The present disclosure provides an Industrial Internet of Things for automatic executing product manufacturing based on a task, comprising a task module, a process processing module, and an analysis module. The task module is configured to generate a product manufacturing task and a first instruction corresponding to the product manufacturing task, the process processing module is configured to determine manufacturing process information based on the first instruction, decompose the manufacturing process information and generate sub-process manufacturing data, and the analysis module is configured to compose a set of manufacturing data based on the sub-process manufacturing data and the process execution time, perform a manufacturing feasibility analysis based on the set of manufacturing data, in response to a determination that an analysis result of the manufacturing feasibility analysis is feasible, perform the product manufacturing corresponding to sub-process based on the sub-process manufacturing data.

The present invention is in the field of computer-implemented methods for determining the carbon footprint of a product in a production process in a production plant, in particular of a product in interconnected production processes. Certain embodiments of the present invention relate to a computer-implemented method for determining the carbon footprint of a product produced in production process of a production plant.

The present invention is in the field of computer-implemented methods for determining the carbon footprint of a product in a production process in a production plant, in particular of a product in interconnected production processes. Certain embodiments of the present invention relate to a computer-implemented method for determining the carbon footprint of a product produced in production process of a production plant.

The present invention is in the field of computer-implemented methods for determining the carbon footprint of a product in a production process in a production plant, in particular of a product in interconnected production processes. Certain embodiments of the present invention relate to a computer-implemented method for determining the carbon footprint of a product produced in production process of a production plant.

A method and device for simulating a production duration of a silicon-wafer slicer, including: constructing a slicer simulating model, wherein the slicer simulating model includes process-step data of the slicer, and the process-step data include: a loading process step, a cutting process step, a discharging process step, a rinsing process step, a waiting process step, a broken-line replacing process step, a guide-pulley replacing process step, a home-roll replacing process step and a paying-off-wheel replacing process step; in the slicer simulating model, according to a predetermined rule, obtaining a process-step-to-be-executed datum; according to historical data, for the process-step-to-be-executed datum, assigning duration data that individually correspond to the process-step-to-be-executed data, wherein the historical data include: historical duration data that individually correspond to the process-step data of the slicer; and executing sequentially the process steps in the process-step-to-be-executed data, and obtaining a sum of the duration data of the process steps.

An industrial CAD system is supplemented with features that allow a developer to easily convert a mechanical CAD model of an automation system to a dynamic digital twin capable of simulation within a simulation platform. The features allow the user to label selected elements of a mechanical CAD drawing with “aspects” within the CAD environment. These aspect markups label the selected mechanical elements as being specific types of industrial assets or control elements. Based on these markups, the CAD platform associates mechatronic metadata with the selected elements based on the type of aspect with which each element is labeled. This mechatronic metadata defines the behavior (e.g., movements, speeds, forces, etc.) of the selected element within the context of a virtual simulation, transforming the mechanical CAD model into a dynamic digital twin that can be exported to a simulation and testing platform.

A control design and testing system simplifies the execution of parallelized control testing simulators using emulation techniques. The system is capable of emulating large and complex industrial systems using a combination of selective model partitioning, space parallel simulation, and co-simulation. According to this approach, a digital model of the industrial automation system is partitioned into sub-models such that inter-model logical relationships between the sub-models comprise only logical relationships that can tolerate a temporal error equal to or less than a duration, or timestep, of a co-simulation cycle. The sub-models are deployed to separate processing spaces, and the system uses co-simulation to execute a parallel emulation of the sub-models.

An energy monitoring system includes a memory storing instructions to execute an energy modeling technique and processing circuitry for executing the instructions to operate the energy modeling technique. The energy modeling technique includes receiving energy data from a plurality of segments representative of one or more logical subgroups. The energy modeling technique includes categorizing the energy data of the logical subgroups into a plurality of segments. The energy modeling technique includes organizing the plurality of segments into a plurality of state-based hierarchical levels. The energy modeling technique includes calculating energy usage and factors associated with the plurality of state-based hierarchical levels via an energy model. The energy modeling technique includes outputting a visualization representative of the energy data corresponding to each of the segments to a monitoring and control system, resulting in a graphical representation accessible by a user-viewable screen.

An industrial CAD system is supplemented with features that allow a developer to easily convert a mechanical CAD model of an automation system to a dynamic digital twin capable of simulation within a simulation platform. The features allow the user to label selected elements of a mechanical CAD drawing with aspects within the CAD environment. These aspect markups label the selected mechanical elements as being specific types of industrial assets or control elements. Based on these markups, the CAD platform associates mechatronic metadata with the selected elements based on the type of aspect with which each element is labeled. This mechatronic metadata defines the behavior (e.g., movements, speeds, forces, etc.) of the selected element within the context of a virtual simulation, transforming the mechanical CAD model into a dynamic digital twin that can be exported to a simulation and testing platform.

An energy monitoring system includes a memory storing instructions to execute an energy modeling technique and processing circuitry for executing the instructions to operate the energy modeling technique. The energy modeling technique includes receiving energy data from a plurality of segments representative of one or more logical subgroups. The energy modeling technique includes categorizing the energy data of the logical subgroups into a plurality of segments. The energy modeling technique includes organizing the plurality of segments into a plurality of state-based hierarchical levels. The energy modeling technique includes calculating energy usage and factors associated with the plurality of state-based hierarchical levels via an energy model. The energy modeling technique includes outputting a visualization representative of the energy data corresponding to each of the segments to a monitoring and control system, resulting in a graphical representation accessible by a user-viewable screen.