Abstract:
The invention provides an implementing method of cloud numerical control system. The method implements a numerical control system with functions of online error compensation, CAD/CAPP/CAM/CNC integrating and interactively cooperative assembling machining control. The cloud numerical control system includes a small cloud numerical control system a large cloud numerical control system. The small cloud numerical control system focuses on inside control of a single numerical control machining device and includes a cloud control core node, cloud measure and control subnodes and fine-tuning driving units. The large cloud numerical control system is based on the small cloud numerical control system and performs interactively cooperative machining between multiple numerical control machining devices for different workpieces to be assembled.
Abstract:
Systems and methods for automated commissioning of virtualized distributed control systems are disclosed. An example method includes accessing a data structure including a list of configuration names for network cards associated with first and second host servers of a virtual process control environment. The first and second host servers implement virtual machines corresponding to workstations for a process control system. The example method also includes when configuring the first host server, assigning a first name to a first one of the network cards associated with the first host server. The example method further includes when configuring the second host server, assigning the first name to a second one of the network cards associated with the second host server based on a user selection of the first name from the list of configuration names. The second host server is configured after the first host server.
Abstract:
Systems and methods for simulating operations of a Fieldbus system (FS). The FS (200) includes a Fieldbus interface module (FIM) coupled to field devices. The methods involve creating a simulation computer model (SCM) of the FS, generating simulation data records (SDRs), and running simulation software (SS). The SS is installed on a computer system (242), FIM (232, 234), or embedded device (222, 226). The SS simulates at least one operation of the FS. The SS uses at least a portion of the SCM and at least one of the SDRs. The SCM includes functional blocks and interconnections between the functional blocks. The functional blocks represent the FIM and/or field devices. The SDRs include data defining the SCM, a control strategy of the FS, and communication links between the FIM and field devices. The SDRs also include data defining the operating characteristics of the FIM and field devices.
Abstract:
A hyperconverged industrial process control architecture is disclosed for controlling an industrial process within a physical process environment using a software-defined distributed control system (DCS) environment. The software-defined DCS environment may be implemented by virtualizing the hardware components of a DCS architecture on a server group to enable both software-defined process controllers and back-end DCS applications to run within the server group. This software-defined DCS network architecture reduces the hardware requirements of the process control system and reduces configuration complexity by implementing control components and higher-level components within a common environment within the server group.
Abstract:
A system and method for operating a remote plant simulation system is disclosed. The system and method uses a light application at the plant to collect relevant data and communicate it to a remote plant simulation. The remote plant simulation uses the relevant data, including data from the actual process, to create a process simulation and communicate the display data to the light application operating at the plant where it is displayed to a user. The remote system offers the advantage of offering decreased cost and improved simulation as the equipment cost, operator cost and set up cost is shared by a plurality of users. Further, the data may be stored remotely and subject to data analytics which may identify additional areas for efficiency in the plant.
Abstract:
A component of a material flow system for transporting goods has a mechatronics arrangement with transport elements, sensors and actuators for transporting the goods, a control device for controlling the mechatronics arrangement, interfaces to adjacent components and the surroundings, and an internal simulator for determining the future state of the component. The internal simulator co-operates with internal simulators of other components of the material flow system, for determining a prognosis of the future state of the installation of the material flow system. The decentralised internal simulators can be synchronously or asynchronously activated.
Abstract:
Systems (200, 230, 240) and methods (700) for controlling a simulation of an operation of a Fieldbus system (100) comprising at least one FIM (114, 116) communicatively coupled to field devices (122, 124). The methods involve initiating a current simulation (CS) of an operation of the FIM and/or field devices. The methods also involve obtaining intermediate simulation information (ISI) indicating a status/progress of CS. The methods further involve displaying ISI to a user of a simulation system and displaying visual elements (610, . . . , 620) for controlling the progress of CS to the user. Gantt charts (672, 674) for the FIM/field devices and visual content showing data exchanges between software elements and/or hardware elements of the simulation system can further be displayed to the user. The visual elements can facilitate speeding up CS, slowing down CS, moving the progress of CS backwards/forwards, and/or stopping/re-starting the CS.
Abstract:
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.
Abstract:
Systems (200, 230, 240) and methods (700) for controlling a simulation of an operation of a Fieldbus system (100) comprising at least one FIM (114, 116) communicatively coupled to field devices (122, 124). The methods involve initiating a current simulation (CS) of an operation of the FIM and/or field devices. The methods also involve obtaining intermediate simulation information (ISI) indicating a status/progress of CS. The methods further involve displaying ISI to a user of a simulation system and displaying visual elements (610, . . . , 620) for controlling the progress of CS to the user. Gantt charts (672, 674) for the FIM/field devices and visual content showing data exchanges between software elements and/or hardware elements of the simulation system can further be displayed to the user. The visual elements can facilitate speeding up CS, slowing down CS, moving the progress of CS backwards/forwards, and/or stopping/re-starting the CS.
Abstract:
A high fidelity distributed plant simulation technique includes a plurality of separate simulation modules that may be stored and executed separately in different drops or computing devices. The simulation modules communicate directly with one another to perform accurate simulation of a plant, without requiring a centralized coordinator to coordinate the operation of the simulation system. In particular, numerous simulation modules are created, with each simulation module including a model of an associated plant element and these simulation modules are stored in different drops of a computer network to perform distributed simulation of a plant or a portion of a plant. At least some of the simulation modules, when executing, perform mass flow balances taking into account process variables associated with adjacent simulation modules to thereby assure pressure, temperature and flow balancing (i.e., conservation of mass flow) through the entire simulation system. In a dynamic situation, a transient mass storage relay technique is used to account for transient changes in mass flow through any non-storage devices being simulated by the simulation modules. Moreover, adjacent simulation modules located in different drops communicate directly with one another using a background processing task, which simplifies communications between adjacent simulation modules without the need for a central coordinator.