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Determination of the Weights of Technical Criteria Influencing the Performance of Petrol-Powered and Battery Powered Chainsaws by Means of the Entropy Method

Year 2025, Volume: 11 Issue: 1, 15 - 22
https://doi.org/10.33904/ejfe.1482472

Abstract

Chainsaws are widely used in the tree cutting phase of wood harvesting activity in forest operations. In general, there are two types of chainsaws: petrol-powered and battery-powered. The performance of petrol and battery-powered chainsaws is affected by different factors, including moisture content of the wood, the tree species, environmental conditions, the experience of the operator, and the different technical characteristics of the chainsaw (power, weight, chain rotation speed, and bar length). This study aims to determine the weight of technical criteria affecting performance of petrol-powered chainsaws and battery-powered chainsaws. In the study, the entropy method was used for weight determination of the criteria. As technical criteria, chain speed at maximum power, total cylinder capacity, power, bar length, chain pitch, and weight criteria were taken into consideration for petrol-powered chainsaws. In battery-powered chainsaws, chain speed at maximum power, bar length, chain pitch, weight, and battery voltage criteria were considered. When the weight values of the technical criteria are evaluated in general, the most important performance criterion in petrol-powered chainsaws is the power criterion, while the chain speed at maximum power criterion in battery-powered saws. Based on that the power factor is the important for both chainsaws. In general, the results of this study will be beneficial for users to know how effective the technical criteria are in terms of performance in the alternative selection of different types of chainsaws, which are frequently used in different activities such as during the tree cutting phase in forest operations, pruning, and garden maintenance in urban areas.

