A computing system for building a virtual factory includes database and a virtual factory building module. The database stores modeling data. The virtual factory building module builds the virtual factory in which a progress situation of a work performed from a first portion to a second portion is displayed, based on the modeling data and a time difference between an output time of a first signal and an output time of a second signal, which is calculated based on the first signal output when a product is at a first portion on one or more facilities monitored from a first location present in an outside of the one or more facilities used in a real factory and the second signal output when the product is at a second portion on the one or more facilities monitored from a second location present in the outside of the one or more facilities. The first location is spaced from the second location, and the first portion is spaced from the second portion.

A resource management system for modular plants includes a database providing a module library of semantic modules representing respective modules in a module pool. At least one of the semantic modules includes a semantic description of the respective module, where the semantic description includes abstract data according to a semantic data model, and where the abstract data describes attributes of the respective module not found in a standard description file for the module. Based thereon, the system facilitates automated generation and optimization of module pipelines.

An arithmetic device includes a deformation amount acquisition unit that acquires an actual measurement deformation amount of a fabrication object that is manufactured based on a target shape, the actual measurement deformation amount corresponding to a deviation amount of a shape of the fabrication object from the target shape, an analysis unit that performs an analysis, based on the target shape of the fabrication object and a reference inherent strain value corresponding to a reference value of an inherent strain of the fabrication object, and acquires an analytical deformation amount corresponding to a deviation amount of the shape of the fabrication object in the analysis from the target shape, and a strain calculation unit that calculates an estimated inherent strain value corresponding to an estimated value of the inherent strain of the fabrication object with the target shape, based on the actual measurement deformation amount and the analytical deformation amount.

A digital twin modeling and simulation method includes generating a manufacturing model ontology, acquiring field data, and generating a semantic model instance based upon the manufacturing model ontology and the field data. In an embodiment, the method further includes searching for the attribute of the field data according to the type of the field data, extracting data from the semantic model instance according to the search result, and simulating the semantic model instance on a simulation platform. A digital twin modeling and simulation mechanism provided by an embodiment has the flexibility of wide application and reduces the dependence on experts in this field.

The disclosure is directed to a novel system and methods for modeling process components using segmental analysis. As opposed to analyzing the entire system at once, each element representing a process component is assigned parameter inputs that enable the system to determine a current state. Changes in the element's parameter inputs are fed in a bi-directional manner to other elements connected by segments where the other elements use the parameter inputs to determine a predictive or current process condition that are used as new parameter inputs for the next element. In some embodiments, the system allows for the prevention of component state change with only a portion of the entire process being solved, as abnormal conditions can be detected without solving for the entire system.

A physical function training device that measuring an amount of exercise automatically enables a user to use safely by determining an appropriate amount of exercise automatically and reduces specialist labor by automatically organizing to manage the actual exercise is provided. A physical function training device equips following; a control unit (20) is composed of a distance detection sensor (16) and, a number of times detection sensor (18) as a detection device for data related to a motion of upper or lower limbs and a storage unit (521); a control unit (20), which enables analyzing exercise data received by a detection device is composed of Various Arduino, NanpPi, RaspberryPi, microcomputer, etc.; and a storage unit (521), which is included in the control unit (20) records personal identification data, exercise data collected, collected time data of the exercise data at the time of enforcement from a time measurement apparatus (20a).

A system and method for generating a holistic digital twin of an industrial facility that includes a plurality of assets, wherein the said system includes conversion units configured to convert asset related data collected from different tools utilized to plan and/or operate the industrial facility in a tool specific data format and asset related data provided by data sources of the industrial facility in a data source specific data format into a common graphical representation, a matching unit configured to match the common graphical representations of the converted asset related data to provide a mapping between the assets of the industrial facility, and a merging unit configured to merge the mapped assets of the industrial facility into a unified graph to provide the holistic digital twin of the industrial facility.

A system for using digital twins to interact with physical objects in an automation system includes a plurality of controller devices, a process image backbone, and a registry comprising a plurality of digital twins. Each respective controller device comprises a volatile computer-readable storage medium comprising a process image area. The process image backbone provides the controllers with uniform access to the process image area of each controller. Each digital twin in the registry corresponds to a physical device controllable via one of the controllers devices via a corresponding process image area.

In some embodiments, systems, devices, and methods described herein provide digitized ecosystem architectures connecting systems and processes within and among various entities using Internet-of-Things (IoT) to integrate physical assets of the entities. In some embodiments, one or more blockchain applications and/or smart contracts and further define and manage system integration.

Configuring distributed control in an industrial system comprises building an asset model representative of a process control installation of the industrial system and creating an asset library of distributed control assets according to a distributed control programming standard. The asset model includes modeled assets defined according to levels of a physical model standard and representing physical devices of the industrial system. The distributed control assets each have one or more predefined, built-in facets. One of the distributed control assets in the asset library is mapped to each of the modeled assets to configure the process control installation of the industrial system and generate an asset-based control application for providing distributed control of the industrial system. Additional aspects relate to auto-creation of control applications based on an information model, either through the use of machine learning or an asset configurator tool.