Systems, devices, and methods including selecting one or more sequences of machining types for a feature of one or more features, where the selection of the one or more sequences of machining types is based on the feature and a database of prior selections of machining types; selecting one or more tools for the selected one or more sequences of machining types, where the selection of the one or more tools is based on the feature, the selected one or more sequences of machining types, and a database of prior selections of one or more tools; and selecting one or more machining parameters for the selected one or more tools, where the selected machining parameters are based on the feature, the selected one or more sequences of machining types, the selected one or more tools, and a database of prior selections of one or more machining parameters.

A machining condition searching method includes: generating a machining condition to be set in a machining device; collecting a machining state; collecting the machining result performed under the machining condition; calculating an evaluation value of the machining on the basis of the machining result; constructing an evaluation value prediction model predicting, on the basis of the machining condition, the machining state, and the evaluation value, an evaluation value corresponding to the machining condition that has not been tried; and constructing the evaluation value prediction model on the basis of a change degree in the relationship between the machining condition and the evaluation value, and performs weighting based on the machining state on the evaluation value prediction model. The machining condition to be tried next is generated using a predictive value of the evaluation value. Each of the above processes is repeatedly performed until it is determined to end a search.

A storage medium storing a work plan specifying program that causes a computer to execute a process that includes specifying a certain order under conditions that, in a work line that generates a plurality of objects in the certain order, a certain amount of a material is partially cut from a raw material for each of the plurality of objects, the cut material is processed, the raw material is switched to a next raw material when the raw material lacks, and a changeover is performed to change the settings of the cutting device and the proceeding; and optimizing an objective function that reflects the changeover and an excess amount of each raw material that are determined according to an input order of the plurality of objects to the work line.

The present disclosure describes systems and methods for quantifying operating strategy energy usage. One embodiment describes an industrial control system that includes a tangible, non-transitory, computer readable medium storing a plurality of instructions executable by a processor of the industrial control system. The instructions include instructions to determine a plurality of operating strategies associated with an industrial automation component that is communicatively coupled to the industrial control system, in which each of the plurality of operating strategies includes a set of operational parameters associated with the industrial automation component, determine an expected energy usage cost associated with the industrial automation component for each of the plurality of operating strategies, determine an expected value added associated with the industrial automation component for each of the plurality of operating strategies, and select one of the plurality of operating strategies for operating the industrial automation component based at least in part on the expected energy usage cost and the expected value added associated with each of the plurality of operating strategies.

The invention relates to a system for generating sets of control data for networked robots, comprising a plurality of robots (R.sub.i), wherein i=1, 2, 3, . . . , n, and n≧2, an optimizer (OE) and a database (DB), which are networked via a data network, wherein each robot (R.sub.i) comprises at least: a control unit (SE.sub.i) for controlling and/or regulating the robot (R.sub.i); a storage unit (SPE.sub.i) for controlling sets of control data SD.sub.i(A.sub.k), which in each case enable the control of the robot (R.sub.i) in accordance with a predetermined task (A.sub.k), wherein k=1, 2, 3, . . . , m; a unit (EE.sub.i) for specifying a new task A.sub.m+1 for the robot (R.sub.i), wherein A.sub.m+1≠A.sub.k; a unit (EH.sub.i) for determining a set of control data SD,(A.sub.m+1) for execution of the task (A.sub.m+1) by the robot (R.sub.i), an evaluation unit (BE.sub.i), which evaluates the set of control data SD.sub.i(A.sub.m+1) determined by the unit (EH.sub.i), with regard to at least one parameter (P1) with the characteristic number K.sub.P1(SD.sub.i(A.sub.m+1)), and a communication unit (KE.sub.i) for communication with the optimizer (OE) and/or the database (DB) and/or other robots (R.sub.j≠i), the optimizer (OE), which is designed and configured in order to determine, upon request by a robot (R.sub.i), at least one optimized set of control data SD.sub.i,P2(A.sub.m+1) with regard to at least one predetermined parameter (P2), wherein the request by the robot (R.sub.i) occurs when the characteristic number K.sub.P1(SD.sub.i(A.sub.m+1) does not meet a predetermined condition, and the data base (DB) stores the set of control data SD.sub.i,P2(A.sub.m+1) optimized by the optimizer (OE) and provides it to the robot (R.sub.i) for execution of the task (A.sub.m+1).

To optimize an automatically optimized machining time for machining a workpiece in a machine tool, an original parts program is loaded into a machine tool controller. The machining of the workpiece using the original parts program is simulated, where a motion path generated by the original parts program in the machine tool is determined. The motion path is classified into at least one area of potential optimization in which there is no workpiece contact. The at least one area of potential optimization is assigned a tolerance space. An optimized motion path is determined within the tolerance space. The machining of the workpiece using the modified parts program is simulated. The optimized motion path is displayed and marked. Once a user has approved the modification in the parts program, machining of the workpiece takes place using the modified parts program.

The present disclosure relates to a method of calculating process parameters. which are optimized for processing a workpiece with specific material properties by means of a laser machine, comprising the method steps of: determining material properties for which the process parameters should be optimized; determining preconfigured initial process parameters; executing a re-optimization algorithm until a target objective function is minimized or maximized for calculating optimized material-specific process parameters by accessing a storage with a statistical model, wherein the statistical model is based on Bayesian optimization using Gaussian Processes as priors.

A machining-process generation device includes: a process-instance storage section to store therein a process instance that is an instance of a machining process indicating machining details of each machining-operation unit; a process generation section to generate a machining process on a basis of the process instance and a generation condition for the machining process, and to generate background information indicating a background to generation of the machining process, the background information including information of the process instance used to generate the machining process; and a display section capable of displaying the background information on a display device.

A machining condition search device according to the disclosure includes a machining condition generation unit, a practical machining command unit, a machining evaluation unit, a prediction unit, an optimum machining condition calculation unit. The machining condition generation unit generates a machining condition defined by one or more control parameters settable on a machining apparatus. The practical machining command unit causes the machining apparatus to perform machining based on a generated machining condition. The machining evaluation unit generates an evaluation value of performed machining, on the basis of information indicating a machining result of the performed machining. The prediction unit predicts an evaluation value corresponding to a machining condition under which machining is not performed, on the basis of the evaluation value and the machining condition corresponding to the evaluation value. The optimum machining condition calculation unit obtains an optimum machining condition on the basis of a prediction value predicted by the prediction unit and an evaluation value generated by the machining evaluation unit. The optimum machining condition is a machining condition under which an evaluation value is equal to or greater than a threshold and a tolerance is maximum.

The present invention relates to method for modifying process parameters based on optimum operation performance criteria for a metal working process, said method comprising the steps of inputting standard process parameters for at least one product to be machined and generating operational data based on the standard process parameters. Operational data is compared with optimized operation performance criteria and is presented to a decision-making entity. This entity may be allowed to modify the process parameters so as to improve operation of the metal working process.