A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A method that is used for self-learning manufacturing scheduling for a flexible manufacturing system that is used to produce at least a product is provided. The manufacturing system consists of processing entities that are interconnected through handling entities. The manufacturing scheduling will be learned by a reinforcement learning system on a model of the flexible manufacturing system. The model represents at least a behavior and a decision making of the flexible manufacturing system. The model is realized as a petri net.

An order of the processing entities and the handling entities is interchangeable, and therefore, the whole arrangement is very flexible.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A system and method include receiving, by a processing device of a manufacturing execution system (MES), a target profile associated with products, wherein the target profile comprises an identifier of a block of steps in a process to make the products and a target work-in-progress (WIP) value representing a target number of parts waiting to be processed by a group of machines used in the block of steps to make the products, identifying a move list or an assignment list that, when issued, causes the group of machines to operate to maintain a number of parts waiting for processing to match the target WIP value of the target profile.

A distributed industrial energy operation optimization platform which is capable of automatically constructing intelligent models and algorithms, is divided into three parts: a modeling terminal, a background service and a human-computer interface. The models like data pre-processing, energy generation-consumption-storage trend forecasting and optimal scheduling decision models are encapsulated in the modeling terminal as different visualization modules facing with multiple categories production scenarios, by dragging which the complex functional models can be realized conveniently. The background service is capable of automatically constructing the training samples and the production plans/manufacturing signals series according to the device model requirements of each edge side, interacts with the trained intelligent models through corresponding interfaces, and the computing results are saved in the specified relational database. The computing results are displayed through a friendly customer human-computer interface, and the real-time state of current working condition can also be adjusted.

The method for self-learning manufacturing scheduling for a flexible manufacturing system (FMS) with processing entities that are interconnected through handling entities is disclosed. The manufacturing scheduling is learned by a reinforcement learning system on a model of the flexible manufacturing system. The model represents at least the behavior and the decision making of the flexible manufacturing system, and the model is transformed in a state matrix to simulate the state of the flexible manufacturing system. A self-learning system for online scheduling and resource allocation is also provided. The system is trained in a simulation and learns the best decision from a defined set of actions for many every situation within an FMS. A decision may be made in near real-time during a production process and the system finds the optimal way through the FMS for every product using different optimization goals.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

Systems and methods for optimizing factory scheduling, layout or both which represent active factory elements (human and machine) as computational objects and simulate factory operation to optimize a solution. This enables the efficient assembly of customized products, accommodates variable demand, and mitigates unplanned events (floor blockages, machines/IMRs/workcell/workers downtime, variable quantity, location, and destination of supply parts).

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.