Surface Performance Multiobjective Decision of a Cold Roll-Beating Spline with the Entropy Weight Ideal Point Method

Cui, Feng; Liu, Fei; Su, Yu-Kai; Ruan, Xiaolin; Xu, S. K.; Liu, Leipo

doi:10.1155/2018/5048387

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…The entropy weight ideal point ranking method is an evaluation and ranking method that combines the entropy weight method (EWM) and the ideal point method. The entropy weight is an objective weighting method [62] that can produce a more reasonable and reliable index weight according to the measured data [57]. The entropy weight method overcomes the shortcomings of strong subjectivity, such as Expert Raters and the Analytic Hierarchy Process (AHP).…”

Section: Ranking the Pareto Frontmentioning

confidence: 99%

“…The entropy weight method overcomes the shortcomings of strong subjectivity, such as Expert Raters and the Analytic Hierarchy Process (AHP). The ideal point method determines the order of the pros and cons of each EEM (Pareto front) by calculating the distance (expressed as closeness degree) from each EEM evaluation to the ideal point [62]. The ideal point is a vector consisting of all the maximum values of each valuation index [63].…”

Section: Ranking the Pareto Frontmentioning

confidence: 99%

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A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

et al. 2023

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Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gases, especially existing buildings that do not meet energy standards. Building retrofitting is considered one of the most promising and significant solutions to reduce energy consumption and greenhouse gas emissions. However, finding suitable energy efficiency measures for existing buildings is extremely difficult due to the existence of thousands of retrofit measures and the need to meet various objectives. In this paper, a multi-stage decision framework, including a multi-objective optimization model, and a ranking method are proposed to help decision-makers select the optimal energy efficiency measures. The multi-objective optimization model considers the economic and environmental objectives, expressed as the retrofit cost and energy consumption, respectively. The entropy weight ideal point ranking method, an evaluation and ranking method that combines the entropy weight method and ideal point method, is adopted to sort the Pareto front and make a final decision. Then, the proposed decision framework was implemented for the retrofit planning of an educational building in Chongqing, China. The results show that decision-makers can quickly identify near-optimal energy efficiency measures through multi-objective optimization and can select suitable energy efficiency measures using the ranking method. Moreover, energy consumption can be reduced by building retrofitting. The energy consumption of the case building was 64.20 kWh/m2 before retrofitting, and the value can be reduced by 6.79% through retrofitting. Furthermore, the reduction in building energy consumption was significantly improved by applying the decision framework. The highest value of energy consumption was 59.84 kWh/m2, while the lowest value was 27.11 kWh/m2 when implementing the multi-stage decision framework. Thus, this paper provides a useful decision framework for decision-makers to formulate suitable energy efficiency measures.

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Section: Ranking the Pareto Frontmentioning

confidence: 99%

Section: Ranking the Pareto Frontmentioning

confidence: 99%

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

et al. 2023

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“…The depth of the microhardness layer and the model of grain evolution during the CRBF process were established. Fengkui Cui et al [10,22,23] measured the residual stress, hardness, and roughness of a spline surface fabricated by CRBF, and a series of empirical expressions were obtained to describe the effects of the roll-beating speed and feed rate on these indices.…”

Section: Introductionmentioning

confidence: 99%

Process Parameters Decision to Optimization of Cold Rolling-Beating Forming Process through Experiment and Modelling

Yang

et al. 2019

Metals

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The cold roll-beating forming (CRBF) process is a particular cold plastic bulk forming technology for metals that is adequate for shaping the external teeth of important parts. The process parameters of the CRBF process were studied in this work to improve the process performance. Of the CRBF process characteristics, the forming forces, tooth profile angle, surface roughness, and forming efficiency were selected as the target indices to describe the process performance. Single tooth experimental tests of ASTM 1045 steel were conducted with different roll-beating modes, spindle rotation speeds, and feed speeds. Using analysis of variance (ANOVA) and regression analysis, the influence of the process parameters in each index was investigated, and regression models of each index were established. Then, the linear weighted sum method and compound entropy weight method were used to determine the process parameters for multi-objective optimization. The results show that the impact capacity and optimum value range of the process parameters vary in different indices, and that, to achieve the comprehensive optimum effect of a small forming force, high product quality, and high forming efficiency, the optimal process parameter combination is the up-beating mode, a spindle rotation speed of 801 r/min, and a feed speed of 960 mm/min.

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Effects of process parameters on forming force and accuracy in cold roll-beating forming external tooth groove

Yang

et al. 2018

Int J Adv Manuf Technol

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Surface Performance Multiobjective Decision of a Cold Roll-Beating Spline with the Entropy Weight Ideal Point Method

Cited by 4 publications

References 16 publications

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

Process Parameters Decision to Optimization of Cold Rolling-Beating Forming Process through Experiment and Modelling

Effects of process parameters on forming force and accuracy in cold roll-beating forming external tooth groove

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