scholarly journals Energy efficient cutting parameter optimization

2021 ◽  
Author(s):  
Xingzheng Chen ◽  
Congbo Li ◽  
Ying Tang ◽  
Li Li ◽  
Hongcheng Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Parameter Optimization ◽  
Energy Efficient ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Current Status ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization

AbstractMechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

Application of Genetic Algorithm in Cutting Parameter Optimization

2014 ◽  
Vol 1082 ◽  
pp. 138-142
Author(s):  
Li Feng Zhu ◽  
Yan Zhang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Parameter Optimization ◽  
Cutting Parameters ◽  
Parameters Optimization ◽  
Numerical Control ◽  
Numerical Control Machining ◽  
Factors Affecting ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization

Process parameters optimization is an important problem in numerical control machining, through the analysis of various factors affecting the cutting effect in cutting process, a mathematical model of cutting parameter optimization in NC machining is established and the constraint conditions are also determined in the paper. The article puts forward using genetic algorithm to realize the optimization of mathematical model, and the optimization analysis results are verified in practical processing. The experimental results show that the optimized cutting parameters can satisfy machining requests and improve the cutting efficiency.

Cutting Parameter Optimization Technique for High Efficiency NC Machining

2011 ◽  
Vol 211-212 ◽  
pp. 167-171
Author(s):  
An Jiang Cai ◽  
Shi Hong Guo ◽  
Zhao Yang Dong ◽  
Hong Wei Guo
Keyword(s):  
Neural Network ◽  
Parameter Optimization ◽  
Bp Neural Network ◽  
High Efficiency ◽  
Cutting Parameters ◽  
Nc Machining ◽  
Processing Efficiency ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization ◽  
Bp Neural Network Model

High efficient cutting process technique is one of the main development directions of cutting process technology in the future, a reasonable choice of NC machining cutting parameter is an important way to realize high efficiency NC machining. NC machining cutting parameter optimization techniques were studied, using BP neural network, milling parameters optimization model of aluminum alloy shell structure was built, and the structure of BP neural network was analysed, realizing the optimizing of the BP neural network model, the improving of the convergence accuracy, convergence speed, prediction accuracy, generalization ability of BP neural network model, which optimized the cutting parameters selection and predicted the processing efficiency to provide a theoretical basis for the selection of high efficiency NC machining cutting parameter. Production practice showed: the application of the optimized cutting parameters of BP neural network for processing could improve processing efficiency, reduce costs notablely while guaranteeing the processing quality, and achieve the optimization of integrated application efficiency for high efficiency NC machining and NC machine, so it has a higher promotional value.

scholarly journals Research on High Speed Cutting Parameter Optimization and Fault Diagnosis Technology

2014 ◽  
Vol 6 ◽  
pp. 281216 ◽  
Author(s):  
Honggen Zhou ◽  
Xuwen Jing ◽  
Lei Wang ◽  
Kaiyun Dai ◽  
Jia Yongpeng
Keyword(s):  
Mathematical Model ◽  
Fault Diagnosis ◽  
Parameter Optimization ◽  
High Speed ◽  
Cutting Parameters ◽  
Cutting Process ◽  
High Speed Cutting ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization ◽  
The Mathematical Model

High speed cutting process is a very complicated process; cutting parameters have a significant effect on cutting process and play a key role in the process of product manufacturing. The overall scheme of high speed cutting parameter optimization and its fault diagnosis have been introduced. The mathematical model of the selected cutting parameters was established and the optimized parameters were obtained by combining the experimental design with the technology of data processing. The statistical description of high speed cutting process control was introduced and the fault diagnosis model of cutting parameter optimization by using the neural network was proposed. Finally, the mathematical model in the present study is validated with a numerical example. The results show that the present method solved the problem of poor universality of high speed cutting data effectively and avoided the inaccuracy of physical and chemical mechanism research. Meanwhile, the present study prevents the passive checks of the cutting and gets better diagnosis of the complicated cutting fault type.

