Parameter optimization of titanium alloy considering energy efficiency and tool wear based on RBFNN-MOPSO algorithm in milling

Xi, Lin; Li, Li; Li, Lingling; Zhao, Junhua; Sutherland, John W.

doi:10.1016/j.jmapro.2024.05.070

Journal of Manufacturing Processes

2024

DOI: 10.1016/j.jmapro.2024.05.070

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Parameter optimization of titanium alloy considering energy efficiency and tool wear based on RBFNN-MOPSO algorithm in milling

Lin Xi,

Li Li,

Lingling Li

et al.

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A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability

Pawanr,

Gupta

2024

Energies

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The pursuit of energy efficiency in machining processes is a critical aspect of sustainable manufacturing. A significant portion of global energy consumption is by the industrial sector; thus, improving the energy efficiency of machining processes can lead to substantial environmental and economic benefits. The present study reviews the recent advancement made for improving the energy efficiency of machining processes. First the energy consumption of the machining processes was explored and then the key areas and developments in their energy consumption modeling were identified. Following this, the review explores various strategies for achieving energy savings in machining. These strategies include energy-efficient machine tools, the accurate modeling of the energy consumption of machining processes, the implementation of optimization techniques and the application of artificial intelligence (AI). Additionally, the review highlights the potential of AI in further reducing energy consumption within machining operations and achieving energy efficiency. A review of these energy-saving strategies in machining processes reveals impressive potential for significant reductions in energy consumption: energy-efficient design can achieve up to a 45% reduction, optimizing cutting parameters may minimize consumption by around 40%, optimizing tool paths can reduce consumption by approximately 50%, optimizing non-cutting energy consumption and sequencing can lead to savings of about 30% and employing AI shows promising energy efficiency improvements of around 20%. Overall, the present review offers valuable insights into recent advancements in making machining processes more energy-efficient. It identifies key areas where significant energy savings can be achieved.

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A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability

Pawanr,

Gupta

2024

Energies

View full text Add to dashboard Cite

show abstract

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Parameter optimization of titanium alloy considering energy efficiency and tool wear based on RBFNN-MOPSO algorithm in milling

Cited by 1 publication

References 42 publications

A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability

A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability

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