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<p>The influence of abrasive waterjet machining parameters viz., water jet pressure (WJP), stand-off distance (SoD), nozzle diameter (ND), and traverse speed (TS) and garnet particle (GP) size towards the kerf angle (KA), average surface roughness (SR), and material removal rate (MRR), are investigated during machining a novel polymer composite made of Nylon-6 matrix, reinforced with seashell biofiller (15 wt.%). The novel polymer composite is fabricated using a twin-screw extruder and injection moulding. Experiments are designed with an L<sub>18</sub> mixed-level orthogonal array of Taguchi’s technique, and the outputs are simultaneously optimized using desirability analysis. Observation shows that as the GP size increases, the KA and SR tend to lower with higher MRR. The least SoD shows better results, whereas higher WJP and moderate TS produces higher MRR and lower SR. The ideal conditions of GP of 75&#xa0;µm, SoD of 1.03&#xa0;mm, WJP of 225&#xa0;MPa, TS of 40&#xa0;mm/min, and ND of 2.5&#xa0;mm, which predicts a SR of 1.705&#xa0;µm, KA of 1.449°, and MRR of 77.106&#xa0;g/min with a unified value of desirability is 0.883. The influence of GP size and WJP on the outputs is higher. An experiment confirms a maximum deviation of 12.61% between the predicted and experimental SR, whereas, for KA and MRR, it is about 4.76% and 1.28%. Prediction of outputs using machine learning approaches viz., support vector regression (SVR) and random forest regression (RFR) shows that higher prediction accuracy is achieved with RFR than SVR and regression model.</p> Graphical Abstract <p></p>

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Abrasive waterjet machining characteristics of nylon 6 polymer matrix reinforced with seashell biofillers: experimental analysis, optimization, and prediction

  • 期刊论文

  • 发表日期：

    2025年7月2日

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  • P. Vasanthkumar,
  • G. Perumal,
  • B. Deepanraj,
  • N. Senthilkumar

摘要

The influence of abrasive waterjet machining parameters viz., water jet pressure (WJP), stand-off distance (SoD), nozzle diameter (ND), and traverse speed (TS) and garnet particle (GP) size towards the kerf angle (KA), average surface roughness (SR), and material removal rate (MRR), are investigated during machining a novel polymer composite made of Nylon-6 matrix, reinforced with seashell biofiller (15 wt.%). The novel polymer composite is fabricated using a twin-screw extruder and injection moulding. Experiments are designed with an L18 mixed-level orthogonal array of Taguchi’s technique, and the outputs are simultaneously optimized using desirability analysis. Observation shows that as the GP size increases, the KA and SR tend to lower with higher MRR. The least SoD shows better results, whereas higher WJP and moderate TS produces higher MRR and lower SR. The ideal conditions of GP of 75 µm, SoD of 1.03 mm, WJP of 225 MPa, TS of 40 mm/min, and ND of 2.5 mm, which predicts a SR of 1.705 µm, KA of 1.449°, and MRR of 77.106 g/min with a unified value of desirability is 0.883. The influence of GP size and WJP on the outputs is higher. An experiment confirms a maximum deviation of 12.61% between the predicted and experimental SR, whereas, for KA and MRR, it is about 4.76% and 1.28%. Prediction of outputs using machine learning approaches viz., support vector regression (SVR) and random forest regression (RFR) shows that higher prediction accuracy is achieved with RFR than SVR and regression model.

Graphical Abstract