The invention relates to production planning systems and methods. A production optimization system is provided which has the following: a production environment with at least one first machine, a second machine, a distribution unit configured to be connected to the first machine and the second machine via a communication network and to ascertain the machine state thereof, and an optimization unit configured to generate a production plan where at least one task for producing a product is separated into machine-specific sub-tasks for the first machine or the second machine, said sub-tasks being provided with a sequence for the first machine or the second machine. The distribution unit ascertains the next occurring sub-task for the first machine or the second machine from the optimization unit while taking into consideration the respective machine state, to remove the sub-task from the production plan, and to assign the sub-task to the respective machine.

A robotic controller is provided for generating sequences of movement primitives for sequential tasks of a robot having a manipulator. The controller includes at least one control processor, and a memory circuitry storing a dictionary including the movement primitives, a pretrained learning module, and a graph-search based planning module having instructions stored thereon. The controller to perform steps acquiring a planned task provided by an interface device operated by a user, wherein the planned task is represented by an initial state and a goal state with respect to an object, generating a planning graph by searching a feasible path of the object for the novel task using the graph-search based planning module and selecting movement primitives from the dictionary in the pretrained learning module, wherein the pretrained learning module has been trained based on demonstration tasks, parameterizing the feasible path represented by the movement primitives as dynamic movement primitives (DMPs) using the initial state and goal state, and implementing the parameterized feasible path as a trajectory according to the selected movement primitives using the manipulator of the robot by tracking and following the parameterized for the planned task.

A flowchart of a process plant is compiled by linking graphical process objects representing operator-controllable and observable facilities of the plant when planning a process plant, wherein the process in the process plant is simulated with reference to simulation models assigned to the graphical process objects during a simulation phase, where simulation models include energy consumption models that describe the electrical energy consumption of the respective facilities to be described as a function of measurable or known process variables in the plant and hence enable simulation and optimization of the automation with respect to electrical energy consumption and energy efficiency.

A method of creating, by a computer, a task plan that prescribes an execution time of a task on which a completion time limit is set, the method includes allocating the execution time of at least one first task in a first period, calculating a first total time length for execution of the at least one first task allocated in the first period, identifying at least one second task that is not allocated in the first period and has the completion time limit set in the first period, calculating a second total time length for execution of the at least one second task, and displaying the first total time length and the second total time length on a display device.

Various embodiments are related to processor subsystems of material handling systems performing methods of creating one or more case placement patterns for placement of cases on a pallet by a palletizer. A human-machine interface (HMI) is executed by the processor subsystem that provides a control affordance to a user, selection, or to provide numerical inputs, for creating or selecting pre-created patterns. The HMI is adapted to provide preview of patterns in real-time, while the patterns are created. In this regard, the preview of patterns corresponds to currently positioned representations of cases on a pallet. The HMI is also adapted to render dynamic changes on the previewed pattern as the cases are positioned on the pallet, in real world, by the palletizer.

A vehicle scheduling apparatus acquires a task list information that indicates tasks assigned to a target person to whom a target vehicle is assigned. The vehicle scheduling apparatus determines an execution order of the tasks of the target vehicle using a cost matrix that indicates a minimum cost for each pair of sites, selects a path to travel for each task, generates schedule information, and detects a conflict between the target vehicle and a temporary obstacle. When the conflict is detected, the vehicle scheduling apparatus updates the cost matrix so as to update the minimum cost of the pair of sites, and repeatedly generating the schedule information until no detection is detected.

A cutting apparatus including a cutting mechanism configured to cut a workpiece, the cutting apparatus includes a controller being configured to control the cutting apparatus to: generate image data by reading a pattern from a surface of the workpiece; generate cut data used for causing the cutting mechanism to cut the pattern, on the basis of the image data; store the cut data; judge whether or not a volume of the cut data exceeds a predetermined threshold value; divide the cut data into sections each having a volume equal to or smaller than the threshold value when determined that the volume of the cut data exceeds the threshold value; and cause the storage unit to store therein a plurality of divided sections of cut data, which is a result of the cut data being divided.

A multi-robot collaboration method in a flexible hardware production workshop is provided, by which allocation of workpiece machining tasks and transfer of workpieces in different workstations can be achieved and meanwhile relatively high calculation cost is avoided. According to the method, a distributed collaboration method is fully used, and in allusion to the current technical condition, the allocation of the workpiece machining tasks and the transfer of the workpieces in different workstations can be achieved and meanwhile the relatively high calculation cost is avoided. A multi-AGV path conflict eliminating method is used for avoiding possible collision of AGVs during movement. A centralized intervention and adjustment method is used for discovering and predicting system conflicts and failure problems and making timely dispatching and adjustment so as to improve the automation level and the flexibility level of a hardware workshop.

A machine management method for performing planned activities on a machine is provided. Workpieces are manufactured by the machine according to a predetermined schedule during a respective planned activity of the machine. Manufactured workpieces are sorted from a removal area of the machine into a deposition area during a further respective planned activity of the machine according to the predetermined schedule. The method includes determining a manufacturing time for the workpieces by a machine management system based on manufacturing process data of the machine, determining a removal time for sorting the workpieces by the machine management system based on removal process data, changing the predetermined schedule to obtain a changed schedule for the planned activities by the machine management system based on a comparison of the manufacturing time with the removal time, and transferring the changed schedule to a controller of the machine.

Disclosed herein, in various embodiments, are systems and methods for creating, implementing, communicating, and/or analyzing control logic governing operation of a system under control, where the control logic is defined in attributed data, which specifies control operators along with their input and output variables for the various control nodes. In example embodiments, attributed data for an execution instance of control logic is interpreted to generate therefrom a symbolic representation of the control logic and associate, in the symbolic representation, output variable values with the control operators.