Adhesion prediction method, adhesion prediction program, and adhesion prediction device

1 . An adhesion prediction method of predicting an adhesion of metal particles in a workpiece to a die in a forging process using an aluminum-based material as the workpiece, the adhesion prediction method comprising:

an input step of receiving computer aided design (CAD) information from a CAD device and various conditions that are used for analysis from an input device;

a cumulative friction work amount calculation step of calculating a cumulative friction work amount generated between the workpiece and the die;

a metal diffusion analysis step of analyzing a diffusion state of the metal particles between the workpiece and the die;

an adhesion prediction determination step of predicting an occurrence of the adhesion of the metal particles to the die, considering the cumulative friction work amount calculated in the cumulative friction work amount calculation step, the diffusion state analyzed in the metal diffusion analysis step, and a film thickness of a lubricating film provided on a surface of the die that comes into contact with the workpiece, the metal particles being of the aluminum-based material; and

an output step of outputting an analysis model of the occurrence of the adhesion.

2 . The adhesion prediction method according to claim 1 , wherein the adhesion prediction determination step includes:

performing a computing process of computing a product of a first term obtained by dividing a function of the cumulative friction work amount by the film thickness of the lubricating film and a second term of a function of the diffusion state; and

determining a prediction of the occurrence of the adhesion of the metal particles to the die considering a result of the computing process.

3 . The adhesion prediction method according to claim 1 , wherein the cumulative friction work amount is calculated from a function obtained by integrating, over a forging time, a contact surface pressure, a friction coefficient, and a sliding velocity acting between the workpiece and the die for a minute time at each of element parts of the workpiece and the die.

4 . The adhesion prediction method according to claim 1 , wherein analysis of the diffusion state is performed by analyzing a diffusion amount of the metal particles using an Arrhenius equation in consideration of a combination of materials of the workpiece and the die and a processing temperature.

5 . The adhesion prediction method according to claim 1 ,

wherein the adhesion prediction determination step includes:

performing a computing process of computing a product of a first term obtained by dividing a function of the cumulative friction work amount by the film thickness of the lubricating film and a second term of a function of the diffusion state; and

determining a prediction of the occurrence of the adhesion of the metal particles to the die considering a result of the computing process,

wherein the cumulative friction work amount is calculated from a function obtained by integrating, over a forging time, a contact surface pressure, a friction coefficient, and a sliding velocity acting between the workpiece and the die for a minute time at each of element parts of the workpiece and the die, and

wherein analysis of the diffusion state is performed by analyzing a diffusion amount of the metal particles using an Arrhenius equation in consideration of a combination of materials of the workpiece and the die and a processing temperature.

6 . The adhesion prediction method according to claim 1 , wherein in the output step, an image information indicating the analysis model is generated, and the image information is output to an output device.

7 . The adhesion prediction method according to claim 6 , wherein the image information includes a group showing timings at which the adhesion is predicted to occur.

8 . The adhesion prediction method according to claim 6 , wherein the image information includes a mapping diagram of a processing shape of the workpiece.

9 . The adhesion prediction method according to claim 8 , wherein in the adhesion prediction determination step, values of an adhesion determination function are determined, and the mapping diagram indicates the values of the adhesion determination function in different colors by sections.

10 . The adhesion prediction method according to claim 8 , wherein in the adhesion prediction determination step, values of an adhesion determination function are determined, and the mapping diagram indicates the values of the adhesion determination function in different segments by a threshold value.

11 . A non-transitory computer-readable storage medium storing an adhesion prediction program for predicting an adhesion of metal particles in a workpiece to a die in a forging process using an aluminum-based material as the workpiece, the adhesion prediction program causing a computer to execute:

an input process of receiving computer-aided design (CAD) information from a CAD device and various conditions that are used for analysis from an input device;

a cumulative friction work amount calculation process of calculating a cumulative friction work amount generated between the workpiece and the die;

a metal diffusion analysis process of analyzing a diffusion state of the metal particles between the workpiece and the die;

an adhesion prediction determination process of predicting a state of an occurrence of the adhesion of the metal particles to the die, considering the cumulative friction work amount calculated in the cumulative friction work amount calculation process, the diffusion state analyzed in the metal diffusion analysis process, and a film thickness of a lubricating film provided on a surface of the die that comes into contact with the workpiece, the metal particles being of the aluminum-based material; and

outputting an analysis model of the occurrence of the adhesion.

12 . An adhesion prediction device for predicting an adhesion of metal particles in a workpiece to a die in a forging process using an aluminum-based material as the workpiece, the adhesion prediction device comprising:

an input unit that receives computer-aided design (CAD) information from a CAD device and various conditions that are used for analysis from an input device;

a cumulative friction work amount calculation unit that calculates a cumulative friction work amount generated between the workpiece and the die;

a metal diffusion analysis unit that analyzes a diffusion state of the metal particles between the workpiece and the die; and

an adhesion prediction determination unit that predicts an occurrence of the adhesion of the metal particles to the die, considering the cumulative friction work amount calculated by the cumulative friction work amount calculation unit, the diffusion state analyzed by the metal diffusion analysis unit, and a film thickness of a lubricating film provided on a surface of the die that comes into contact with the workpiece, the metal particles being of the aluminum-based material; and

outputting an analysis model of the occurrence of the adhesion.