Energy consumption characteristics in finish hard milling

Liu, Z. Y.; Sealy, Michael P.; Li, W.; Zhang, D.; Fang, Xiaojun; Guo, Y. B.; Liu, Z. Q.

doi:10.1016/j.jmapro.2018.08.036

Cited by 35 publications

(10 citation statements)

References 22 publications

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“…The results of such capabilities represent an innovative product that is best suited to the environment, which ultimately gains the support of the customers and all other stakeholders. The safe products that incorporate a low energy consumption support the businesses for making it a consumers' priority, which finally leads to the sustainability [72]. Sustainability is a major goal in many sectors, including the tourism one, where sustainability is a main issue for tourism further development [73].…”

Section: Green Business Strategies and Sustainable Developmentmentioning

confidence: 99%

Harmonization of Green Motives and Green Business Strategies towards Sustainable Development of Hospitality and Tourism Industry: Green Environmental Policies

Yousaf¹,

Rădulescu

Sinisi

et al. 2021

Sustainability

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This study aims to investigate the direct impact of green motives (GM) and green business strategies (GBS) on sustainable development (SD) in the hospitality sector. It explores the direct links between GM and SD. Moreover, the mediating role of GBS between GM and SD was tested. The research relies on the stakeholders’ theory, which states that the organization’s success and future development depends on the satisfaction of stakeholders. Data were collected from 451 top managers and owners from 54 hotels (5, 4 and 3-star hotels) operating in Pakistan. Quantitative analysis including correlation, regression, confirmatory factor analysis and structural equation model techniques were used. The mediating role of GBS was assessed using the bootstrapping method. Results proved that GM and GBS enable hotel industry to achieve the targets of SD. Finding also proved that GBS act as a mediator between the GM and SD link. The hotel industry needs attention to achieve the targets of SD and customers’ inclination towards more hygienic and environmental issues after the worldwide COVID-19 pandemic situation has forced the hotel industry to adapt GBS initiated through GM. The current research articulated this upcoming issue and offered a SD model for the hotel industry.

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Section: Green Business Strategies and Sustainable Developmentmentioning

confidence: 99%

Harmonization of Green Motives and Green Business Strategies towards Sustainable Development of Hospitality and Tourism Industry: Green Environmental Policies

Yousaf¹,

Rădulescu

Sinisi

et al. 2021

Sustainability

View full text Add to dashboard Cite

show abstract

“…Garg et al [13] applied a variety of advanced intelligent optimization algorithms to model and analyze the energy consumption in the turning process, and finally found that cutting speed is the main factor affecting the power consumption of the machine tool. Based on the prediction model of material removal energy consumption, Some researchers found that when different processing technology planning and processing were adopted, the machine tool energy consumption was greatly affected [14,15]. Wang et al established a novel drilling energy consumption prediction model, which fully considers the impact of tool wear on energy consumption, and experimental results show that the model has high prediction accuracy [16].…”

Section: Prediction Of Cutting Energy Consumptionmentioning

confidence: 99%

Modeling and Multi-objective Optimization Method of Machine Tool Energy Consumption Considering Tool Wear

Tian

Zhang

2021

Int. J. of Precis. Eng. and Manuf.-Green Tech.

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The natural energy crisis and the increasingly serious environmental problems have imposed all industries to reduce energy consumption. During milling process, selecting a correct cutting parameters can not only greatly improve production quality and processing efficiency, but also can reduce energy consumption, in addition, tool wear also has a great impact on them. Therefore, a milling power consumption model of CNC machine tools is established based on modern machining theory is established in this article, unlike traditional energy consumption models, our model takes full account of cutting conditions and tool wear. The surface roughness of parts is one of the important indicators to measure the machining quality of machine tools. Therefore, taking milling process as research object, a multi-objective cutting parameters optimization model that takes the machining surface roughness, material removal rate (MRR) and machining energy consumption as the optimization goals was established. Furthermore, an intelligent optimization algorithm was proposed based on improved Teaching-Learning-Based Optimization (TLBO) to solve the model under various limited milling conditions. Finally, comparing experimental results of optimized parameter and empirical parameters, it shows that goals of reducing energy consumption, improving productivity and machining quality can be achieved by optimizing cutting parameters.

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“…Energy consumption with regard to machine tool can be divided into three main approaches: machine tools, spindle, and process levels. 17,18 At the machine perspective, the whole energy efficiency of the machine is considered. However, saving energy at this level is not practical.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of hard milling process of AISI H13 in terms of productivity, quality, and cutting energy under nanofluid minimum quantity lubrication condition

Dang

Huang

2020

Measurement and Control

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This paper presents the multi-objective optimization of the hard milling process of AISI H13 steel under minimum quality lubricant with graphite nanoparticle. The cutting speed, feed per tooth, depth of cut, and hardness of workpiece were taken as the process parameters, while surface roughness, cutting energy, cutting temperature, and material removal rate were considered as technological responses. Response surface or Kriging approximate models were applied to generate the mathematical regression models showing the relationship between machining inputs and outputs obtained by physical experiments. Then, multi-objective particle swarm optimization algorithm in conjunction with the Pareto approach and engineering data mining was adopted to figure out the feasible solutions. The research results show that cutting energy can be reduced up to around 14% compared to the worst case. Based on the Pareto plot, the appropriate selection of machining parameters can help the machine tool operator to increase machining productivity and energy efficiency.

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Energy consumption characteristics in finish hard milling

Cited by 35 publications

References 22 publications

Harmonization of Green Motives and Green Business Strategies towards Sustainable Development of Hospitality and Tourism Industry: Green Environmental Policies

Harmonization of Green Motives and Green Business Strategies towards Sustainable Development of Hospitality and Tourism Industry: Green Environmental Policies

Modeling and Multi-objective Optimization Method of Machine Tool Energy Consumption Considering Tool Wear

Multi-objective optimization of hard milling process of AISI H13 in terms of productivity, quality, and cutting energy under nanofluid minimum quantity lubrication condition

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