Carbon emissions and overall sustainability assessment in eco-friendly machining of Monel-400 alloy
Source abstract
Abstract
With increasing regulations about global warming, environmental pollution, and climate change, reducing carbon emissions from energy-intensive industrial activities routes to sustainable production. Because of its robust thermo-physical qualities at elevated temperatures, Monel 400 alloy is a renowned material for employment in modern aviation, medical tools, and prosthetic parts. Though, its structural stability imparts its low thermal conductivity that causes heat accumulation at the tool-workpiece contact during machining, resulting in tool cutting-edge damage. Many bio-based cutting fluids have been already tried to curtail heat generation and environmental footprints to progress overall machinability. In this endeavor, the effectiveness of dry, minimum quantity lubrication (MQL), cryogenic carbon dioxide (CO2) and Nano based MQL (N-MQL) are evaluated in terms of important sustainability indicator Carbon emission (CE). Multi-walled carbon Nano-tubes (MWCNT) in MQL oil limit the friction at the contact region which in turn reduces the power consumption. The highest CE value was found under a dry (0.0051 Kg-CO2) cutting environment and the lowest with N-MQL (0.0014 Kg-CO2). The sustainability assessment was done for CE with the help of Machine learning (ML) techniques like Decision tree (DT), Naïve Bayes, Random Forest (RF), and Support Vector Machine (SVM). Finally, when the CE levels are discretized while considering industrial needs, SVM paired with the Synthetic Minority Over-sampling approach (SMOTE) demonstrated an accuracy of almost around 100%.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced machining processes and optimization · Advanced Machining and Optimization Techniques · Injection Molding Process and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (54)
Show source-provided references
1. Current status, challenges and opportunities of sustainable ultra-precision manufacturing10.1007/s10845-021-01782-3 ↗
2. Resource scheduling based on energy consumption for sustainable manufacturing10.1007/s10845-015-1142-5 ↗
3. Cryogenic and minimum quantity lubrication for an eco-efficiency turning of AISI 30410.1016/j.jclepro.2016.08.030 ↗
4. Implementation of green cooling/lubrication strategies in metal cutting industries: a state of the art towards sustainable future and challenges
5. Rankin · 2014
6. Environment and economic burden of sustainable cooling/lubrication methods in machining of Inconel-80010.1016/j.jclepro.2020.125074 ↗
7. Environmental friendly cutting fluids and cooling techniques in machining: a review10.1016/j.jclepro.2014.07.071 ↗
8. Experimental comparison of the performance of nanofluids, cryogenic and hybrid cooling in turning of Inconel 62510.1016/j.triboint.2019.05.014 ↗
9. Comparison the machinability of Inconel 718, Inconel 625 and Monel 400 in hot turning operation10.1016/j.jestch.2018.03.018 ↗
10. Experimental investigation on dry turned Monel 400 alloy surface parameters with uncoated and coated tool10.1016/j.matpr.2021.03.264 ↗
11. Performance analysis in turning of D3 tool steel using silver nanoplatelets as additives under MQL10.1007/s40430-022-03909-w ↗
12. The effects of heat generation on cutting tool and machined workpiece10.1088/1742-6596/1378/2/022012 ↗
13. Process
14. Application of coolants during tool-based machining – a review
15. Influence of graphene nanofluid on various environmental factors during turning of M42 steel10.1016/j.jmapro.2021.07.019 ↗
16. Influence of cutting fluid on tool Wear and tool life during turning10.21884/IJMTER.2016.3078.9LPXS ↗
17. Experimental investigations on cryogenic cooling by liquid nitrogen in the end milling of hardened steel10.1016/j.cryogenics.2011.06.006 ↗
18. Resource saving by optimization and machining environments for sustainable manufacturing: a review and future prospects10.1016/j.rser.2022.112660 ↗
19. The critical raw materials in cutting tools for machining applications: a review10.3390/ma13061377 ↗
20. Investigation of hard turning performance of eco-friendly cooling strategies: cryogenic cooling and nanofluid based MQL10.1016/j.triboint.2019.106127 ↗
