Empirical models for specific energy consumption and optimization of cutting parameters for minimizing energy consumption during turning

2014 ◽  
Vol 80 ◽  
pp. 139-149 ◽  
Author(s):  
Stefan Velchev ◽  
Ivan Kolev ◽  
Krasimir Ivanov ◽  
Simeon Gechevski
Keyword(s):  
Energy Consumption ◽  
Specific Energy ◽  
Specific Energy Consumption ◽  
Cutting Parameters ◽  
Empirical Models ◽  
Optimization Of Cutting Parameters

Prediction models for specific energy consumption of machine tools and surface roughness based on cutting parameters and tool wear

2020 ◽  
pp. 095440542097106
Author(s):  
Yu Su ◽  
Congbo Li ◽  
Guoyong Zhao ◽  
Chunxiao Li ◽  
Guangxi Zhao
Keyword(s):  
Surface Roughness ◽  
Energy Consumption ◽  
Tool Wear ◽  
Specific Energy ◽  
Machine Tools ◽  
Prediction Models ◽  
Specific Energy Consumption ◽  
Cutting Parameters ◽  
Experimental Results ◽  
Support Vector

The specific energy consumption of machine tools and surface roughness are important indicators for evaluating energy consumption and surface quality in processing. Accurate prediction of them is the basis for realizing processing optimization. Although tool wear is inevitable, the effect of tool wear was seldom considered in the previous prediction models for specific energy consumption of machine tools and surface roughness. In this paper, the prediction models for specific energy consumption of machine tools and surface roughness considering tool wear evolution were developed. The cutting depth, feed rate, spindle speed, and tool flank wear were featured as input variables, and the orthogonal experimental results were used as training points to establish the prediction models based on support vector regression (SVR) algorithm. The proposed models were verified with wet turning AISI 1045 steel experiments. The experimental results indicated that the improved models based on cutting parameters and tool wear have higher prediction accuracy than the prediction models only considering cutting parameters. As such, the proposed models can be significant supplements to the existing specific energy consumption of machine tools and surface roughness modeling, and may provide useful guides on the formulation of cutting parameters.

Determination of grinding parameters of fenugreek seed

1970 ◽  
Vol 26 (1) ◽  
pp. 16 ◽  
Author(s):  
S Balasubramanian ◽  
Rajkumar Rajkumar ◽  
K K Singh
Keyword(s):  
Particle Size ◽  
Energy Consumption ◽  
Moisture Content ◽  
Specific Energy ◽  
Feed Rate ◽  
Average Particle Size ◽  
Specific Energy Consumption ◽  
Average Particle ◽  
Fenugreek Seeds ◽  
Fenugreek Seed

Experiment to identify ambient grinding conditions and energy consumed was conducted for fenugreek. Fenugreek seeds at three moisture content (5.1%, 11.5% and 17.3%, d.b.) were ground using a micro pulverizer hammer mill with different grinding screen openings (0.5, 1.0 and 1.5 mm) and feed rate (8, 16 and 24 kg h-1) at 3000 rpm. Physical properties of fenugreek seeds were also determined. Specific energy consumptions were found to decrease from 204.67 to 23.09 kJ kg-1 for increasing levels of feed rate and grinder screen openings. On the other hand specific energy consumption increased with increasing moisture content. The highest specific energy consumption was recorded for 17.3% moisture content and 8 kg h-1 feed rate with 0.5 mm screen opening. Average particle size decreased from 1.06 to 0.39 mm with increase of moisture content and grinder screen opening. It has been observed that the average particle size was minimum at 0.5 mm screen opening and 8 kg h-1 feed rate at lower moisture content. Bond’s work index and Kick’s constant were found to increase from 8.97 to 950.92 kWh kg-1 and 0.932 to 78.851 kWh kg-1 with the increase of moisture content, feed rate and grinder screen opening, respectively. Size reduction ratio and grinding effectiveness of fenugreek seed were found to decrease from 4.11 to 1.61 and 0.0118 to 0.0018 with the increase of moisture content, feed rate and grinder screen opening, respectively. The loose and compact bulk densities varied from 219.2 to 719.4 kg m-3 and 137.3 to 736.2 kg m-3, respectively.  

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