Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing a plan for one or more robots using a process definition graph. One of the methods includes receiving a process definition graph for a robot, the process definition graph having a plurality of action nodes. One or more of the action nodes are motion nodes that represent a motion to be taken by the robot from a respective start location to an end location. It is determined that a motion node satisfies one or more splitting criteria, and in response to determining that the motion node satisfies the one or more splitting criteria, the process definition graph is modified. Modifying the process definition graph includes splitting the motion node into two or more separate motion nodes whose respective paths can be scheduled independently.

A building management system (BMS) interface system. The BMS interface system includes a user interface and a BMS controller in communication with the user interface. The BMS controller includes a processor. The processor is configured to display a graphical scheduling interface on the user interface and receive a scheduling input from the user interface. The processor is further configured to extract one or more scheduling elements from the received scheduling input and convert the scheduling elements into one or more BMS data objects. The processor is further configured to update the graphical scheduling interface displayed on the user interface. The processor is also configured to execute one or more scheduling instructions based on the received scheduling input, wherein the scheduling instructions are associated with the operation of one or more BMS devices.

An operation state display device displays an operation state of a board production facility in which a board is sequentially conveyed to multiple board work machines, which perform predetermined board work on the board, and the board work is sequentially performed to produce a board product, and includes an acquisition section and a display section. The acquisition section acquires an execution time zone in which setup changing work required for switching a type of the board product to be produced is performed, for each board work machine, based on production information acquired by the board production facility during production of the board product. The display section graphically displays at least one of the execution time zone for each of the multiple board work machines and the execution time zone for a predetermined board work machine of the board production facility in time series.

Example implementations described herein involve systems and methods for operation of a robot configured to work on a first process and a second process, which can involve receiving sensor data indicative of a status of one or more of the first process and the second process; for the status indicative of the first process waiting on the robot, controlling the robot to work on the first process; and for the status indicative of the first process not waiting on the robot, controlling the robot to conduct one or more of work on the second process or return to standby.

A scheduling method using a knowledge graph (KG) performs following steps by a processor: obtaining an initial scheduling solution of the production system; converting the initial scheduling solution into triples to form the KG, each triples includes two entities and a relationship of the production system, the two entities indicate two production resources; embedding triples into a vector space to generate embedded vectors by a KG embedding technique; generating embedded vector combinations according to the embedded vectors and computing a distance of each of embedded vector combinations; and performing a scheduling algorithm to generate a target scheduling solution according to the embedded vector combinations, and providing reference information when the scheduling algorithm generates a schedule of a station, wherein the reference information comprises at least one of the embedded vector combinations associated with the station, and the distance corresponding to said at least one embedded vector combinations.

Provided is a production control system of a factory including: a plurality of machines; an air conditioner; a power computation unit for monitoring power consumption of an entire factory; a temperature information generation unit for generating information on temperature inside the factory; wherein running status and processing condition of the machines and running status of the air conditioner are controlled to produce the products dictated by the production plan by a delivery deadline; and a machine learning unit that learns a relationship of operational status including the running status and the processing condition of the machines and the running status of the air conditioner to environmental status including production completion time according to the operational status, the temperature inside the factory, and the power consumption of the factory, and outputs operational status that brings the environmental status to a desired condition in accordance with the production plan.

A building management system (BMS) interface system. The BMS interface system includes a user interface and a BMS controller in communication with the user interface. The BMS controller includes a processor. The processor is configured to display a graphical scheduling interface on the user interface and receive a scheduling input from the user interface. The processor is further configured to extract one or more scheduling elements from the received scheduling input and convert the scheduling elements into one or more BMS data objects. The processor is further configured to update the graphical scheduling interface displayed on the user interface. The processor is also configured to execute one or more scheduling instructions based on the received scheduling input, wherein the scheduling instructions are associated with the operation of one or more BMS devices.

Systems, methods, devices, and other techniques for planning and re-planning robot motions. The techniques can include obtaining a schedule that defines an execution order for a plurality of plans, each plan defining a sequence of tasks; providing instructions to the robotic system to execute plans from the plurality of plans according to the schedule; obtaining measurements for one or more parameters that represent a state of the robotic system or its environment that results from execution of at least one plan from the plurality of plans; determining, based on the measurements, that a particular plan from the plurality of plans, which has not completed execution, is to be revised; generating, using the measurements, a revised version of the particular plan; and adjusting the schedule so as to resolve a conflict between the revised version of the particular plan and at least one other plan in the plurality of plans.

A process control system for a facility that has a station arrangement including at least one at least partially automated working station and a vehicle arrangement including at least one at least partially automated transport vehicle for transporting material to be conveyed to, in and/or from the station arrangement. The process control system includes a process means for planning, implementing and/or observing, particularly monitoring processes of the station arrangement, a fleet means for planning, implementing and/or observing, particularly monitoring movements of the vehicle arrangement, and a working means arrangement with at least one working means for controlling and/or monitoring at least one working station of the station arrangement. The process and fleet means and/or the process means and the working means arrangement and/or the fleet means and the working means arrangement are configured to communicate with each other.

Example implementations described herein involve systems and methods for operation of a robot configured to work on a first process and a second process, which can involve receiving sensor data indicative of a status of one or more of the first process and the second process; for the status indicative of the first process waiting on the robot, controlling the robot to work on the first process; and for the status indicative of the first process not waiting on the robot, controlling the robot to conduct one or more of work on the second process or return to standby.