References

  • Akay, A.O., Senturk, E., Akgul, M., Demir, M. 2023. Spatial assessment of sediment risk with integrated entropy-based WASPAS and fuzzy clustering methods in Turkey: impact of forestry activities and meteorological factors. Environmental Monitoring and Assessment, 195(10):1201.
  • Alao, M.A., Ayodele, T.R., Ogunjuyigbe, A.S.O., Popoola, O.M. 2020. Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria. Energy, 201: 117675.
  • Antonić, S., Danilović, M., Stojnić, D., Dražić, S. 2023. Impact of chainsaw power on fuel and oil consumption. Sustainability, 15(3):2795.
  • Bernardi, B., Macrì, G., Falcone, G. 2022. Productivity and life cycle assessment (LCA) of tree felling by chainsaw in thinning of calabrian pine stands. Environmental Sciences Proceedings, 22(1):10.
  • Chen, W., Feng, D., Chu, X. 2015. Study of poverty alleviation effects for Chinese fourteen contiguous destitute areas based on entropy method. International Journal of Economics and Finance, 7(4), 89-98.
  • Ciubotaru, A., Câmpu, R.V. 2018. Delimbing and cross-cutting of coniferous trees–time consumption, work productivity and performance. Forests, 9(4):206.
  • Colantoni, A., Mazzocchi, F., Cossio, F., Cecchini, M., Bedini, R., Monarca, D. 2016. Comparisons between battery chainsaws and internal combustion engine chainsaws: performance and safety. Contemporary Engineering Sciences, 9(27): 1315–1337.
  • Czyzowski, P., Korcz, N., Flis, M. 2022. Effects of time of year and chainsaw operator experience on tree felling safety. Sylwan, 166(8):491-499.
  • Goswami, S.S., Behera, D.K. 2021. Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38: 2256–2262.
  • Gulci, N., Akay, A.E., Erdas, O. 2016. Investigation of timber harvesting operations using chainsaw considering productivity and residual stand damage: The Case of Bahçe Forest Enterprise Chief. Journal Of The Faculty Of Forestry-Istanbul University, 66(2): 357-368.
  • Husqvarna, 2024. Chainsaws models. https://www.husqvarna.com/tr/motorlu-testereler/ (Accessed: 10 March 2024).
  • Jourgholami, M., Majnounian, B. Zargham, N. 2013. Performance, capability and costs of motor-manual tree felling in Hyrcanian hardwood forest. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering, 34(2), 283-293.
  • Kaliniewicz, Z., Maleszewski, Ł., Krzysiak, Z. 2018. Influence of saw chain type and wood species on the kickback angle of a chainsaw. Technical Sciences/University of Warmia and Mazury in Olsztyn, 21 (4):323–334.
  • Kumar, R., Singh, S., Bilga, P. S., Jatin, Singh, J., Singh, S., Scutaru, M.L., Pruncu, C. I. 2021. Revealing the benefits of entropy weights method for multi-objective optimization in machining operations: A critical review. Journal of Materials Research and Technology, 10: 1471–1492.
  • Laschi, A., Neri, F., Marra, E., Fabiano, F., Frassinelli, N., Marchi, E., Paoloni R., Foderi, C. 2023. Comparing the productivity of the latest models of li-ıon battery and petrol chainsaws in a conifer clear-cut site. Forests, 14(3):585.
  • Lescauskiene, I., Bausys, R., Zavadskas, E. K., Juodagalviene, B. 2020. VASMA Weighting: survey-based criteria weighting methodology that combines ENTROPY and WASPAS-SVNS to reflect the psychometric features of the VAS Scales. Symmetry, 12(10):1641.
  • Maciak, A., Kubuśka, M., Młodzińska, E. 2017. Impact of saw chain cutters type on cutting efficiency and fuel consumption in timber cutting. Annals of Warsaw University of Life Sciences – SGGW, 69:71-77.
  • Marenče, J., Mihelič, M., Poje, A. 2017. Influence of chain filing, tree species and chain type on cross cutting efficiency and health risk. Forests, 8(12):464.
  • Neri, F., Laschi, A., Marchi, E., Marra, E., Fabiano, F., Frassinelli, N., Foderi, C. 2022. Use of battery- vs. petrol-powered chainsaws in forestry: comparing performances on cutting time. Forests, 13(5):683.
  • Odu, G.O. 2019. Weighting methods for multi-criteria decision making technique. Journal of Applied Sciences and Environmental Management, 23(8):1449–1457.
  • Otto, A., Parmigiani, J. 2015. Velocity, depth-of-cut, and physical property effects on saw chain cutting. BioResources, 10(4), 7273-7291.
  • Otto, A., Parmigiani, J. P. 2018. Cutting performance comparison of low-kickback saw chain. International Journal of Forest Engineering, 29(2):83-91.
  • Özgüner, Z., Özgüner, M. 2020. Entegre Entropi-Topsis yöntemleri ile tedarikçi değerlendirme ve seçme probleminin çözümlenmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(37), 551-568.
  • Pandur, Z., Bačić, M., Šušnjar, M., Landekić, M., Šporčić, M., Jambreković, B., Lepoglavec, K. 2023. Energy consumption and cutting performance of battery-powered chainsaws. Forests, 14(7):1329.
  • Poje, A., Mihelič, M. 2020. Influence of chain sharpness, tension adjustment and type of electric chainsaw on energy consumption and cross-cutting time. Forests, 11(9): 1017.
  • Poje, A., Potočnik, I., Mihelič, M. 2018. Comparison of electric and petrol chainsaws in terms of efficiency and safety when used in young spruce stands in small-scale private forests. Small-Scale Forestry, 17(3):411–422.
  • Rukat, W., Jakubek, B., Barczewski, R., Grochalski, K. 2022. Identification of operating mode of a petrol chainsaw based on short-time parametrization and analysis of vibro-acoustic signals. Applied Acoustics, 192:108704.
  • Shannon, C. E. 1948. A mathematical theory of communication. The Bell System Technical Journal, 27(3):379–423.
  • Soenarno, Dulsalam, Yuniawati, Suhartana, S., Gandaseca, S., Rochmayanto, Y., Supriadi A., Andini, S. 2022. Working time, productivity, and cost of felling in a tropical forest: a case study from Wijaya Sentosa’s Forest Concession Area, West Papua, Indonesia. Forests, 13(11):1789.
  • Sun, R., Gong, Z., Gao, G., Shah, A. A. 2020. Comparative analysis of multi-criteria decision-making methods for flood disaster risk in the yangtze river delta. International Journal of Disaster Risk Reduction, 51:101768.
  • Tomczak, K., Naskrent, B. 2022. Work efficiency of battery-powered chainsaws during the commercial thinning in the young pine stand. Environmental Sciences Proceedings, 22(1):18.
  • Wang, E., Alp, N., Shi, J., Wang, C., Zhang, X., Chen, H. 2017. Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting. Energy, 125:197–210.
  • Wu, J., Chen, X., Lu, J. 2022. Assessment of long and short-term flood risk using the multi-criteria analysis model with the AHP-entropy method in poyang lake basin. International Journal of Disaster Risk Reduction, 75:102968.
Year 2025, Volume: 11 Issue: 1, 15 - 22
https://doi.org/10.33904/ejfe.1482472

