Modelling of specific energy requirements in machining as a function of tool and lubricoolant usage

Priarone, Paolo Claudio; Robiglio, Matteo; Settineri, Luca; Tebaldo, Vincenzo

doi:10.1016/j.cirp.2016.04.108

Cited by 43 publications

(14 citation statements)

References 19 publications

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“…The machining process have minimal chance to reduce the embodied energy consumption of workpiece material. Hence, in energy efficient cutting parameter optimization, the main focuses are the electrical energy of machine tool and the embodied energy of cutting tool and cutting fluid [18][19][20].…”

Section: Energy Consumption Characteristics Of Machining Processmentioning

confidence: 99%

Energy efficient cutting parameter optimization

Chen

Tang

et al. 2021

Front. Mech. Eng.

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Mechanical 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.

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Section: Energy Consumption Characteristics Of Machining Processmentioning

confidence: 99%

Energy efficient cutting parameter optimization

Chen

Tang

et al. 2021

Front. Mech. Eng.

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“…Priarone et al [62] criticized the measurement of surface roughness Ra as a key performance indicator. They pointed out that the average surface roughness is not enough to characterize the surface profile performance and suggested using statistical parameters such as skewness (RSk) and kurtosis (RKu).…”

Section: 1-topological Aspectsmentioning

confidence: 99%

State-of-The-Art Cooling and Lubrication for Machining Inconel 718

Bartolomeis

Newman

Biermann

et al. 2020

Journal of Manufacturing Science and Engineering

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Inconel 718 is the most used nickel superalloys with applications in aerospace, oil and gas, nuclear, and chemical industries. It is mostly used for safety-critical components where the condition of the surface is a significant concern. The combination of mechanical, thermal, and chemical properties of Inconel 718 has made it a difficult-to-machine material. Despite recent advances in machining Inconel 718, achieving desired surface integrity with prescribed properties is still not possible. Different machining environments have been investigated for improving the machinability of Inconel 718 and enhance the surface integrity of machined components. This paper provides a new investigation and classification into recent advances in the machining of Inconel 718 regarding surface integrity, mostly concentrated on turning applications. The major findings and conclusions provide a critique of the state-of-the-art in machining environments for Inconel 718 together with future directions for research. Surface integrity has been evaluated in terms of surface topology as well as mechanical and microstructural properties. The impact of various cooling and lubrication methods has been investigated. It has been found that surface integrity is affected by the thermomechanical conditions at the cutting zone which are influenced by the cutting parameters, cutting tool, tool wear, and cooling/lubrication condition. The current technologies are incapable of delivering both productivity and sustainability while meeting surface integrity requirements for machining Inconel 718. High-pressure cooling has shown the potential to enhance tool wear at the expense of higher power consumption.

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“…He et al (2012) further broke the machining power into power consumed by servos system, fan motors, spindle motor, feed motor, tool changer motor and coolant pump motor. Similar work was carried out by Balogun and Mativenga (2013) and Priarone et al (2016), in which the total power was divided into basic power, ready state power, coolant pumping power, air cutting power and cutting power. In the above researches, each part of power is usually obtained from power measurements of the machine tools.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The specific cutting energy of stainless steel was evaluated as 4.72 J/mm 3 using regression analysis of measured total power required for machining and MRR. Priarone et al (2016) calculated the specific energy by dividing the measured material removal power by MRR. They observed that increased tool wear lead to higher values of specific energies due to higher increased force.…”

Section: Literature Reviewmentioning

confidence: 99%

An investigation into methods for predicting material removal energy consumption in turning

Tang

et al. 2018

Journal of Cleaner Production

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The wide use of machining processes has imposed a large pressure on environment due to energy consumption and related carbon emissions. The total power required in machining include power consumed by the machine before it starts cutting and power consumed to remove material from workpiece. Accurate prediction of energy consumption in machining is the basis for energy reduction. This paper investigates the prediction accuracy of the material removal power in turning processes, which could vary a lot due to different methods used for prediction. Three methods, namely the specific energy based method, cutting force based method and exponential function based method are considered together with model coefficients obtained from literatures and experiments. The methods have been applied to a cylindrical turning of three types of workpiece materials (carbon steel, aluminum and ductile iron). Methods with model coefficients obtained from experiments could achieve a higher prediction accuracy than those from literatures, which can be explained by the inability of the coefficients from literatures to match the specific machining conditions. When the coefficients are obtained from literatures, the prediction accuracy is largely dependent on the sources of coefficients and there is no definitive dominance of one approach over another. With model coefficients from experiments, the cutting force based model achieves the best accuracy, followed by 2 the exponential function based method and specific energy based method. Furthermore, the power prediction methods can be used in process design stage to support energy consumption reduction of a machining process.

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Modelling of specific energy requirements in machining as a function of tool and lubricoolant usage

Cited by 43 publications

References 19 publications

Energy efficient cutting parameter optimization

Energy efficient cutting parameter optimization

State-of-The-Art Cooling and Lubrication for Machining Inconel 718

An investigation into methods for predicting material removal energy consumption in turning

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