Robust optimization of energy consumption during mechanical processing of wood

Melo, Diego Jean de; Guedes, Taiane Oliveira; Silva, José Reinaldo Moreira da; Paiva, Anderson Paulo de

doi:10.1007/s00107-019-01458-z

Cited by 5 publications

(5 citation statements)

References 29 publications

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“…Density is one of the main parameters for assessing quality and indicative of wood use. It is the product of different wood anatomical characteristics, and it has a direct and indirect relationship with several other wood characteristics [41], such as mechanical properties [42][43][44][45], best energetic product [46][47][48][49] and material durability, machinability and workability [50,51].…”

Section: Physical Propertiesmentioning

confidence: 99%

Wood from Forest Residues: Technological Properties and Potential Uses of Branches of Three Species from Brazilian Amazon

et al. 2022

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Branch wood presents potential volumetry that may have several applications, and its use may improve forest management efficiency in the Amazon. However, there is a lack of knowledge regarding the properties of branch wood when compared to the stem or what its potential applications might be, considering the possible variability of wood formation in branches. This study aimed to characterize physically and mechanically the branch wood of Dipteryx odorata, Hymenolobium petraeum and Hymenaea courbaril and to compare them with their respective stems. No significant statistical differences were observed for the basic density between the branch and stem woods. The branch wood of Dipteryx odorata and Hymenaea courbaril showed a lower coefficient of anisotropy (1.23 and 1.99, respectively) than the stem wood (1.62 and 2.49, respectively). D. odorata showed similar mechanical properties between the branch and stem, except for hardness, while H. petraeum and H. courbaril branch wood showed lower strengths when compared to the stem wood for all mechanical tests, except for the shear strength test. Branch wood has similar potential uses to stem wood and can be used for non-structural purposes such as small artifacts, decorative items, furniture, tools and panels composed of short, glued pieces.

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Section: Physical Propertiesmentioning

confidence: 99%

Wood from Forest Residues: Technological Properties and Potential Uses of Branches of Three Species from Brazilian Amazon

et al. 2022

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“…Therefore, studying the energy consumption of machine tools in the materials processing has great significance for promoting the power efficiency and energy-saving operation, and then achieving the purposes of sustainable development of the manufacturing industry and reducing environmental pollution. Taking wood material machining as an example, improving energy efficiency is also one of the key research directions in wood material processing [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Optimization of cutting power and power efficiency during particleboard helical milling

Yao

Wang

2023

Materialwissenschaft Werkst

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With the aim of providing scientific guidance for the application of spiral cutters in particleboard machining, this work studied the influence of milling parameters on milling power and power efficiency during helical milling of particleboard. And the response surface methodology was applied to optimize the milling parameters to reduce machining energy consumption and improve energy efficiency. The factors of milling depth, spindle speed and helical angle were selected as input parameters, and the mathematical models between the input parameters and the response parameters were established. Then, the significant influence of each factor and the interaction of two factors were determined by variance analysis, and the change trend of milling power and power efficiency was studied by response surface methodology. Results showed that the milling depth had the greatest impact on milling power and power efficiency, followed by the spindle speed and helical angle. An increase in the milling depth and spindle speed resulted in an increase in milling power and power efficiency, while the increased helical angle resulted in a decrease in milling power and power efficiency. The optimized values of helical angle, spindle speed and milling depth were 54°, 5650 min−1 and 1.3 mm, respectively.

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“…Their results showed that the cutting motor rotation, feed motor rotation and cutting depth had significant influence on the specific cutting energy. They also found that the optimal parameter combination for lower power consumption was determined by the mean square error (MSE) [33]. The ANN modeling method is also a common modeling technique to predict the cutting power.…”

Section: Introductionmentioning

confidence: 99%

Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards

Yao

et al. 2022

Materials

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The cutting power consumption of milling has direct influence on the economic benefits of manufacturing particle boards. The influence of the milling parameters on the cutting power were investigated in this study. Experiments and data analyses were conducted based on the response surface methodology. The results show that the input parameters had significant effects on the cutting power. The high rake angle reduced the cutting force. Thus, the cutting power decreased with the increase in the rake angle and the cutting energy consumption was also reduced. The cutting power increased with the rotation speed of the main shaft and the depth of milling induced the impact resistance between the milling tool and particle board and the material removal rate. The P-values of the created models and input parameters were less than 0.05, which meant they were significant for cutting power and power efficiency. The depth of milling was the most important factor, followed by the rotation speed of the main shaft and then the rake angle. Due to the high values of R2 of 0.9926 and 0.9946, the quadratic models were chosen for creating the relationship between the input parameters and response parameters. The predicted values of cutting power and power efficiency were close to the actual values, which meant the models could perform good predictions. To minimize the cutting power and maximize the power efficiency for the particle board, the optimized parameters obtained via the response surface methodology were 2°, 6991.7 rpm, 1.36 mm for rake angle, rotation speed of the main shaft and depth of milling, respectively. The model further predicted that the optimized parameters combination would achieve cutting power and power efficiency values of 52.4 W and 11.9%, respectively, with the desirability of 0.732. In this study, the influence of the input parameters on the cutting power and power efficiency are revealed and the created models were useful for selecting the milling parameters for particle boards, to reduce the cutting power.

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Robust optimization of energy consumption during mechanical processing of wood

Cited by 5 publications

References 29 publications

Wood from Forest Residues: Technological Properties and Potential Uses of Branches of Three Species from Brazilian Amazon

Wood from Forest Residues: Technological Properties and Potential Uses of Branches of Three Species from Brazilian Amazon

Optimization of cutting power and power efficiency during particleboard helical milling

Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards

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