Reduction of edge effect using response surface methodology and artificial neural network modeling of a spur gear treated by induction with flux concentrators

Khalifa, Mohamed; Barka, Noureddine; Brousseau, Jean; Bocher, Philippe

doi:10.1007/s00170-019-03817-9

Cited by 7 publications

(2 citation statements)

References 26 publications

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“…The multiobjective optimization problem with the appropriate economic, environmental, and social metrics was analyzed in [14] to assure the sustainability of the induction hardening process using empirical models. The reduction of edge effect using the RSM and artificial neural network modeling of a spur gear treated by induction with flux concentrators was shown in [15]. Artificial intelligence modeling of induction contour hardening of 300M steel bar and C45 steel spur-gear was performed in [16].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Optimizing Process Parameters in the Induction Hardening of Rack Bar by Response Surface Methodology and Desirability Function Approach under Industrial Conditions

Dziatkiewicz,

Kuska,

Popiel

2023

Materials

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Conditions of industrial production introduce additional complexities while attempting to solve optimization problems of material technology processes. The complexity of the physics of such processes and the uncertainties arising from the natural variability of material parameters and the occurrence of disturbances make modeling based on first principles and modern computational methods difficult and even impossible. In particular, this applies to designing material processes considering their quality criteria. This paper shows the optimization of the rack bar induction hardening operation using the response surface methodology approach and the desirability function. The industrial conditions impose additional constraints on time, cost and implementation of experimental plans, so constructing empirical models is more complicated than in laboratory conditions. The empirical models of nine system responses were identified and used to construct a desirability function using expert knowledge to describe the quality requirements of the hardening operation. An analysis of the hypersurface of the desirability function is presented, and the impossibility of using classical gradient algorithms during optimization is empirically established. An evolutionary strategy in the form of a floating-point encoded genetic algorithm was used, which exhibits a non-zero probability of obtaining a global extremum and is a gradient-free method. Confirmation experiments show the improvement of the process quality using introduced measures.

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Section: Introductionmentioning

confidence: 99%

Evolutionary Optimizing Process Parameters in the Induction Hardening of Rack Bar by Response Surface Methodology and Desirability Function Approach under Industrial Conditions

Dziatkiewicz,

Kuska,

Popiel

2023

Materials

View full text Add to dashboard Cite

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“…Another study was focused on the effects of induction machine parameters on the case-depths of 4340 spur gear with a 2D model [44], and explore how machine parameters and geometrical factors are effective on the hardness pro le of 4340 steel disc hardened by induction hardening [45]. Furthermore, surface methodology and arti cial neural network modeling were exploited to observe the effects of ux concentrators on changing of edge effect in spur gear treated by induction [46]. Barglik et al [47], are recently performed a numerical study on dual frequency hardening process of a AISI 300M gear.…”

Section: Introductionmentioning

confidence: 99%

A novel investigation into the edge effect reduction of 4340 steel disc through induction hardening process using magnetic flux concentrators

Parvinzadeh

Karganroudi

Omidi

et al. 2021

Int J Adv Manuf Technol

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Induction hardening serves as one of the best mass production processes used recently due to its ability to quickly generating high-intensity heat in a well-de ned location of the part. Numerous advantages of this method make it a reliable technique to produce a thin martensite layer on the part surface that has compressive residual stresses. In this regard, the presented study is devoted to investigating utilizing induction heating for surface hardening of AISI 4340 steel disc. The purpose is to evaluate the performance of magnetic ux concentrators and the effects of the induction process parameter on the case-depth and edge effect in the surface hardening of the disc. Once the proper range of parameters is de ned, Taguchi experimentation planning is used to frame comprehensive experimentation with the minimum possible trial. Then, the case-depth of discs is evaluated on their cross-sections (edge and middle plane) through hardness pro le measurement of samples using a micro-indentation hardness machine. The results are then statistically analyzed using Analysis of Variance (ANOVA) and Response Surface Methodology (RSM) to determine the best combination of parameters to achieve maximum casedepth yet minimum edge effect. The goodness-of-t regression models are then developed to predict the case-depth pro le as a function of machine parameters based on linear regression utilizing case-depth responses in the edge and middle plane of discs. Results imply that maximum case-depth with minimum edge effect can be produced by using the highest heating time along with the average amplitude of the power, axial gap, and radial gap. This study gives a good exploration of case-depths optimized by setting up process parameters when magnetic ux concentrator is utilized, thus, a guideline to reduce discs edge effect in induction surface hardening application is given.

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A novel investigation into edge effect reduction of 4340 steel spur gear during induction hardening process

Parvinzadeh

Karganroudi

Omidi

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Reduction of edge effect using response surface methodology and artificial neural network modeling of a spur gear treated by induction with flux concentrators

Cited by 7 publications

References 26 publications

Evolutionary Optimizing Process Parameters in the Induction Hardening of Rack Bar by Response Surface Methodology and Desirability Function Approach under Industrial Conditions

Evolutionary Optimizing Process Parameters in the Induction Hardening of Rack Bar by Response Surface Methodology and Desirability Function Approach under Industrial Conditions

A novel investigation into the edge effect reduction of 4340 steel disc through induction hardening process using magnetic flux concentrators

A novel investigation into edge effect reduction of 4340 steel spur gear during induction hardening process

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