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<p>Technological improvements of the existing non-traditional machining processes along with ever-increasing demands for machining of many of the hard-to-cut advanced engineering materials have led to the development of abrasive water jet machining (AWJM) process, hybridizing the material removal mechanisms of both water jet and abrasive jet machining processes. Due to involvement of numerous input parameters and conflicting responses having significant interactions between them, optimization of an AWJM process is really a challenging task, especially when there exist varying opinions of the decision makers with respect to relative importance assigned to the considered responses. In this paper, based on the past experimental data, two AWJM processes are optimized using an almost unexplored multi-criteria decision making tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) under single-valued neutrosophic fuzzy environment considering subjectivity and ambiguity in the decision making process. In the first example, an optimal combination of water pressure = 275&#xa0;MPa, stand-off distance (SOD) = 4.5&#xa0;mm, abrasive flow volume = 0.24&#xa0;kg/min and feed rate = 80&#xa0;mm/min would result in maximum material removal rate (MRR) (600.06&#xa0;mm<sup>3</sup>/min) and minimum geometrical errors (circularity = 0.0170&#xa0;mm, cylindricity = 0.0263&#xa0;mm, axis perpendicularity = 0.0431&#xa0;mm, surface perpendicularity = 0.0270&#xa0;mm and parallelism = 0.1110&#xa0;mm). On the other hand, in the second example, maximum MRR (12.03&#xa0;mm<sup>3</sup>/min), and minimum surface roughness (4.71&#xa0;μm) and kerf width (0.69&#xa0;mm) can be attained at an optimal parametric intermix of SOD = 1&#xa0;mm, traverse speed = 146&#xa0;mm/s and abrasive flow rate = 200&#xa0;g/min. Both the derived solutions closely corroborate with the observations of the past researchers, validating applicability of MACONT method in optimizing the considered AWJM processes in uncertain decision making environment.</p>

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Optimization of abrasive water jet machining processes using mixed aggregation by comprehensive normalization technique (MACONT) under single-valued neutrosophic fuzzy environment

  • 期刊论文

  • 发表日期：

    2025年8月20日

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  • Srinjoy Chatterjee,
  • Shankar Chakraborty

摘要

Technological improvements of the existing non-traditional machining processes along with ever-increasing demands for machining of many of the hard-to-cut advanced engineering materials have led to the development of abrasive water jet machining (AWJM) process, hybridizing the material removal mechanisms of both water jet and abrasive jet machining processes. Due to involvement of numerous input parameters and conflicting responses having significant interactions between them, optimization of an AWJM process is really a challenging task, especially when there exist varying opinions of the decision makers with respect to relative importance assigned to the considered responses. In this paper, based on the past experimental data, two AWJM processes are optimized using an almost unexplored multi-criteria decision making tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) under single-valued neutrosophic fuzzy environment considering subjectivity and ambiguity in the decision making process. In the first example, an optimal combination of water pressure = 275 MPa, stand-off distance (SOD) = 4.5 mm, abrasive flow volume = 0.24 kg/min and feed rate = 80 mm/min would result in maximum material removal rate (MRR) (600.06 mm3/min) and minimum geometrical errors (circularity = 0.0170 mm, cylindricity = 0.0263 mm, axis perpendicularity = 0.0431 mm, surface perpendicularity = 0.0270 mm and parallelism = 0.1110 mm). On the other hand, in the second example, maximum MRR (12.03 mm3/min), and minimum surface roughness (4.71 μm) and kerf width (0.69 mm) can be attained at an optimal parametric intermix of SOD = 1 mm, traverse speed = 146 mm/s and abrasive flow rate = 200 g/min. Both the derived solutions closely corroborate with the observations of the past researchers, validating applicability of MACONT method in optimizing the considered AWJM processes in uncertain decision making environment.