Multi-Response Optimization of Electrical Discharge Drilling Process of SS304 for Energy Efficiency, Product Quality, and Productivity

Nguyen, Trung-Thanh; Tran, Van-Tuan; Mia, Mozammel

doi:10.3390/ma13132897

Cited by 9 publications

(4 citation statements)

References 35 publications

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“…This methodology was developed in 1980 by Thomas L. Saaty and has been developed for the better. The method is based on a series of psychological, mathematical, and empirically proven foundations in innumerable applications [18][19][20].…”

Section: Methodsmentioning

confidence: 99%

European Universities Initiative: How Universities May Contribute to a More Sustainable Society

Valdés

Comendador

2022

Sustainability

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The European Universities initiative, launched by the European Commission in 2018, has its origin in the concept of Civic Universities (CivUs) and consists of transnational higher education alliances throughout the European Union that share long-term strategies. They are expected to become universities of the future, to promote European ideals and character, and to revolutionize the competitiveness and excellence of European higher education. European universities add 41 alliances, involving 31 different countries. This article presents an early quantitative evaluation of this initiative. This paper addresses the coverage of the 41 alliances and selects five of the most advanced for a deeper evaluation of their best practices and their contribution to the realization of CivUs. This paper also outlines the criteria for evaluating the extent to which good practices implemented by these alliances are aligned and can contribute to the attributes of CivUs, based upon state-of-the-art educational standards. A quantitative framework, based on application of the analytical hierarchy process (AHP), is also provided to rank the good practices developed by these alliances against the previous evaluation criteria. Furthermore, by applying a sensitivity analysis, this paper also addresses the robustness of this approach.

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Section: Methodsmentioning

confidence: 99%

European Universities Initiative: How Universities May Contribute to a More Sustainable Society

Valdés

Comendador

2022

Sustainability

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“…Sukumar et al ( 2014 ) used the Taguchi method and artificial neural network method to solve the optimal combination of processing parameters with the roughness in the CNC milling process as the optimization objective. Nguyen et al ( 2020 ) improved the energy efficiency, product quality, and productivity of the electrical discharge drilling (EDD) process by optimizing various parameters in the EDD process. Wang et al ( 2014 ) used the NSGA-II algorithm to solve the optimal combination of cutting parameters, and the research has shown that the optimization of cutting parameters is beneficial to energy saving in the machining process, but it will increase the cost.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective parameter optimization of CNC plane milling for sustainable manufacturing

Jia

Wang

Zhang

et al. 2022

Environ Sci Pollut Res

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Energy modeling and cutting parameter optimization of the machining process have been recognized as powerful and effective ways to save energy. However, in the actual machining process, technologists often use empirical methods to determine the final cutting parameters. Due to the lack of theoretical support and optimization tools, this method is difficult to fully consider the constraints of machine tool capability, cutting tool performance, and workpiece material, which affects the overall performance of the machine tool to give full play. To address this problem, a multi-objective parameter optimization method of computer numerical control (CNC) plane milling for sustainable manufacturing was proposed in this paper. More specifically, three tasks were carried out: (1) an accurate milling energy model considering transient processes such as spindle acceleration was established; (2) a multi-objective parameter optimization model of CNC plane milling was established with cutting parameters as optimization variables and considering various complex constraints; (3) by drawing 3D surface maps, the internal relationship between the cutting parameters and the optimization index was presented in detail and intuitively. Finally, a case study was carried out in the XHK-714F vertical machining center. The results showed that the processing efficiency is improved by 21.0%, the energy consumption is reduced by 15.3%, and the surface roughness is reduced by 5.5% through the optimization of cutting parameters, which verified the effectiveness and feasibility of the proposed model and method.

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“…Pastras et al, [47] developed an analytical and numerical approach of evaporation pulsed laser drilling process and established the energy efficiency of the pulsed laser drilling process dependent on the laser source parameters. Nguyen et al, [48] carried out optimization of electrical discharge drilling process by comprehensively considering three objectives, including energy efficiency, product quality, and drilling productivity.…”

Section: Literature Reviewmentioning

confidence: 99%

An Improved Rapid Power and Energy Prediction Method of Drilling Process for Sustainable Manufacturing

Jia

Zhang

et al. 2021

IEEE Access

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Energy modeling and energy-saving have attracted extensive attention in the manufacturing industry. Energy monitoring, modeling, and management issues of grinding, milling, and turning processes have been widely studied. However, special research on drilling power and energy consumption needs to be strengthened. The existing drilling power and energy models have the problems of high computational complexity and low practicability. To address this issue, an improved rapid power and energy prediction method of drilling process is proposed in this study. The motivation of the proposed method is to reduce the computational complexity and improve the practicability without losing the predictive accuracy for drilling power and energy. To verify the effectiveness of the proposed method, experimental and case studies were carried out. The results show that the number of formulas, variables, coefficients of the proposed method are all decreased significantly, therefore, the computational complexity is greatly reduced. Meanwhile, power predictive accuracy is improved by 1.91% instead of decreasing compared with the traditional method. Consequently, the simpler model, lower computational complexity, and higher power accuracy make the proposed method more practical in manufacturing industry.INDEX TERMS drilling processes; power prediction; energy prediction; sustainable manufacturing.

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Multi-Response Optimization of Electrical Discharge Drilling Process of SS304 for Energy Efficiency, Product Quality, and Productivity

Cited by 9 publications

References 35 publications

European Universities Initiative: How Universities May Contribute to a More Sustainable Society

European Universities Initiative: How Universities May Contribute to a More Sustainable Society

Multi-objective parameter optimization of CNC plane milling for sustainable manufacturing

An Improved Rapid Power and Energy Prediction Method of Drilling Process for Sustainable Manufacturing

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