Development of Hybrid Optimization Model Using Grey‐ANFIS‐Jaya Algorithm for CNC Drilling of Aluminium Alloy Article Swipe
Lakshmi Narasimhamu Katta
,
N. Manikandan
,
Thejasree Pasupuleti
,
Emad Makki
,
Jayant Giri
,
Neeraj Sunheriya
,
Rajkumar Chadge
,
Chetan Mahatme
,
Pallavi Giri
,
T. Sathish
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1155/2024/1476770
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1155/2024/1476770
Aluminium alloys are gaining popularity in a diversity of engineering applications because of their extraordinary features such as strength, resistance to oxidation, and so on. AA5052 (Al‐Mg series) is generally used in antirust uses, particularly in desalination related activities, due to its better resistance to corrosion in marine applications at temperature ranges up to 125°C, lower cost, better heat‐carrying capacity, and nontoxicity of its corrosion components. Drilling is one of the most commonly adopted material removal processes that is adopted in numerous engineering uses. Taguchi’s technique is engaged to arrange and examine the tests, by treating the drilling diameter and speed and as independent process factors. The studies were carried out using an L27 orthogonal array. Material removal rate (MRR), surface roughness (SR), and form/orientation error are deemed as output characteristics. Taguchi’s analysis was engaged to discover the best process factors. ANOVA is used to examine the influence of process variables. Suitable application of artificial intelligence tools for making effective decision assists the manufacturer in accomplishing the benefits in numerous engineering domains. To obtain the maximum material removal and minimum roughness, circularity (circ), and perpendicularity errors (perp), the process variables have been optimized with the help of grey‐ANFIS‐amalgamated with Jaya algorithm. The multiperformance index was developed using grey theory. Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best‐suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2024/1476770
- https://downloads.hindawi.com/journals/je/2024/1476770.pdf
- OA Status
- gold
- Cited By
- 14
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391618467
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391618467Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/2024/1476770Digital Object Identifier
- Title
-
Development of Hybrid Optimization Model Using Grey‐ANFIS‐Jaya Algorithm for CNC Drilling of Aluminium AlloyWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
-
Lakshmi Narasimhamu Katta, N. Manikandan, Thejasree Pasupuleti, Emad Makki, Jayant Giri, Neeraj Sunheriya, Rajkumar Chadge, Chetan Mahatme, Pallavi Giri, T. SathishList of authors in order
- Landing page
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https://doi.org/10.1155/2024/1476770Publisher landing page
- PDF URL
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https://downloads.hindawi.com/journals/je/2024/1476770.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://downloads.hindawi.com/journals/je/2024/1476770.pdfDirect OA link when available
- Concepts
-
Aluminium, Drilling, Aluminium alloy, Alloy, Computer science, Algorithm, Engineering drawing, Engineering, Mechanical engineering, Materials science, MetallurgyTop concepts (fields/topics) attached by OpenAlex
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14Total citation count in OpenAlex
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2025: 9, 2024: 5Per-year citation counts (last 5 years)
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29Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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