Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling

Author:

Kumar Raman1ORCID,Chohan Jasgurpreet Singh1ORCID,Singh Sandeep2ORCID,Sharma Shubham3ORCID,Singh Yadvinder3,Rajkumar S.4ORCID

Affiliation:

1. Department of Mechanical Engineering, Chandigarh University, Gharuan 140413, India

2. Department of Civil Engineering, Chandigarh University, Gharuan 140413, India

3. Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Jalandhar-Kapurthala Highway, VPO Ibban 144603, India

4. Department of Mechanical Engineering, Faculty of Manufacturing, Institute of Technology, Hawassa University, Awasa, Ethiopia

Abstract

Additive manufacturing has gained popularity among material scientists, researchers, industries, and end users due to the flexible, low cost, and simple manufacturing process. Among number of techniques, fused deposition modeling (FDM) is the most recognized technology due to easy operation, lower environmental degradation, and portable apparatus. Despite numerous advantages, the limitations of this technique are poor surface finish, dimensional accuracy, and mechanical strength, which must be improved. The present study focuses on the implementation of the genetic algorithm and Taguchi techniques to achieve minimum dimensional variability of FDM parts especially for polymeric biocomposites. The output has been measured using standard testing techniques followed by Taguchi and genetic algorithm analyses. Four response variables were measured and were converted into single variable with combination of different weightages of each response. Maximum weightage was given to width of FDM polymeric biocomposite parts which may play critical role in biomedical and aerospace applications. The advanced optimization and production techniques have yielded promising results which have been validated by advanced algorithms. It was found that layer thickness and orientation angle were significant parameters which influenced the dimensional accuracy whereas best fitness value was 0.377.

Publisher

Hindawi Limited

Subject

Biomedical Engineering,Biomaterials

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