A method and computer program product for monitoring one or more processes occurring during a first portion of a multi-portion recipe being executed on a processing device to obtain data concerning at least of portion of the one or more processes. At least a portion of the data is stored. The availability of the at least a portion of the data is enabled to one or more processes occurring during a second portion of the multi-portion recipe.

A computer-implemented method determines a property of a machine, in particular a machine tool, without metrologically capturing the property. The method includes the following steps: capturing one or more first time series of one or more physical measurement variables of the machine; detecting change points in the one or more first time series; extracting pattern-sequence instances from the first time series on the basis of the detected change points; producing a plurality of pattern-sequence classes in accordance with the extracted pattern-sequence instances; identifying at least one characteristic of a plurality of pattern-sequence instances of the same pattern-sequence class and a time curve of the characteristic; determining a property of a machine using the determined characteristic and/or using the time curve of the determined characteristic.

An online prediction method of tool-electrode consumption adapted for an electrical discharge machining (EDM) apparatus includes an experimental design; extracting electrode consumption variables from machining parameters of the electrical discharge machining (EDM) apparatus; and obtaining a correlation between the machining parameters and the electrode consumption variables through a correlation analysis to obtain a prediction model capable of predicting an effective contact area of a tool-electrode and a workpiece. In addition, a prediction method of machining accuracy is provided.

A smart digital computer platform is disclosed that collects, analyzes, and/or renders appropriate information about fugitive emissions identified by a sensor network-based emissions monitoring system in a facility. More specifically to the methods used by the smart digital computer platform to analyze, filter, and transform the collected monitoring data into a visual output that is capable of being rendered on a graphical user interface (GUI) on a screen display with, in some embodiments, a restricted form factor. For example, smart analytics may be used to cull, filter, and transform the data displayed in a pop-up dialog box on a GUI. In another example, the transformed data may be translated into a visual, graphical element that conveys an abundance of appropriate, tailored information to a particular type of user viewing the GUI.

A display system according to one or more embodiments includes: a control unit; a display unit; and a storage unit. The storage unit is configured to store a causal relationship model representing a relationship between two or more components of the plurality of components and an abnormality that may occur in the production facility, and the control unit is configured to: display, on the display unit, a model diagram that has nodes and one or more edges connecting the nodes to each other, based on the causal relationship model; and in response to a mode selection, such as a request from a user, display the model diagram in either a first mode in which all the nodes are displayed, or a second mode in which the nodes are allocated among a predetermined number of groups based on a predetermined criterion and the groups are displayed as nodes.

A monitoring apparatus according to the present invention includes: a detecting unit configured to detect that a monitored object is in a preset specific state based on a plurality of measured values measured from the monitored object; and a specifying unit configured to specify, among elements causing the measured values, the element related to detection of the specific state of the monitored object based on the measured values, and also specify the element based on preset properties of the elements of the measured values.

A method and industrial automation system for controlling performance of batch process includes obtaining operational data and Key Performance Indicators (KPI's) for a batch process. The operational data is provided with an absolute timestamp such that absolute timestamp associated with operational data and KPI's is converted to time duration relative to predefined event. The obtained operational data and KPI's, and reference set of operational data and KPI's are aligned based on time duration relative to a predefined event. The method comprises comparing aligned operational data and the KPI's with the reference set of KPI's and operational data. Based on comparison, one or more reference batches are determined. The method comprises identifying one reference batch based on predefined criteria. Thereby, the method involves controlling performance of batch process by providing modified setpoints based on identified reference batch.

A distributed automation control system includes a network for connecting members of the system to a central server for communication between the members and the central server. The members can include a device controlled by a microcontroller in communication with the network, a mobile object digitized to communicate with the central server via the network, and a facility component in communication with the central server. A member can be assigned to one or more groups of members for group learning and for generating a group heartbeat. Each member defines a safety volume which is monitored by the central server. When the safety volume of one member overlaps the safety volume of another member, the central server initiates a responsive action which can include ceasing the operation of at least one of the members.

The present disclosure relates to manufacturing a pharmaceutical compound according to a manufacturing process. The manufacturing process comprises process parameters and rules that use the process parameters as literals. A control system determines a partition of the rules into subsets of rules, each being independent from the other subsets of rules in relation to the literals used in the rules. The controller creates simplified representations of the manufacturing process, which comprise the literals from a corresponding subset of rules and are created by eliminating literals used by other subsets of rules. The controller checks compliance of the manufacturing process based on the simplified representations of the manufacturing process by comparing values of the literals of a current process execution against literals in the simplified representations and adjusts the manufacturing process where the comparing identifies a difference. The controller repeats the steps of checking and adjusting until no differences are identified.

A manufacturing device monitoring system includes a plurality of manufacturing devices and a remote monitoring device. The manufacturing device includes a work unit, an equipment notifier, an error detector, and an error notifier. The error notifier determines whether or not an error detected by the error detector may be corrected by an operation from the remote monitoring device, notifies the remote monitoring device of the occurrence of the error in a case where the error can be corrected, and operates the equipment notifier to notify a first notification pattern in a case where the error cannot be corrected.