A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

A scalable industrial data ingestion and analysis architecture integrates and collects data from multiple diverse sources at one or more industrial facilities. Data sources can include plant-level industrial devices and higher-level business systems. The data can be integrated and collected from multiple sources at an on-premise edge or gateway device, which sends the data to event queues on the cloud platform. The data queues orchestrate and store the data on cloud storage, and an analytics layer performs business analytics or other types of analysis on the stored data to produce various outcomes. Similar analytic platforms can also be implemented at the device level, and analytic functions can be scaled between the device level and higher levels in accordance with the scope of a given analytic function.

A diagnostics system for rapid industrial network troubleshooting for an automation system includes a user interface device with a memory device storing a computer program with executable instructions; an automation component with an identification tag; and a communication network interfacing with the user interface device and the automation component, and adapted to transmit data. The computer program of the user interface device includes instructions to establish communication with the automation component based on data of the identification tag via the communication network, and instructions to retrieve diagnostics data of the automation component via the communication network after establishing communication with the automation component. Further, a diagnostics method and a computer program product for rapid industrial network troubleshooting for an automation system are provided.

A manufacturing process visualization apparatus is provided. The apparatus includes: at least one processor configured to implement: a data receiving unit which receives apparatus data from at least one production apparatus of a manufacturing process line processing a plurality of products; and a matching unit which extracts product record information about each of the products from the received apparatus data, classifies the extracted product record information as information corresponding to specific product flow properties of the manufacturing process line, generates product flow information indicating the specific product flow properties by using the classified product record information, and generates graphic process information about the manufacturing process line in which the product flow information about each product is represented in graphics; and a screen display which displays the generated graphic process pattern information on a screen.

A system and method for monitoring, operating and maintaining an industrial plant in the metal-producing industry, including: a mobile terminal device with at least one sensor for recording measured values within the industrial plant, at least one position sensor for detecting the position of the mobile terminal device in the industrial plant, a central data processing device for processing the measured values recorded by the mobile terminal device by the at least one sensor, taking into account the position of the mobile terminal device recorded by the at least one position sensor in the industrial plant, and at least one communication network for exchanging data between the mobile terminal device, the at least one position sensor and/or the central data processing device.

The present invention refers to an ECOSCEL supervisory system with application in the E&P area, particularly in the control rooms of offshore production platforms, or in onshore plants, aiming to allow a summary of the process in only two screens, in which all the most important variables used are concentrated. The flexibility of inserting important variables and notifications allows, at any time, a rapid update of the operational demands of the control room administrators. With the visual organization of the ECOSCEL supervisor, the operator of control room can immediately perceive a variable outside the range, in time to intervene with appropriate control actions to prevent (shutdown) of a piece of equipment, system or process.

Disclosed herein are a method and system for providing backwards compatibility between software versions of supervisory system software executing on a supervisory system and on device control software executing on a device under control of the supervisory system, wherein the on device control software executes on a computing module located on the device to act as an intermediary between the supervisory system and device software running on the device. Providing backwards compatibility between software versions enables upgrade schedules to be more flexible and no longer requires the supervisory system and all devices under control of the supervisory system to be upgraded at the same time.