A tree search-based scheduling method and an electronic apparatus are provided. In the method, multiple order lists are received and a schedule is initialized, wherein each order list includes multiple production operations. In each order list, a first production operation which has not been joined into the schedule yet is selected, such that multiple prior operations are selected. An execution priority of the prior operations is calculated according to multiple dispatching rules, and multiple candidate operations are selected from the prior operations according to the execution priority. Afterwards, the candidate operations are listed as a next operation of the schedule respectively, and a scheduling simulation is performed according to the dispatching rules to obtain multiple scheduling indicators of the candidate operations. Scheduling is performed according to the scheduling indicators.

A recipe management system includes a versioning system that tracks the revision history of templates and their child instances. Modifications to templates and instances create new records with new primary key identifiers and version identifiers. However, each new version of a template or instance has the same root identifier as the prior versions. When a template is modified, a flag is set in its child instances, but they are not modified automatically. When an instance is modified, it has no effect on the parent template. At runtime, a recipe model is loaded to an equipment model to execute a recipe on a piece of equipment. Only approved versions of equipment models are used during execution, even if newer versions exist. During execution, new equipment models can be created. The recipe management system includes an execution engine that can be hosted as a standalone executable or in a system platform.

A tree search-based scheduling method and an electronic apparatus are provided. In the method, multiple order lists are received and a schedule is initialized, wherein each order list includes multiple production operations. In each order list, a first production operation which has not been joined into the schedule yet is selected, such that multiple prior operations are selected. An execution priority of the prior operations is calculated according to multiple dispatching rules, and multiple candidate operations are selected from the prior operations according to the execution priority. Afterwards, the candidate operations are listed as a next operation of the schedule respectively, and a scheduling simulation is performed according to the dispatching rules to obtain multiple scheduling indicators of the candidate operations. Scheduling is performed according to the scheduling indicators.

A work center in a manufacturing setup includes a machine learning model that uses a decision tree to facilitate the work of a supervisor on the production line to choose a machine to perform a particular operation on a particular part. The decision tree outputs a ranking of machines indicating the suitability of the ranked machines for performing the particular operation on the particular part.

A workpiece processing system and method to process a workpiece in processing chambers in order, in which even if processing duration varies at any chamber, such a variation does not affect the processing of the workpiece in other chambers. Each chamber performs processing of a workpiece in a predetermined order; a conveyor that conveys a workpiece to a next chamber; and a control device controls at least a start time of predetermined processing at each processing chamber. The control device sets: predetermined representative processing at a first chamber as a reference processing step, start time of the reference processing step as control start time, necessary processing duration specific to each chamber, necessary conveyance duration required to convey a workpiece between the chambers, and controls starting of the representative processing at each chamber while considering the control start time as origination.

An industrial control system stores three types of models. Models of a first type are associated with models of a second type. When a model of the first type is associated with a model of a third type, the set of models of the second type that are associated with the model of the first type is established. The industrial control system can provide an indication of the set of models of the second type. The industrial control system also establishes the set of models of the first type that are associated with the set of models of the second type. The industrial control system provides an indication of the set of models of the first type. In some embodiments, the industrial control system is a recipe management system and the models of the first, second, and third types are capability models, equipment models, and recipe models.

A recipe management system executes a recipe on a piece of equipment in a process plant using one or more capabilities of the piece of equipment. A configuration system creates models of the capabilities, piece of equipment, and recipe and associates the capability models with the equipment model and recipe model. The recipe model can be used to execute the recipe on any piece of equipment with the capabilities with which it is associated. The equipment model can be used to execute any recipe that uses no capabilities other than those with which it is associated.

Systems and methods are provided for decision making and/or control in multi-agent systems. The methods include receiving objectives of a mission that includes agents performing actions in an operational area, activating an active mode selected from two or more modes for a first agent, wherein each of the modes include actions that the first agent may perform and control algorithms for executing the actions, and directing the first agent by: initiating a current action based on the control algorithms, receiving and processing sensor data and/or communication data from the agents and/or other systems, updating a hybrid state estimator based on the sensor data and/or communication data, generating an estimation of a current state of the mission with the hybrid state estimator, and activating one of the modes for the first agent in accordance with confidence-based transition logic based on the estimation generated by the hybrid state estimator.