Article detail · 2022
Estimation, optimization and analysis based investigation of the energy consumption in machinability of ceramic-based metal matrix composite materials
Journal
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&TISSN 2238-7854
The ISSN points to another catalog journal; the name is from the YÖKSİS record.
- Year
- 2022
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
- Catalog match (ISSN) Journal of Materials Research and Technology
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
The current study aims to determine the influence of machining and production parameters during the milling of Cu/B–CrC composites. The relationship between energy consumption and cutting speed, feed rate and reinforcement ratio were investigated. For this purpose, 2d and 3d graphs for comparison of the effects of input parameters were demonstrated and analyzed. The predictability of the energy consumption during milling was measured by a fuzzy inference system (FIS). According to the graphical and optimization results, the optimum conditions to obtain the minimum energy consumption were 5% reinforcement ratio, 125 m/min cutting speed and 0.2 mm/rev feed rate. A reinforcement ratio of 52.71% was the most effective factor on energy demand followed by the feed rate (24.26%) and cutting speed (12.85%). According to the obtained results, there was a minor margin of error between the actual and predicted findings ranging from 1.6 to 2.4%. Considering the energy consumption is one of the key factors among machinability criteria, the study proposes a comprehensive approach for industrial and academic works.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
54 citations
OpenAlex cited_by_count (cache / database)
37 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Machinability Investigations Based on Tool Wear, Surface Roughness, Cutting Temperature, Chip Morphology and Material Removal Rate during Dry and MQL-Assisted Milling of Nimax Mold Steel 2023
- Machinability Investigations Based on Tool Wear, Surface Roughness, Cutting Temperature, Chip Morphology and Material Removal Rate during Dry and MQL-Assisted Milling of Nimax Mold Steel 2023
- Different Aspects of Machinability in Turning of AISI 304 Stainless Steel: A Sustainable Approach with MQL Technology 2023
- Different Aspects of Machinability in Turning of AISI 304 Stainless Steel: A Sustainable Approach with MQL Technology 2023
- Machining and optimization of reinforced copper composites using different cooling-lubrication conditions 2022
- Investigation of the Effects of Cooling and Lubricating Strategies on Tribological Characteristics in Machining of Hybrid Composites 2022
- Investigation of the Effects of Cooling and Lubricating Strategies on Tribological Characteristics in Machining of Hybrid Composites 2022
- Investigation of the Effects of Cooling and Lubricating Strategies on Tribological Characteristics in Machining of Hybrid Composites 2022
- Machining characterization and optimization under different cooling/lubrication conditions of Al-4Gr hybrid composites fabricated by vacuum sintering 2023
- Development of the hardness, three-point bending, and wear behavior of self-lubricating Cu-5Gr/Al2O3-Cr3C2 hybrid composites 2023