operational data received from the field machines may be used to generate an updated prediction model.

A control device, includes: a modification instruction receiving unit for receiving modification instructions for a control parameter and for machining program; a history storage unit for causing a storage unit to store a modification history for the control parameter and the machining program; an Undo/Redo processing unit for performing an Undo/Redo process based on the modification history; a determination unit for determining whether a prescribed condition has been met; and a history deletion control unit for deleting the change history stored in the storage unit when the determination unit has determined that the prescribed condition has been met.

2Systems and methods described herein use context-adaptive resolution to achieve lossless transfer of critical industrial control system data. Bandwidth and storage optimization is achieved for time-series data generated or collected by an industrial control system and transmitted through a network to a remote historian system. The control system may be implemented through one or more embedded historians and local historians. The control system continuously processes input data, computes output variables, and generates an event trigger when a set of variables meet pre-defined set of conditions. When there are no active event triggers, the control system publishes time-series data for a pre-defined set of variables at a lower resolution to conserve bandwidth and storage. When an event trigger is activated, the control system publishes recent and current time-series data for a subset of the variables to subscribers at a higher resolution.

An industrial machine is an industrial machine which has a history recording function, and includes: a manual pulse generator which includes a handle for manually operating the position of a drive axis in the industrial machine by an operator; a drive axis control unit which controls the drive axis according to the operation of the handle; a handle operation determination unit which determines the operation of the handle; and an operation history recording unit which records, as an operation history, the operation of the handle determined with the handle operation determination unit, and when the number of rotations of the handle exceeds a threshold value, the handle operation determination unit determines the operation of the handle, and the operation history recording unit records, as the operation history, the operation of the handle.

An object is to provide a control system of a machine tool which can efficiently return the set state of parameters for CNC to a previous set state. A storage unit which stores parameter change history data and parameter attribute data and a change history organization unit which uses the parameter change history data and the parameter attribute data to organize parameters for each of change history attributes and which thereby generates a change history attribute unit list are included. Moreover, a change history display unit which displays the change history attribute unit list, a Undo/Redo target selection unit which specifies arbitrary parameters in the change history attribute unit list obtained by organizing the parameters for each of the change history attributes and a parameter setting return processing unit which performs return processing for returning to the parameters specified in the Undo/Redo target selection unit are included.

Methods according to the disclosure include: identifying at least one non-candidate tool which previously processed at least one prior semiconductor wafer, and represented in a set of historical data, the set of historical data including manufacturing settings for performing an operation on the at least one prior semiconductor wafer, and a candidate tool which has not previously performed the operation on at least one prior semiconductor wafer, the candidate tool not being represented in the set of historical data; determining whether the set of historical data predicts the performing of the operation with the candidate tool based on the manufacturing settings for performing the operation on the at least one prior semiconductor wafer; and in response to the set of historical data predicting the performing of the operation with the candidate tool, selecting a manufacturing setting for the candidate tool based on the set of historical data.

A non-transitory computer-readable recording medium stores therein a program utilization support program that causes a computer to execute processing including: obtaining first data items included in production management data; specifying second data items which are used in execution of a production support program with reference to a storage that stores information indicating an execution status of the production support program; and determining whether the production support program is usable based on whether all of the second data items are included in the first data items.

Methods according to the disclosure include: identifying at least one non-candidate tool which previously processed at least one prior semiconductor wafer, and represented in a set of historical data, the set of historical data including manufacturing settings for performing an operation on the at least one prior semiconductor wafer, and a candidate tool which has not previously performed the operation on at least one prior semiconductor wafer, the candidate tool not being represented in the set of historical data; determining whether the set of historical data predicts the performing of the operation with the candidate tool based on the manufacturing settings for performing the operation on the at least one prior semiconductor wafer; and in response to the set of historical data predicting the performing of the operation with the candidate tool, selecting a manufacturing setting for the candidate tool based on the set of historical data.