The purpose of the present invention is to provide an assistance device that can more easily find optimal machining conditions. This assistance device comprises: a program management unit that associates verification results, which are obtained by verifying machining conditions using a plurality of verification functions, with a machining program and stores the verification results in a verification result storage unit; a determination unit that determines whether the verification results meet a target time value for a workpiece; and an advice unit that, if any of the verification results do not meet the target time value for the workpiece, proposes an adjustment to the machining conditions on the basis of the machining condition-associated information that pertains to the machining conditions for the workpiece, the verification results, and the verification functions.

The purpose of the present invention is to provide an assistance device that can more easily find optimal machining conditions. This assistance device comprises: a program management unit that associates verification results, which are obtained by verifying machining conditions using a plurality of verification functions, with a machining program and stores the verification results in a verification result storage unit; a determination unit that determines whether the verification results meet a target time value for a workpiece; and an advice unit that, if any of the verification results do not meet the target time value for the workpiece, proposes an adjustment to the machining conditions on the basis of the machining condition-associated information that pertains to the machining conditions for the workpiece, the verification results, and the verification functions.

In a CAD data-based automatic operation device of a machining center equipped with a CNC device, the CNC device is provided in a storage unit with a learned model generated by learning beforehand machining conditions including a tool used and cutting conditions, a manufacturing process including a tool trajectory, and a machining program that caused the manufacturing process to be performed in correspondence with one another with respect to each feature subjected to various cutting operations. An automatic machining command generation unit provided in a control unit is provided with: a feature extraction function of extracting features from three-dimensional CAD design data of a machined product; an automatic manufacturing process setting function of automatically determining required machining conditions and automatically setting a manufacturing process including a tool trajectory, by applying each feature to the learned model; an all manufacturing process setting function of determining a procedure for manufacturing processes for all the features; and a machining command generation function of generating a machining command for causing a machine tool to perform all the manufacturing processes based on the learned model. The automatic manufacturing process setting function is further provided with a function of displaying a 3D model of the machined product generated based on the three-dimensional CAD design data in one or more possible different directions of mounting to a machining unit in a selectable and executable manner and the manufacturing processes are automatically set based on the determined mounting direction.

In a CAD data-based automatic operation device of a machining center equipped with a CNC device, the CNC device is provided in a storage unit with a learned model generated by learning beforehand machining conditions including a tool used and cutting conditions, a manufacturing process including a tool trajectory, and a machining program that caused the manufacturing process to be performed in correspondence with one another with respect to each feature subjected to various cutting operations. An automatic machining command generation unit provided in a control unit is provided with: a feature extraction function of extracting features from three-dimensional CAD design data of a machined product; an automatic manufacturing process setting function of automatically determining required machining conditions and automatically setting a manufacturing process including a tool trajectory, by applying each feature to the learned model; an all manufacturing process setting function of determining a procedure for manufacturing processes for all the features; and a machining command generation function of generating a machining command for causing a machine tool to perform all the manufacturing processes based on the learned model. The automatic manufacturing process setting function is further provided with a function of displaying a 3D model of the machined product generated based on the three-dimensional CAD design data in one or more possible different directions of mounting to a machining unit in a selectable and executable manner and the manufacturing processes are automatically set based on the determined mounting direction.

A dynamic optimization method for procurement specifications of BEF raw materials includes: obtaining finished product data; obtaining an initial feasible raw material size set; mapping the initial feasible raw material size set in length and width directions to obtain a complete feasible raw material size set; filtering an unreasonable raw material size out of the complete feasible raw material size set to obtain a final feasible raw material size set; and determining whether a scale of the final feasible raw material size set is larger than a threshold, if not, building and solving an integer programming model, and outputting results; and if yes, batchwise processing the final feasible raw material size set to obtain multiple subsets, and building an integer programming model for each subset, and solving the integer programming model, and outputting results. A dynamic optimization system of BEF is further provided.

A dynamic optimization method for procurement specifications of BEF raw materials includes: obtaining finished product data; obtaining an initial feasible raw material size set; mapping the initial feasible raw material size set in length and width directions to obtain a complete feasible raw material size set; filtering an unreasonable raw material size out of the complete feasible raw material size set to obtain a final feasible raw material size set; and determining whether a scale of the final feasible raw material size set is larger than a threshold, if not, building and solving an integer programming model, and outputting results; and if yes, batchwise processing the final feasible raw material size set to obtain multiple subsets, and building an integer programming model for each subset, and solving the integer programming model, and outputting results. A dynamic optimization system of BEF is further provided.

A method for accessing a computer-numerically-controlled machine can include receiving a command to be executed by the computer-numerically-controlled machine. A hardware state of a component in the computer-numerically-controlled machine can be determined by receiving, from the component, data indicative of the hardware state. An origin of the command including a user identification of a user who sent the command and/or a machine identification of a device that sent the command can be determined. Whether the computer-numerically-controlled machine is allowed to execute the command can be determined by applying a set of rules and based on the hardware state and/or the origin of the command. In response to determining that the computer-numerically-controlled machine is allowed to execute the command, the command can be executed at the computer-numerically-controlled machine.

A method for accessing a computer-numerically-controlled machine can include receiving a command to be executed by the computer-numerically-controlled machine. A hardware state of a component in the computer-numerically-controlled machine can be determined by receiving, from the component, data indicative of the hardware state. An origin of the command including a user identification of a user who sent the command and/or a machine identification of a device that sent the command can be determined. Whether the computer-numerically-controlled machine is allowed to execute the command can be determined by applying a set of rules and based on the hardware state and/or the origin of the command. In response to determining that the computer-numerically-controlled machine is allowed to execute the command, the command can be executed at the computer-numerically-controlled machine.

An integrated simulation system includes a first simulation device which executes a simulation of a first program, a second simulation device which executes a simulation of a second program, a start timing setting section which sets start timing for the correlated first program and second program so as to verify the presence or absence of malfunctions caused by a start order of the correlated first program and second program, and a program starting section which issues commands to the first simulation device and the second simulation device to start the correlated first program and second program at the set start timing by a single starting operation.

An integrated simulation system includes a first simulation device which executes a simulation of a first program, a second simulation device which executes a simulation of a second program, a start timing setting section which sets start timing for the correlated first program and second program so as to verify the presence or absence of malfunctions caused by a start order of the correlated first program and second program, and a program starting section which issues commands to the first simulation device and the second simulation device to start the correlated first program and second program at the set start timing by a single starting operation.