Cloud-aware industrial devices feed robust sets of data to a cloud-based data analyzer that executes as a service in a cloud platform. In addition to industrial data generated or collected by the industrial devices, the devices can provide device profile information to the cloud-based analyzer that identifies the device and relevant configuration information. The industrial devices can also provide customer data identifying an owner of the industrial devices, contact information for the owner, active service contracts, etc. The cloud-based data analyzer leverages this information to perform a variety of custom analytics on the data and generate reports or notifications catered to the particular industrial assets' optimal performance and business goals of the owner's industrial enterprise, as well as perform real-time decision making and control.

Industrial data analytics in a cloud platform

A cloud-based operator interface system is provided that runs as a cloud service on a cloud platform The cloud-based operator interface system collects industrial data from one or more industrial systems via respective cloud gateway devices A set of predefined operator interface screens are stored on cloud storage associated with the operator interface system, and delivered to authorized Internet-capable client devices upon request The industrial data received from the cloud gateways can be delivered to the client devices from the cloud platform via the operator interface screens Additional cloud-side services can correlate and analyzes the industrial data on the cloud platform to facilitate additional reporting, alarming, and notification features

Cloud-based operator interface for industrial automation

A cloud-based performance enhancement service captures and collects data relating to interactions of users with industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform. The service employs a performance enhancement component that analyzes the data to facilitate determining correlations between certain user interactions and favorable performance of an industrial automation system, determining user interactions that are less favorable or unsafe, determining alternative actions that a user can take to achieve a same or similar preferred operational result, generating recommendations relating to the alternative actions, determining or designing components or techniques that can automate a preferred user action, determining improved user assignments in connection with the industrial automation system, and/or generating training modules or presentations based on preferred user actions that can be used to train users to more efficiently interact with an industrial automation system to achieve improved system performance.

Using cloud-based data for industrial automation system training

A cloud gateway for coupling an industrial system to a cloud platform is provided. The cloud gateway collects data from one or more industrial controllers, meters, sensors, or other devices comprising an industrial automation system. The cloud gateway optionally performs additional transformations on the data to add context, summarize, filter, reformat, and/or encrypt the data. The cloud gateway then sends data to a cloud platform for use by one or more cloud-based applications or services. The cloud gateway can facilitate cloud-based data collection from both fixed-location and mobile industrial systems. The cloud gateway can also support store-and-forward logic, allowing industrial data to be temporarily stored in local storage in the event that communication between the cloud gateway and the cloud platform is disrupted.

Cloud gateway for industrial automation information and control systems

A simulation environment for running a process simulation used to validate an industrial control program. The simulation environment exposes the I/O module configurations defined in the control program and retrieves module configuration information therefrom. This I/O module configuration information is combined with generic, module-specific I/O module profiles to create a pool of available controller I/O points, which can be selectively associated with I/O points in the simulation to create an I/O point mapping. During control program validation, simulated I/O data is exchanged between the process simulation and the I/O module instances in the controller in accordance with the I/O point mapping.

Industrial simulation using redirected I/O module configurations

A system for testing a distributed control system of an industrial plant is provided. The distributed control system includes at least two industrial control devices and at least one data communication device. The system includes at least one engineering computer that includes an engineering data storage unit for storing engineering data of at least one part of the distributed control system, and at least one human machine interface for manipulating the engineering data. The system also includes at least one remote data processing server connected to the at least one engineering computer via a remote data connection and including an emulating virtual machine on which a soft emulator is installed for emulating one of the at least two industrial control devices and the at least one data communication device.

System and method for testing a distributed control system of an industrial plant

The invention relates to a method and a system for debugging the control system of an industrial plant or parts of it, e.g. a factory cell, a factory line, a mechatronical unit, a machine, a process plant or parts of it, comprising at least two different control subsystems, of the same or different control equipment type, on plant or sub-system level, comprising specific programmable controller units in devices like PLCs, DCSs, robots, drives, instruments and/or other process specific components whereas all required parameters and signals of the control system across its sub-systems, devices, and technologies are extracted and visualized on a single sight and are utilized for the definition of system wide breakpoints, utilizing a subset of those signals or parameters, and related conditions, e.g. logical combinations of the signals or parameters.

Method for debugging of process or manufacturing plant solutions comprising multiple sub-systems

Engineering is a major cost factor in automation system projects Hence, both industry and academia aim to develop new methods and concepts to increase engineering efficiency However, the verification and comparison of those methods is difficult because the measurement of engineering efficiency is unsolved and is considered to be a possible breakthrough in the domain of engineering This paper proposes an approach to measure engineering efficiency in a systematic, reproducible and comparable way The proposed approach allows a systematic assessment of any new engineering method, tool or concept and hence allows a systematic comparison of alternatives To evaluate the proposed approach, an automatic measurement tool was developed and applied on a benchmark project First results are described and discussed

Ben Schroeter

Papers

System and method for testing a distributed control system of an industrial plant

Method for debugging of process or manufacturing plant solutions comprising multiple sub-systems

A novel approach to measure engineering efficiency of automation projects