Systems for providing efficient manufacturing of paper, sheet, and/or box products of varying size and structure, often with pre-applied print (“pre-print”), are provided herein. One or more controllers can be used to aggregate upcoming orders and information needed to complete the manufacturing process for the order. A controller enables a user to prepare control plans (e.g., reel maps, reel plans, etc.) for processing rolls of web product through the manufacturing process. Criteria filtering and/or various features enable generation of efficient and effective control plans for rolls of web product, including, in some cases, multiple orders. The control plan may include a set of instructions for operating one or more systems within the manufacturing process to form the desired finished paper-based product. In such a regard, efficient manufacturing of various paper-based products, including corrugated boxes, folded carton, labels, flexible paper, industrial bags, plates, cups, décor, and many others, can be achieved.

A cloud-based industrial controller that controls devices, processes, and other assets of an industrial automation system via control algorithms that execute on a cloud platform is presented. A cloud-based collection component collects information from the industrial automation system via cloud gateways associated with the industrial automation system or extrinsic data sources. The cloud-based industrial controller can monitor and analyze the information, generate control instructions based on the analysis results, and communicate the control instructions to the devices, processes, and/or other assets of the industrial automation system to control operation of the industrial automation system. The cloud-based industrial controller also can interface with a industrial plant-based industrial controller, wherein the cloud-based industrial controller can determine supplemental control instructions to the industrial plant-based industrial controller, based on the information, including extrinsic information, to assist in controlling the industrial automation system and control decision-making.

A method includes receiving, from one or more sensors associated with manufacturing equipment, current trace data associated with producing, by the manufacturing equipment, a plurality of products. The method further includes performing signal processing to break down the current trace data into a plurality of sets of current component data mapped to corresponding component identifiers. The method further includes providing the plurality of sets of current component data and the corresponding component identifiers as input to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, one or more outputs indicative of predictive data and causing, based on the predictive data, performance of one or more corrective actions associated with the manufacturing equipment.

A system for monitoring cutting devices in a packaging production line having a line for supplying a material to be cut, an area of a predetermined type of cutting device, and a packaging output line is provided. The system includes means for counting cutting actions of the cutting device, configured to provide a time series of cutting action counting data, a video camera to frame an area of the output line, the video camera configured to provide video data of packaging elements in the output line, first code means, configured to run, on a computer, a first algorithm for recognizing cutting defects starting from video data, the first algorithm providing defect recognition data, and second code means, configured to run, on the computer, a trained expert algorithm to predict cutting performance degradation based on historical defect recognition data, time series of cutting action counting data, and type of cutting device.

A method of preparing a self-aligned via on a semiconductor workpiece includes using an integrated sequence of processing steps executed on a common manufacturing platform hosting a plurality of processing modules including one or more film-forming modules, one or more etching modules, and one or more transfer modules. The integrated sequence of processing steps include receiving the workpiece into the common manufacturing platform, the workpiece having a pattern of metal features in a dielectric layer wherein exposed surfaces of the metal features and exposed surfaces of the dielectric layer together define an upper planar surface; selectively etching the metal features to form a recess pattern by recessing the exposed surfaces of the metal features beneath the exposed surfaces of the dielectric layer using one of the one or more etching modules; and depositing an etch stop layer over the recess pattern using one of the one or more film-forming modules.

The systems and methods described provide improved process control operating range and capabilities and integrate process control monitoring and management with broader process automation (PA) systems process management, extending the real-time operation and control of a process control system to process handling of a PA system, and extending PA-style process management by adding real-time process controls and monitoring, and adding new functionality by permitting management of these processes to externally defined completion goals. This combination provides new functionality in dynamically determined process flexibility, extended operating range and extended process recipe definition capabilities for process control systems using this technology, and provides improved error recovery and exception handling of traditional PA systems.

The present teachings relate to a method comprising a plurality of sensors, and one or more functionally connected processing units, the method comprising: providing, at any of the one or more processing units, time-series residual data of a sensor object; the sensor object being a group of at least some of the sensors from the plurality of sensors, and wherein the residual data comprises, for each of the sensors of the sensor object, a residue signal which is a difference between the sensor's measured output and the sensor's expected output, monitoring, via any of the one or more processing units, a level signal; wherein the level signal is indicative of a collective time-based variation of the time-series residual data, monitoring, via any of the one or more processing units, an association signal; wherein the association signal is indicative of the variation and/or association structure of the time-series residual data, generating, via any of the one or more processing units, an anomaly event signal when at a given time a value of the level signal and/or a value of the association signal changes from an expected value of the respective signal at or around that time. The present teachings also relate to a monitoring and/or control system for a plant comprising a plurality of sensors, wherein the system comprises one or more processing units configured to perform the method steps of any of the steps herein disclosed, and a computer software product.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A computer-based method for maintaining an autonomous or self-driving vehicle is provided. The method is implemented using a vehicle controlling (“VC”) computer device installed on the vehicle. The method may include determining that a maintenance operation is required for the self-driving vehicle, retrieving an operator schedule for an operator of the self-driving vehicle, retrieving a facility schedule for a facility, determining a time for performing the maintenance operation based upon the operator schedule, the facility schedule, and an amount of time required to (i) complete the maintenance operation, (ii) drive the self-driving vehicle from a first location to the facility to arrive at the determined time, and (iii) drive the self-driving vehicle to a second location, instructing the self-driving vehicle to drive from the first location to the facility to arrive at the determined time; and/or instructing the self-driving vehicle to drive from the facility a second location.

The present invention provides methods, systems and computer program products that enable the optimized synchronization of data between mobile client devices assigned to field operators in an industrial plant and a centralized repository for plant data. The invention optimizes synchronization of data between mobile client devices assigned to field operators in an industrial plant and a centralized repository for plant data by selecting a reduced set of data records associated with a field operator, for data synchronization based on one or more of a set of data record selection parameters, and a set of version synchronization rules to ensure that only data records that are relevant to a field operator's foreseeable activities in a shift are downloaded to the field operator's mobile client device.