jerzy dobrodziej, jacek wojutyƒski, jerzy ratajski, tomasz suszko, jerzy michalski

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COMPUTER-AIDED PROJECTING OF GAS NITRRIDING PROCESSES WITH UTILIZATION OF SIMULATION AND METHODS OF ARTIFICIAL INTELLIGENCE. Jerzy DOBRODZIEJ, Jacek WOJUTYŃSKI, Jerzy RATAJSKI, Tomasz SUSZKO, Jerzy MICHALSKI. IN STITUTE FOR SUSTAINABLE TECHNOLOGIES – NATIONAL RESEARCH INSTITUTE POLAND. - PowerPoint PPT Presentation

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  • Jerzy DOBRODZIEJ, Jacek WOJUTYSKI, Jerzy RATAJSKI, Tomasz SUSZKO,Jerzy MICHALSKI INSTITUTE FOR SUSTAINABLE TECHNOLOGIES NATIONAL RESEARCH INSTITUTEPOLANDCOMPUTER-AIDED PROJECTING OF GAS NITRRIDING PROCESSES WITH UTILIZATION OF SIMULATION AND METHODS OF ARTIFICIAL INTELLIGENCE

  • PRESENTATION PLAN

  • Computer-aided processes of layers creation How it to do ?

    Classical approach empirical methods of trial and error PROBLEMS TO SOLVE

  • METHODS OF SOLVINGArchival dataInput parametersOutput parametersDATABASE

  • MODULE OF DATABASES - INFORMATION STRUCTURE

    ProcessParameter nameValueParameter typeParameter nameValueParameter typeParameter nameValueParameter type...

    Devices

    MaterialsEffects of the process (economical, ecological, innovative, etc.)

    Stages of the processParameters for the whole processSubstrate (before the process)Materials with layers (after the process)Parameter nameValueParameter typeParameter nameValueParameter typeParameter nameValueParameter typeParameter nameValueParameter typeParameter nameValueParameter type

    Device 1

    Device m

    Stage 1

    Stage n...Archival processIn-situ process

  • MODULE OF DATABASES - APPLICATION

  • EXPERT SYSTEM - STRUCTURE OF EXPERT SYSTEMUser interaction moduleSelection of input and output parameters setFormulation of database queryCreation of the fuzzy logic functionKnowledge bases generationDatabase integration moduleSet of processesInference moduleFuzzification of input parametersvaluesRules congregationDefuzzificationOptimisation moduleKnowledge bases optimisationINFERENCE RESULTS:LAYER PARAMETERS VALUES (output parameters)12/16

  • EXPERT SYSTEM - APPLICATIONTASKPrediction of layers properties manufacturedin nitriding and PVD processes. Support for designing the nitriding processes technologies on the basis of substrate and process milieu parameters.System propertiesInference versatility Inferencing with diverse parameters.

    Flexibility and coherence of inferencing Inferencing on the basis of different domains parameters: continue (e.g. temperature in time function), discrete (e.g. value of layer resistance to corrosion), nominaly ordered (e.g. type of mechanical treatment used for substrate surface). Inference adaptation and self-learning Using data referring to new and completed processes as well as created layers in order to improve inference quality. IFHTSE 2007 Congress Adam Mazurkiewicz, 31.10.200713/16

  • EXPERT SYSTEM - VALIDATION IN THE FIELD OF NITRIDING PROCESSES Process milieu and substrateResults

    Process 1 Process 2 Process 3 Process duration [min] 57060480Mean nitride potential [atm] 4.753.256Temperature [C] 530570530Amount of N2 in the atmosphere [%] 602060Amount of NH3 in the atmosphere [%] 406040Substrate material 40 HMJ40 HMJ38 HMJFuzzification method triangletriangletriangle

    Parameter nameProcess 1 Process 2Process 3ObtainedPredictedObtainedPredictedObtainedPredictedEffective thickness g400 [m] 0.1850.17670.170.162100.20.1913Effective thickness g500 [m] 0.090.0860.070.066800.10.0957Effective thickness gr+50 [m] 0.3450.32950.240.228900.30.2870Grey area thickness [m] 54.775044.184804.54.3047Nitride layer thickness [m] 1010.450012.513.077510.510.0443Maximum hardness HV 551575.795538562.8556552575.9568Surface hardness HV1 659629.345692723.9704644671.9496Surface hardness HV10 642670.890630600.8940625652.125Surface hardness HV0.5 519495.645512535.6544532555.0888Surface hardness HV5 544519.520559533.1742562537.6092

  • MODULE DESIGN OF DYNACMICS CHARACTERISTIC OF NITIRIDING PROCESS

    Purpose Designing of atmospheres for gas nitriding process. Module properties Two- and tree-component atmospheres: Nitriding potential model on the basis of isoconcentrative characteristics or established by the designer. Model of dissociation level.

    Designing of process environment characteristics

  • MODULE DESIGN OF DYNACMICS CHARACTERISTIC OF NITIRIDING PROCESS Purpose Simulation of layer growth kinetics.Simulation of nitrogen concentration profiles on phases borders. System properties Short time of calculations. Additional software for mathematical calculations not required. Possibility of layer growth in time animation. Possibility of concentrations on phase border animation. Possibility of concentration profiles on phase border animation.

  • MODULE OF NEURAL NETWORK

    Purpose Prediction of micro hardness distribution in the function of:Process durationTemperature Nitridning potential Module properties Optimal structure of neuron network. Generalization option. Possibility of adapting for diverse materials substrates.

  • MODULE OF OPTIMISATION EVOLUTIONARY ALGORITHMS

    Purpose Temperature and nitriding potential prediction in order to obtain the projected micro hardness distribution System properties Determining optimal average values of temperature and potential in successive gas nitriding process. Possibility of adapting for diverse materials substrates.

  • CONCLUSIONSDesigned system enables:The system might be used for:

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