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Research Article

Abrasive Jet Machining of Incense Stick Ash Filled Luffa-Human Hair Based Sustainable Bio-composite Using Taguchi Based GRA

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Pages 15022-15034 | Published online: 11 May 2022
 

ABSTRACT

In this research, a new class of partially biodegradable epoxy-based sustainable bio-composite is developed in house by using blend of luffa cylindrica (LC) and short human hair (SHH) as fiber and diverse weight proportions (0, 5, 10,15 and 20 wt.%) of incense stick ash (ISA) as filler through the conventional hand lay-up method. The presently developed hybrid natural fiber composites are characterized for their density and porosity and subsequently, investigated for their machinability through abrasive jet machining (AJM) process. Two grits of silicone carbide (SiC, 300 µm and 600 µm) and combination of aluminum oxide (Al2O3) and glass powder (90 µm) are used as the abrasives. The material removal rate (MRR) and surface roughness (Ra) of the machined surface are acquired according to Taguchi design of experiment. The significance of the control factors (type of composite, gas pressure, standoff distance and type of abrasive) is identified through ANOVA and ideal factor setting for optimum individual responses are established. Moreover, simultaneous optimization of multi performance characteristics is also attempted through Grey Relational Analysis (GRA) method. The outcomes from the confirmation runs showed an improvement in the predicted optimal machining parameters for individual as well as the multiple performance characteristic in AJM of the newly developed ISA filled LC-SHH fiber polymer composite.

摘要

本研究以丝瓜 (LC)和短发 (SHH) 的混合物为纤维, 以不同重量比例(0、5、10、15和20 wt.%)的香煤灰(ISA) 为填料, 通过传统的手糊法, 在室内开发了一种新型部分可生物降解的环氧基可持续生物复合材料. 目前开发的混杂天然纤维复合材料以其密度和孔隙率为特征, 随后通过磨料喷射加工(AJM)工艺对其可加工性进行了研究. 使用两种粒度的碳化硅(SiC, 300 µm和600 µm)以及氧化铝(Al2O3)和玻璃粉(90 µm) 的混合物作为磨料. 根据田口实验设计, 获得了加工表面的材料去除率(MRR) 和表面粗糙度(Ra). 通过ANOVA确定了控制因素(复合材料类型、气压、隔离距离和磨料类型) 的重要性, 并建立了最佳个体响应的理想因素设置. 此外, 还尝试通过灰色关联分析(GRA) 方法同时优化多性能特征. 确认运行的结果表明, 新开发的ISA填充LC-SHH纤维聚合物复合材料在AJM中的单个和多个性能特性的预测最佳加工参数都有所改善.

Acknowledgments

This work is supported by Science and Technology Department, Govt. of Odisha, India under Biju Patnaik Research Fellowship via. Reference no. ST-BT-MISC-0007-2020/2626/ST, Dt. 22/06/2021 and TEQIP-III, VSSUT via reference number VSSUT/TEQIP/86/2020 dated 20/01/2020, respectively.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the TEQIP III, VSSUT, Odisha [VSSUT/TEQIP/86/2020 dated 20/01/2020]; Science and Technology Department, Govt. of Odisha, India [ST-BT-MISC-0007-2020/2626/ST, Dt. 22/06/2021].

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