Publication2025
Intelligent Machine Learning Strategies for Minimizing Machining Power in Minimum Quantity Lubrication Machining of Ti6Al4V Alloy
The record
- Type
- Publication
- Date
- 1 October 2025
- Level
- National
- Journal
- Journal of Materials Engineering and Performance
- Volume
- 34
- Issue
- 20
- Pages
- 24415-24428
- Published
- 1 October 2025
- DOI
- 10.1007/s11665-025-10989-x
- Scopus ID
- 105000479897
- ISSN
- 10599495
- Authors
- 5
- Open access
- No
- Citations
- 15
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Machine learning optimization of machining power in sustainable manufacturing processes for Ti6Al4V alloy demonstrates industrial innovation reducing energy consumption
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
12 Ensure sustainable consumption and production patterns
Minimum quantity lubrication machining with optimized parameters exemplifies sustainable resource consumption and waste reduction in manufacturing
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.2 Industry and manufacturing
Advanced manufacturing techniques with sustainable practices improve industrial efficiency and resource management
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Intelligent Machine Learning Strategies for Minimizing Machining Power in Minimum Quantity Lubrication Machining of Ti6Al4V Alloy”. Kortex.