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.

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.

To optimize NC program cores included in a generated machining program and expedite operation of a machine tool. An optimization device includes a block analysis unit, a code processing unit, and a program generation unit. The block analysis unit analyzes a preparatory function code and/or an auxiliary function code for each of a plurality of blocks included in a first program. The code processing unit performs a process on the preparatory function code and/or the auxiliary function code in a plurality of successive blocks based on a result of the analysis by the block analysis unit and optimizes the first program. The program generation unit generates the first program optimized by the code processing unit as a second program.

A control system configured to serve one or more energy loads in a building comprises equipment configured to consume, produce, or store one or more resources including electricity, water, natural gas, steam, hot thermal energy, cold thermal energy, or electrical energy. The control system includes an asset allocator configured to receive an input model that describes a physical layout of the equipment and create a net list that defines connections between the equipment using the input model. The asset allocator is configured to discover one or more systems of interconnected equipment and one or more groups of equipment using the net list, formulate an optimization problem using the systems and groups of equipment, and operate the equipment according to the optimization problem.

An automated computer-implemented method for generating commands for controlling a computer numerically controlled machine to fabricate an object from a workpiece, the method including the steps of selecting a maximum permitted engagement angle between a rotating cutting tool and the workpiece, selecting a minimum permitted engagement angle between the rotating cutting tool and the workpiece, and configuring a tool path for the tool relative to the workpiece in which the engagement angle gradually varies between the maximum permitted engagement angle and the minimum permitted engagement angle.

A central plant control system configured to serve one or more energy loads in a building comprises equipment configured to consume, produce, or store one or more resources including electricity, water, natural gas, steam, hot thermal energy, cold thermal energy, or electrical energy. The central plant control system further comprises an asset allocator configured to receive an input model that describes a physical layout of the equipment of the central plant and create a net list that defines connections between the equipment of the central plant using the input model. The asset allocator is further configured to discover one or more systems of interconnected equipment and one or more groups of equipment using the net list, formulate an optimization problem for the central plant using the systems and groups of equipment, and operate the equipment of the central plant according to the optimization problem.

An exemplary method includes solving on a computing system an optimal power flow formulation for a plurality of generators in a power system. The solving includes computing using multi-threaded parallelism a plurality of constraints for the formulation, computing using multi-threaded parallelism a plurality of Jacobian functions of the constraints, and computing using multi-threaded parallelism a Hessian of Lagrangian functions. The method further includes outputting results of the solving, wherein the results comprise values of generation levels for the plurality of generators. Apparatus and program products are also disclosed.

An automated computer-implemented method for generating commands for controlling a computer numerically controlled milling machine to fabricate a machined object from a workpiece, the machined object being configured to facilitate subsequent finishing into a finished object, the method including defining a surface of the finished object, defining an offset surface defining an inner limiting surface of the machined object, defining a scallop surface defining an outer limiting surface of the machined object and calculating a tool path for the milling machine which produces multiple step-up cuts in the workpiece resulting in the machined object, wherein surfaces of the machined object all lie between the inner limiting surface and the outer limiting surface and the number of step-up cuts in the workpiece and the areas cut in each of the step-up cuts are selected to generally minimize the amount of workpiece material that is removed from the workpiece.

The present disclosure discloses a system and a method for predicting energy consumption in a numerically controlled lathe turning process based on a decision tree and belongs to the technical field of lathe control systems. According to the present disclosure, the energy consumption in the turning process of the numerically controlled lathe turning process based on mass historical data generated in the turning process, and the limit of specific workshop environmental factors such as lathe types and workpiece machining methods on a traditional energy consumption prediction algorithm is broken through; and the influence of various factors on turning energy consumption of a numerically controlled lathe is fully considered, a quantitative relationship between turning energy consumption and turning parameters is obtained by using a decision tree algorithm in a data mining technology and then combined with a self-correction module to correct a preliminary prediction result, and energy consumption in the numerically controlled lathe turning process is pre-calculated and used to guide an actual machining process. In addition, a model and a historical turning parameter database can be continuously updated according to actual conditions, so that the prediction precision of the prediction model is continuously improved, and an operator can select more reasonable turning parameters, thus finally helping enterprises to improve the machining efficiency.

An automated computer-implemented method for generating commands for controlling a computer numerically controlled milling machine to fabricate a machined object from a workpiece, the machined object being configured to facilitate subsequent finishing into a finished object, the method including defining a surface of the finished object, defining an offset surface defining an inner limiting surface of the machined object, defining a scallop surface defining an outer limiting surface of the machined object and calculating a tool path for the milling machine which produces multiple step-up cuts in the workpiece resulting in the machined object, wherein surfaces of the machined object all lie between the inner limiting surface and the outer limiting surface and the number of step-up cuts in the workpiece and the areas cut in each of the step-up cuts are selected to generally minimize the amount of workpiece material that is removed from the workpiece.