Pareto fronts of machining parameters for trade-off among energy consumption, cutting force and processing time

He, Keyan; Tang, Renzhong; Jin, Mingzhou

doi:10.1016/j.ijpe.2016.12.012

Cited by 53 publications

(28 citation statements)

References 20 publications

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“…The values of the two constants can be obtained by experimental power measurements The feed power P f can be expressed as Equation 5 [29], where feed speed f vt is with the unit of [mm/min]. The values of the two constants can be obtained by experimental power measurements and quadratic regression like our previous work [27].…”

Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 98%

“…According to our previous work [27,28], the energy consumption objective E o during a machining process with a fixed group of machining parameters can be approximately expressed as Equation (3). t f is the lasting time of feed movement, t c is the lasting time of cutting materials.…”

Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 99%

“…is the lasting time of feed movement, is the lasting time of cutting materials. Figure 4 shows the power profile of a typical milling process: By carrying out experiments, the values of basic machine motion power and fluid spraying power can be directly measured [27]. The selection of parameters, set-up, data acquisition, and analysis methods of the experiments can be found in our previous work [29,30], and Figure 5 shows the diagram of the experimental set-up.…”

Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy

Hong

Tang

et al. 2020

Sustainability

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Machining allowance distribution and related parameter optimization of machining processes have been well-discussed. However, for energy saving purposes, the optimization priorities of different machining phases should be different. There are often significant incoherencies between the existing research and real applications. This paper presents an improved method to optimize machining allowance distribution and parameters comprehensively, considering energy-saving strategy and other multi-objectives of different phases. The empirical parametric models of different machining phases were established, with the allowance distribution problem properly addressed. Based on previous analysis work of algorithm performance, non-dominated sorting genetic algorithm II and multi-objective evolutionary algorithm based on decomposition were chosen to obtain Pareto solutions. Algorithm performances were compared based on the efficiency of finding the Pareto fronts. Two case studies of a cylindrical turning and a face milling were carried out. Results demonstrate that the proposed method is effective in trading-off and finding precise application scopes of machining allowances and parameters used in real production. Cutting tool life and surface roughness can be greatly improved for turning. Energy consumption of rough milling can be greatly reduced to around 20% of traditional methods. The optimum algorithm of each case is also recognized. The proposed method can be easily extended to other machining scenarios and can be used as guidance of process planning for meeting various engineering demands.

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Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 98%

Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 99%

Section: Modeling Of Energy Consumption During Machining Processmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy

Hong

Tang

et al. 2020

Sustainability

Self Cite

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“…Due to resource constraints in construction projects, it has been a well-known challenge providing an effective method to solve the multi-objective tradeoff problem [46]. Various methods and algorithms that determine strategies have been used to investigate this issue [47]. Many studies have explored the time-cost tradeoff problem of project scheduling and related algorithms under certain conditions [48][49][50][51][52].…”

Section: Multi-objective Trade-off In Sustainable Constructionmentioning

confidence: 99%

A Multi-Objective Trade-Off Model in Sustainable Construction Projects

2017

Sustainability

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Based on the consideration of the relative importance of sustainability-related objectives and the inherent nature of sustainable construction projects, this study proposes that the contractor can balance the levels of efforts and resources used to improve the overall project sustainability. A multi-objective trade-off model using game theory was established and verified through simulation and numerical example under a moral hazard situation. Results indicate that effort levels of the contractor on sustainability-related objectives are positively related to the outcome coefficient while negatively to the coefficients of effort cost of the relevant objectives. High levels of the relative importance of sustainability-related objectives contribute to high levels of effort of the contractor. With the variation in effort levels and the coefficient of benefit allocation, the project net benefit increases before declining. The function of project benefit has a marked peak value, with an inverted "U" shape. An equilibrium always exists as for the given relative importance and coefficients of the effort costs of sustainability-related objectives. Under this condition, the owner may offer the contractor a less intense incentive and motivate the contractor reasonably arranging input resources. The coefficient of benefit allocation is affected by the contractor characteristic factors and the project characteristic factors. The owner should balance these two types of factors and select the most appropriate incentive mechanism to improve the project benefit. Meanwhile, the contractor can balance the relative importance of the objectives and arrange the appropriate levels of effort and resources to achieve a sustainability-related objective. Very few studies have emphasized the effects of the relative importance of sustainability-related objectives on the benefits of sustainable construction projects. This study therefore builds a multi-objective trade-off model to bridge this research gap. This study sheds significant theoretical and practical insights regarding the objective management of sustainability-related objectives, as well as insights into the improvement of performance in sustainable construction projects.

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“…Liu et al [15] took the cost of carbon emissions into account, taking the cutting speed and feed rate as decision variables, and carbon emissions and the processing time as the optimization objectives to analyze the relationship between decision variables and the optimization objectives. He et al [16] proposed the establishment of a multi-objective optimization model that takes the cutting parameters as the decision variables, and the energy consumption, cutting force, and time as the performance indicators for the turning and milling processes. Non-inferior optimal target areas were obtained through a theoretical analysis, experimental design, and statistical regression.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time

Jiang

Gao

Lü

et al. 2019

Chin. J. Mech. Eng.

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As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input-output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design (CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135di lathe cutting of AISI 1045 steel, and NSGA-II was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.

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Pareto fronts of machining parameters for trade-off among energy consumption, cutting force and processing time

Cited by 53 publications

References 20 publications

Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy

Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy

A Multi-Objective Trade-Off Model in Sustainable Construction Projects

Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time

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