| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1688641 | Vacuum | 2013 | 7 Pages |
A method to the control of vacuum nitriding process that could be applicable for a variety of tool steels is presented. The quantitative diffractometric x-ray phase analysis has been applied to identify the nitrides growth and their stoichiometry as the function of steel composition, nitriding parameters and time. It has been found that the nitrogen content in the ɛ nitride depends not only on the nitriding parameters but it is also strongly influenced by alloying elements in steel. This statement has practically excluded using any steady state models to control and monitor the precise nitriding of alloy steels, especially in the case of vacuum nitriding of tool steels. The importance of the nucleation stage for repeatability of vacuum nitriding results has been shown, too. The effective method for active washing of charge is demonstrated and proposed to unify and shorten nucleation time. Finally, the neural network model is presented as a new approach to modelling and control of the non-steady state vacuum nitriding of various tool steels. This model is based on the “boost-diffusion” schedule of the process.
► New approach to the control of vacuum nitriding process. ► Examination of the effectiveness of formation of nitrided layers. ► Modelling and dissolving non-steady stage boost-diffusion vacuum nitriding.
