Experimental investigations on high precision abrasive waterjet cutting of natural fibre reinforced nano clay filled green composites

Rajamani, D.; Esakki, Balasubramanian; Babu, G. Dilli; Ananthakumar, K.

doi:10.1177/1528083720942962

Cited by 16 publications

(8 citation statements)

References 55 publications

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“…A creative experimental approach can significantly reduce the number of experimental trials while maintaining the precision of any manufacturing process. As a result, the current work employs a box-behnken design (BBD) based on response surface methodology (RSM), a statistical and cost-effective design of experiment approach, to design and conduct the PAC experiments [ 45 ]. Thirty experiments were designed and performed with six replicates in a block with four-factors and three levels.…”

Section: Proposed Methodologymentioning

confidence: 99%

A Hybrid Approach of ANFIS—Artificial Bee Colony Algorithm for Intelligent Modeling and Optimization of Plasma Arc Cutting on Monel™ 400 Alloy

et al. 2021

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This paper focusses on a hybrid approach based on genetic algorithm (GA) and an adaptive neuro fuzzy inference system (ANFIS) for modeling the correlation between plasma arc cutting (PAC) parameters and the response characteristics of machined Monel 400 alloy sheets. PAC experiments are performed based on box-behnken design methodology by considering cutting speed, gas pressure, arc current, and stand-off distance as input parameters, and surface roughness (Ra), kerf width (kw), and micro hardness (mh) as response characteristics. GA is efficaciously utilized as the training algorithm to optimize the ANFIS parameters. The training, testing errors, and statistical validation parameter results indicated that the ANFIS learned by GA outperforms in the forecasting of PAC responses compared with the results of multiple linear regression models. Besides that, to obtain the optimal combination PAC parameters, multi-response optimization was performed using a trained ANFIS network coupled with an artificial bee colony algorithm (ABC). The superlative responses, such as Ra of 1.5387 µm, kw of 1.2034 mm, and mh of 176.08, are used to forecast the optimum cutting conditions, such as a cutting speed of 2330.39 mm/min, gas pressure of 3.84 bar, arc current of 45 A, and stand-off distance of 2.01 mm, respectively. Furthermore, the ABC predicted results are validated by conducting confirmatory experiments, and it was found that the error between the predicted and the actual results are lower than 6.38%, indicating the adoptability of the proposed ABC in optimizing real-world complex machining processes.

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Section: Proposed Methodologymentioning

confidence: 99%

A Hybrid Approach of ANFIS—Artificial Bee Colony Algorithm for Intelligent Modeling and Optimization of Plasma Arc Cutting on Monel™ 400 Alloy

et al. 2021

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“…The nano-clay added to polyester resins enhanced mechanical properties and reduced shrinkage. [77][78][79] The addition of nano-clay, Nanomer I30 E, improved the tensile stiffness of epoxy matrix with drop in strain at failure. [80] The tensile strength, modulus along with flexural strength of polyester resin improved with addition of graded nano-clay.…”

Section: Polymersmentioning

confidence: 99%

A comprehensive review on natural fiber/nano‐clay reinforced hybrid polymeric composites: Materials and technologies

Rajeshkumar

Seshadri

Swaminathan³

et al. 2021

Polymer Composites

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The utilization of sustainable natural fibers as green filler/reinforcement material for producing polymeric composites is substantially improved due to increase in the perception of ecological safety and usage of biodegradable and renewable materials toward a green environment. These natural fibers are obtained from various sources and are reinforced in the polymer matrices to produce polymer matrix composites. However, the overall properties of these composites are low when compared to that of the synthetic fiber-based composites due to poor interfacial bonding between the hydrophilic natural fiber and hydrophobic polymers. This deficiency can be addressed by incorporating

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“…165 The impact on the composite by unconventional machining process on some of the composite is shown in Table 6. [166][167][168][169][170][171][172] Issue generated during the machining of NFRC…”

Section: Laser Beam Machiningmentioning

confidence: 99%

Machining parametric study on the natural fiber reinforced composites: A review

Mahakur

Bhowmik

Patowari

2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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Nowadays, the utilization of natural fiber reinforced composite has increased frequently. These natural fibers have significant features like low cost, renewable, and, more importantly, biodegradable in nature, making them to be utilized for various industrial sectors. However, the massive demand for natural fiber reinforced composites (NFRC), forces them to be machined and operated, which is required for countless areas in multiple industries like automotive, marine, aerospace and constructions. But before obtaining the final shape of any specimen, this specimen should come across numerous machining processes to get the desired shape and structure. Therefore, the present review paper focused on the various aspects during conventional and unconventional machining of the NFRC. It covers the work by exploring the influence of all input variables on the outcome produced after machining the NFRC. Various methodologies and tools are also discussed in this article for reducing the machining defects. The machining of the NFRC is found as a challenging task due to insufficient interlocking between the matrix and fibers, and minimum knowledge in machining characteristics and appropriate input parameters. Thus, this review is trying to assist the readers to grasp a basic understanding and information during the machining of the NFRC in every aspect.

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Experimental investigations on high precision abrasive waterjet cutting of natural fibre reinforced nano clay filled green composites

Cited by 16 publications

References 55 publications

A Hybrid Approach of ANFIS—Artificial Bee Colony Algorithm for Intelligent Modeling and Optimization of Plasma Arc Cutting on Monel™ 400 Alloy

A Hybrid Approach of ANFIS—Artificial Bee Colony Algorithm for Intelligent Modeling and Optimization of Plasma Arc Cutting on Monel™ 400 Alloy

A comprehensive review on natural fiber/nano‐clay reinforced hybrid polymeric composites: Materials and technologies

Machining parametric study on the natural fiber reinforced composites: A review

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