21. Examining the role of cutting Fluids in machining and efforts to address associated environmental/health concerns10.1080/10910340500534282 ↗
22. Performances of different eco-friendly nanofluid lubricants in the milling of Inconel X-750 superalloy10.1016/j.triboint.2019.04.042 ↗
23. Evaluation of a novel controlled cutting fluid impinging supply system when machining titanium alloys10.3390/app7060560 ↗
24. Dhar · 2007
25. Marksberry · 2008 · 48 · 878
26. Dilip Jerold · 2012
27. Effect of cryogenic cooling in deep hole drilling process–a stride in the direction of green manufacturing
28. Nanofluids application in machining: a comprehensive review
29. Effects of hybrid nanofluids on machining performance in MQL-milling of Inconel X-750 superalloy10.1016/j.jmapro.2021.08.038 ↗
30. Evaluation of the tribological performance of the green hBN nanofluid on the friction characteristics of AISI 316L stainless steel10.1108/ILT-04-2021-0140 ↗
31. Investigation of the performance of cermet tools in the turning of Haynes 25 superalloy under gaseous N2 and hybrid nanofluid cutting environments10.1016/j.jmapro.2022.02.029 ↗
32. Investigating the optimum molybdenum disulfide (MoS2) nanolubrication parameters in CNC milling of AL6061-T6 alloy10.1007/s00170-013-5334-x ↗
33. Effects of nano-cutting fluids on tool performance and chip morphology during machining Inconel 71810.1007/s00170-018-1825-0 ↗
34. Sustainability-based performance evaluation of hybrid nanofluid assisted machining: sustainability assessment of hybrid nanofluid assisted machining10.1016/j.jclepro.2020.120541 ↗
35. Sustainable nanomaterial-based technologies for renewable energy production and efficient storage based on machine learning techniques
36. Evaluation of machine learning approaches for estimating thermodynamic properties of new generation refrigerant R513A
37. Covid-19 prediction applying supervised machine learning algorithms with comparative analysis using weka10.3390/a14070201 ↗
38. Improving the accuracy of machine-learning models with data from machine test repetitions10.1007/s10845-020-01661-3 ↗
39. Machine learning: a review of classification and combining techniques10.1007/s10462-007-9052-3 ↗
40. Prediction and optimization of process parameters in wire cut electric discharge machining for high-speed steel (HSS)
41. Industry 4.0, digitization, and opportunities for sustainability10.1016/j.jclepro.2019.119869 ↗
42. Role of sustainable cooling/lubrication conditions in improving the tribological and machining characteristics of Monel-400 alloy10.1016/j.triboint.2022.107880 ↗
43. Thermal and fluid dynamics performance of MWCNT-water Nanofluid based on Thermophysical properties: an experimental and theoretical study10.1038/s41598-020-62143-3 ↗
44. Smart machining process using machine learning: a review and perspective on machining industry10.1007/s40684-018-0057-y ↗
45. Bio-inspiring learning style Chatbot inventory using brain computing Interface to increase the efficiency of E-learning10.1109/ACCESS.2020.2984591 ↗
46. Influence of coal ashes on fired clay brick quality: random forest regression and artificial neural networks modeling10.1016/j.jclepro.2023.137153 ↗
47. Comparative analysis of image classification algorithms based on traditional machine learning and deep learning10.1016/j.patrec.2020.07.042 ↗
48. Ecological, economical and technological perspectives based sustainability assessment in hybrid-cooling assisted machining of Ti-6Al-4 V alloy
49. Experimental investigation of friction and wear behavior of AL7075-TiO 2 -B 4 C using RSM, ANN and desirability function
50. Machine-learning for automatic prediction of flatness deviation considering the wear of the face mill teeth10.1007/s10845-020-01645-3 ↗
51. Transfer learning-based condition monitoring of single point cutting tool10.1155/2022/3205960 ↗
52. Chronic suprapubic catheterization in the management of patients with spinal cord injuries: analysis of upper and lower urinary tract complications10.1111/j.1464-410X.2007.07404.x ↗
53. Model comparison in speech emotion recognition for Indonesian language10.1016/j.procs.2021.01.098 ↗
54. Tool wear condition prediction using vibration signals in high speed machining (HSM) of titanium (Ti-6Al-4V) alloy10.1016/j.procs.2015.04.049 ↗