Abstract

References

  • Akay, A.O., Senturk, E., Akgul, M., Demir, M. 2023. Spatial assessment of sediment risk with integrated entropy-based WASPAS and fuzzy clustering methods in Turkey: impact of forestry activities and meteorological factors. Environmental Monitoring and Assessment, 195(10):1201.
  • Alao, M.A., Ayodele, T.R., Ogunjuyigbe, A.S.O., Popoola, O.M. 2020. Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria. Energy, 201: 117675.
  • Antonić, S., Danilović, M., Stojnić, D., Dražić, S. 2023. Impact of chainsaw power on fuel and oil consumption. Sustainability, 15(3):2795.
  • Bernardi, B., Macrì, G., Falcone, G. 2022. Productivity and life cycle assessment (LCA) of tree felling by chainsaw in thinning of calabrian pine stands. Environmental Sciences Proceedings, 22(1):10.
  • Chen, W., Feng, D., Chu, X. 2015. Study of poverty alleviation effects for Chinese fourteen contiguous destitute areas based on entropy method. International Journal of Economics and Finance, 7(4), 89-98.
  • Ciubotaru, A., Câmpu, R.V. 2018. Delimbing and cross-cutting of coniferous trees–time consumption, work productivity and performance. Forests, 9(4):206.
  • Colantoni, A., Mazzocchi, F., Cossio, F., Cecchini, M., Bedini, R., Monarca, D. 2016. Comparisons between battery chainsaws and internal combustion engine chainsaws: performance and safety. Contemporary Engineering Sciences, 9(27): 1315–1337.
  • Czyzowski, P., Korcz, N., Flis, M. 2022. Effects of time of year and chainsaw operator experience on tree felling safety. Sylwan, 166(8):491-499.
  • Goswami, S.S., Behera, D.K. 2021. Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38: 2256–2262.
  • Gulci, N., Akay, A.E., Erdas, O. 2016. Investigation of timber harvesting operations using chainsaw considering productivity and residual stand damage: The Case of Bahçe Forest Enterprise Chief. Journal Of The Faculty Of Forestry-Istanbul University, 66(2): 357-368.
  • Husqvarna, 2024. Chainsaws models. https://www.husqvarna.com/tr/motorlu-testereler/ (Accessed: 10 March 2024).
  • Jourgholami, M., Majnounian, B. Zargham, N. 2013. Performance, capability and costs of motor-manual tree felling in Hyrcanian hardwood forest. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering, 34(2), 283-293.
  • Kaliniewicz, Z., Maleszewski, Ł., Krzysiak, Z. 2018. Influence of saw chain type and wood species on the kickback angle of a chainsaw. Technical Sciences/University of Warmia and Mazury in Olsztyn, 21 (4):323–334.
  • Kumar, R., Singh, S., Bilga, P. S., Jatin, Singh, J., Singh, S., Scutaru, M.L., Pruncu, C. I. 2021. Revealing the benefits of entropy weights method for multi-objective optimization in machining operations: A critical review. Journal of Materials Research and Technology, 10: 1471–1492.
  • Laschi, A., Neri, F., Marra, E., Fabiano, F., Frassinelli, N., Marchi, E., Paoloni R., Foderi, C. 2023. Comparing the productivity of the latest models of li-ıon battery and petrol chainsaws in a conifer clear-cut site. Forests, 14(3):585.
  • Lescauskiene, I., Bausys, R., Zavadskas, E. K., Juodagalviene, B. 2020. VASMA Weighting: survey-based criteria weighting methodology that combines ENTROPY and WASPAS-SVNS to reflect the psychometric features of the VAS Scales. Symmetry, 12(10):1641.
  • Maciak, A., Kubuśka, M., Młodzińska, E. 2017. Impact of saw chain cutters type on cutting efficiency and fuel consumption in timber cutting. Annals of Warsaw University of Life Sciences – SGGW, 69:71-77.
  • Marenče, J., Mihelič, M., Poje, A. 2017. Influence of chain filing, tree species and chain type on cross cutting efficiency and health risk. Forests, 8(12):464.
