Development of the nitrided layer

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Development of the nitrided layer mechanism of
the growth, mathematical modeling and simulation.

• Jerzy Ratajski, Adam Mazurkiewicz, Dariusz
  Lipinski, Jerzy Dobrodziej
• Koszalin University of Technology, Koszalin,
  Poland
• Institute of Sustainable Technology, Radom,
  Poland

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• Nitriding process is very efficient
• in long-run production,
• in the mass production,
• and also is very often used in so called duplex
  process

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Duplex processes
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• The nitrided layer should characterizes
• demanded hardness and thickness,
• The nitrided parts should maintain their sizes
  and shape stability.

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g
a-Fe(N)
e
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Equilibrium diagram Fe-N
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• Metods of artificial inteligence
• Neural network
• Fuzzy logic
• Evolutional algorithms

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Calculation by iteration methods
i 1, 2, 3 1 e 2 g 3 a
etc
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Structure of nitrided layer
Structure of nitrided layer
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Structure of nitrided layer Hardness distribution
Hp
g600
g500
g400
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Steel 4340 (AISI) KN 3,25 , T 5800C , t 10 h
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t 3 h
t 10 h
Steel 4340 KN 3,25 T 5800C
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Steel 4340
KN 10 T 5800C t 16 h
KN 10/0.5 T 5800C t 8/8 h
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Conclusion

• A research results presented, indicate that,
  besides temperature and nitrogen potential, also
  phase composition of iron (carbo)nitrides layer
  on steel has considerable influence on
  development of hardness profiles in diffusion
  layer.

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• Metods of artificial inteligence
• Neural network
• Fuzzy logic
• Evolutional algorithms

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Table Characteristics of experimental data used
for modeling.
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• The established neural model enables
  estimation of influence of the chemical
  composition of steel (grade of steel) and
  nitriding process parameters including number
  of stages, on hardness profile.

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Summary

• A research results presented show, that also
  phase composition of iron (carbo) nitrides layer
  on steel has considerable influence on
  development of hardness profile in diffusion
  layer.
• Elaborated neural network model constitute tool
  to the simulation of the profiles of hardness in
  the nitrided layer - predicted results showed
  relatively low scatter with experimental results.
  
• The model is open for constant upgrade and
  improvement and also can be applied in a control
  system and in visualization of the process course.

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• Thank you