Application of Fuzzy Integrated JAYA Algorithm for the Optimization of Surface Roughness of DMLS Made Specimen: Comparison with GA

  • Hiren GajeraEmail author
  • Veera Darji
  • Komal Dave
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 949)


In today’s competitive era, the quality of the die or mold plays a significant role in tooling industries. The surface roughness of the die or mold drastically affects the final product and requires many post-processing processes which consume considerable time and money. These problems need to be minimized by controlling process parameters of direct metal laser sintering (DMLS). In order to establish the relationship between the surface roughness of DMLS made parts and process parameters, i.e., laser power, hatch spacing, scan speed, and layer thickness, Box–Behnken design (BBD) of response surface methodology (RSM) was used. This study demonstrates the application of optimization by a combination of nonlinear regression modeling in terms of a fuzzy inference system with the JAYA algorithm to select an optimal parameter set. The result obtained from the JAYA has been compared with the genetic algorithm (GA). A very good agreement has been found between JAYA and GA.


DMLS RSM JAYA GA CL50WS Surface roughness 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.C U Shah UniversitySurendranagarIndia
  2. 2.L D College of EngineeringAhmedabadIndia

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