Studying The Effect of a New Mixed Cutting Fluid on Surface Roughness

2020 ◽  
Vol 38 (11A) ◽  
pp. 1593-1601
Author(s):  
Mohammed H. Shaker ◽  
Salah K. Jawad ◽  
Maan A. Tawfiq
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Machining Processes ◽  
Dry Cutting ◽  
Cutting Speeds

This research studied the influence of cutting fluids and cutting parameters on the surface roughness for stainless steel worked by turning machine in dry and wet cutting cases. The work was done with different cutting speeds, and feed rates with a fixed depth of cutting. During the machining process, heat was generated and effects of higher surface roughness of work material. In this study, the effects of some cutting fluids, and dry cutting on surface roughness have been examined in turning of AISI316 stainless steel material. Sodium Lauryl Ether Sulfate (SLES) instead of other soluble oils has been used and compared to dry machining processes. Experiments have been performed at four cutting speeds (60, 95, 155, 240) m/min, feed rates (0.065, 0.08, 0.096, 0.114) mm/rev. and constant depth of cut (0.5) mm. The amount of decrease in Ra after the used suggested mixture arrived at (0.21µm), while Ra exceeded (1µm) in case of soluble oils This means the suggested mixture gave the best results of lubricating properties than other cases.

Cutting parameter optimization for machining operations considering carbon emissions

2019 ◽  
Vol 208 ◽  
pp. 937-950 ◽  
Author(s):  
Guanghui Zhou ◽  
Qi Lu ◽  
Zhongdong Xiao ◽  
Ce Zhou ◽  
Changle Tian
Keyword(s):  
Parameter Optimization ◽  
Carbon Emissions ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization ◽  
Machining Operations

Potential of Pine Needle Biomass as an Alternative Fuel to Mitigate Forest Fire in Uttarakhand Himalayas - A Review

2021 ◽  
Vol 58 (02) ◽  
pp. 192-203
Author(s):  
Padam Singh ◽  
T. P. Singh ◽  
Rajat Kumar Sharma ◽  
Yogesh Kumar Negi ◽  
Ramesh Pal
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Anaerobic Digestion ◽  
Forest Fire ◽  
Energy Efficient ◽  
Alternative Fuel ◽  
Pine Needle ◽  
Direct Combustion ◽  
Energy Harnessing

Pine needle is a typical biomass which is abundantly available in Uttarakhand hills. This shredded biomass contributes significantly in forest fire occurring regularly in Uttarakhand. Different energy harnessing routes as direct combustion, anaerobic digestion, pyrolysis, gasification, and briquetting for pine needle were reviewed. These routes were further compared on the basis of energy consumption and energy efficiency of the processes as per the available literature. The review suggested that briquetting of pine needle and its anaerobic digestion are two most energy efficient methods having energy efficiency of 88% and 41.6%, respectively. The estimated energy required for briquetting of 1 ton pine needle was 1370.5 MJ, whereas for gasification it was 1170 MJ

Reliable and Energy-Efficient Routing Scheme for Underwater Wireless Sensor Networks (UWSNs)

2021 ◽  
Vol 11 (4) ◽  
pp. 42-58
Author(s):  
Semab Iqbal ◽  
Israr Hussain ◽  
Zubair Sharif ◽  
Kamran Hassan Qureshi ◽  
Javeria Jabeen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Transmission Error ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Underwater Communication ◽  
Radio Waves ◽  
Energy Efficient Routing ◽  
Resource Exploration

Despite the fact that the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Underwater wireless sensor network (UWSN) is one of the options helping us to discover some domains such as natural assets and underwater resource exploration. However, the acoustic signal is the only suitable option in underwater communication in the absence of radio waves, which face a number of challenges under this environment. To overcome these issues, many routing schemes are introduced by researchers though energy consumption is still a challenge in underwater communication. To overcome the issue of rapid energy consumption, a reliable and energy-efficient routing method is introduced that avoids the redundant forwarding of data; hence, it achieves energy efficiency and eventually prolongs the network lifetime. Simulation results support the claim that the proposed scheme achieves energy efficiency along higher delivery ratio by reducing the data transmission error rate during the routing decisions.

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