  • Neri, F., Laschi, A., Marchi, E., Marra, E., Fabiano, F., Frassinelli, N., Foderi, C. 2022. Use of battery- vs. petrol-powered chainsaws in forestry: comparing performances on cutting time. Forests, 13(5):683.
  • Odu, G.O. 2019. Weighting methods for multi-criteria decision making technique. Journal of Applied Sciences and Environmental Management, 23(8):1449–1457.
  • Otto, A., Parmigiani, J. 2015. Velocity, depth-of-cut, and physical property effects on saw chain cutting. BioResources, 10(4), 7273-7291.
  • Otto, A., Parmigiani, J. P. 2018. Cutting performance comparison of low-kickback saw chain. International Journal of Forest Engineering, 29(2):83-91.
  • Özgüner, Z., Özgüner, M. 2020. Entegre Entropi-Topsis yöntemleri ile tedarikçi değerlendirme ve seçme probleminin çözümlenmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(37), 551-568.
  • Pandur, Z., Bačić, M., Šušnjar, M., Landekić, M., Šporčić, M., Jambreković, B., Lepoglavec, K. 2023. Energy consumption and cutting performance of battery-powered chainsaws. Forests, 14(7):1329.
  • Poje, A., Mihelič, M. 2020. Influence of chain sharpness, tension adjustment and type of electric chainsaw on energy consumption and cross-cutting time. Forests, 11(9): 1017.
  • Poje, A., Potočnik, I., Mihelič, M. 2018. Comparison of electric and petrol chainsaws in terms of efficiency and safety when used in young spruce stands in small-scale private forests. Small-Scale Forestry, 17(3):411–422.
  • Rukat, W., Jakubek, B., Barczewski, R., Grochalski, K. 2022. Identification of operating mode of a petrol chainsaw based on short-time parametrization and analysis of vibro-acoustic signals. Applied Acoustics, 192:108704.
  • Shannon, C. E. 1948. A mathematical theory of communication. The Bell System Technical Journal, 27(3):379–423.
  • Soenarno, Dulsalam, Yuniawati, Suhartana, S., Gandaseca, S., Rochmayanto, Y., Supriadi A., Andini, S. 2022. Working time, productivity, and cost of felling in a tropical forest: a case study from Wijaya Sentosa’s Forest Concession Area, West Papua, Indonesia. Forests, 13(11):1789.
  • Sun, R., Gong, Z., Gao, G., Shah, A. A. 2020. Comparative analysis of multi-criteria decision-making methods for flood disaster risk in the yangtze river delta. International Journal of Disaster Risk Reduction, 51:101768.
  • Tomczak, K., Naskrent, B. 2022. Work efficiency of battery-powered chainsaws during the commercial thinning in the young pine stand. Environmental Sciences Proceedings, 22(1):18.
  • Wang, E., Alp, N., Shi, J., Wang, C., Zhang, X., Chen, H. 2017. Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting. Energy, 125:197–210.
  • Wu, J., Chen, X., Lu, J. 2022. Assessment of long and short-term flood risk using the multi-criteria analysis model with the AHP-entropy method in poyang lake basin. International Journal of Disaster Risk Reduction, 75:102968.
There are 33 citations in total.

Details

Primary Language English
Subjects Forest Products Transport and Evaluation Information
Journal Section Research Articles
Authors

Anıl Orhan Akay 0000-0002-8745-0295

Early Pub Date February 9, 2025
Publication Date
Submission Date May 11, 2024
Acceptance Date October 22, 2024
Published in Issue Year 2025 Volume: 11 Issue: 1

Cite

APA Akay, A. O. (2025). Determination of the Weights of Technical Criteria Influencing the Performance of Petrol-Powered and Battery Powered Chainsaws by Means of the Entropy Method. European Journal of Forest Engineering, 11(1), 15-22. https://doi.org/10.33904/ejfe.1482472

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The works published in European Journal of Forest Engineering (EJFE) are licensed under a  Creative Commons Attribution-NonCommercial 4.0 International License.