Evidence map›Paper›PMID 42215627›Full record

ArticleScientific reports2026

Predictive analysis of tensile strength in FDM Fabricated PLA wood composite materials.

Mahendrasinh R Chauhan, Akanksha Mishra, Praveen Oggu, Jasgurpreet Singh, Ripendeep Singh, Koushik V Prasad, Dhirendra Nath Thatoi, Kamaljit Singh Boparai, Abhijit Bhowmik, Yalew Tamene

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Mahendrasinh R ChauhanDepartment of Mechanical Engineering, Gokul Global University, Siddhpur, Gujarat, India.
Akanksha MishraDepartment of Mechanical Engineering, Sharda School of Engineering & Sciences, Sharda University, Greater, Noida, India.
Praveen OgguVardhaman College of Engineering, Hyderabad, Telangana, India.
Jasgurpreet SinghMarwadi University Research Center, Department of Mechanical Engineering, Faculty of Engineering & Technology, Marwadi University, Rajkot, Gujarat, India.
Ripendeep SinghDepartment of Mechanical Engineering, Chandigarh University, Mohali, Punjab, India.
Koushik V PrasadDepartment of Mechanical Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Dhirendra Nath ThatoiDepartment of Mechanical Engineering, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, 751030, Odisha, India.
Kamaljit Singh BoparaiDepartment of Mechanical Engineering, GZSCCET, Maharaja Ranjit Singh Punjab Technical University, Bathinda, 151001, Punjab, India.
Abhijit BhowmikDepartment of Additive Manufacturing, Mechanical Engineering, SIMATS, Saveetha Institute of Medical and Technical Sciences, Thandalam, 602105, Chennai, India.
Yalew TameneFaculty of Mechanical Engineering, Jimma Institute of Technology, Jimma University, Jimma, 378, Ethiopia. yalew.tamene@ju.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A computational modeling strategy was established to predict the tensile strength of polylactic acid (PLA) reinforced with wood particles fabricated using fused deposition modeling (FDM). Three different predictive approaches-Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Response Surface Methodology (RSM)-were applied to estimate the mechanical response of the printed composites. The experimental program was arranged using a Taguchi L

Indexed as

Analysis of varianceFused deposition modelingPLA/wood compositesPredictive modelingTensile strength

Identifiers

PMID42215627
PMCPMC13470469

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