Integrated Sustainable Manufacturing and Waste Management Framework for Medium-Density Fiberboard (MDF): Finite Element Methods-Based Structural Optimization for Bookshelf Applications
DOI:
https://doi.org/10.26877/asset.v8i3.3440Keywords:
MDF, waste management, wood industry, manufacturing strategy, bookshelfAbstract
Medium-density fiberboard (MDF) is commonly used in furniture manufacture because of its consistent qualities, low cost, and ease of processing. However, its relatively short lifespan and rising market demand have resulted in substantial waste generation, posing serious environmental and disposal concerns. This study provides an integrated sustainable manufacturing and waste management framework for MDF that incorporates artificial intelligence technology and finite element method (FEM)-based structural optimization for bookshelf applications. The structural performance is evaluated by numerical simulations focusing on von mises stress, displacement, and safety factor. These findings indicate that combining FEM-based design optimization with intelligent waste management strategies might enhance the structural performance and sustainability of MDF products. This study emphasizes the necessity of merging advanced simulation, artificial intelligence, and life-cycle assessment methodologies to create intelligent, efficient, and ecologically responsible wood-based manufacturing systems.
References
[1] R. Salima and J. Johanssonb, “The influence of raw material on the wood product manufacturing,” Procedia CIRP, vol. 57, pp. 764–768, 2016, doi: https://doi.org/10.1016/j.procir.2016.11.132
[2] J. Hanták and D. Končeková, “The positive impact of wooden material on educational processes in the environment of Slovenian wooden kindergartens,” Archit. Pap. Fac. Archit. Des. STU, vol. 27, no. 3, pp. 29–35, 2022, doi: https://doi.org/10.2478/alfa-2022-0017.
[3] M. R.-M. and C. Aguilera-Carrasco, “Trends and Opportunities of Industry 4.0 in Wood Manufacturing Processes,” Intech, vol. 11, p. 13, 2016, doi: DOI: http://dx.doi.org/10.5772/intechopen.99581.
[4] B. M. Esteves and H. M. Pereira, “Wood modification by heat treatment: A review,” BioResources, vol. 4, no. 1, pp. 370–404, 2009, doi: https://doi.org/10.15376/biores.4.1.esteves.
[5] A. Zimmer and S. Angie Lunelli Bachmann, “Challenges for recycling medium-density fiberboard (MDF),” Results Eng., vol. 19, no. April, 2023, doi: https://doi.org/10.1016/j.rineng.2023.101277.
[6] O. Kunickaya et al., “Analysis of modern wood processing techniques in timber terminals,” Cent. Eur. For. J., vol. 68, no. 1, pp. 51–59, 2022, doi: https://doi.org/10.2478/forj-2021-0017
[7] P. Namichev and M. Petrovski, “Wood as a primary selection of material for furniture production,” J. Process Manag. New Technol., vol. 7, no. 4, pp. 6–12, 2019, doi: https://doi.org/10.5937/jouproman7-23198
[8] A. P. Wibowo, “Unveiling the Potential of AI Assistants: A Review of AI in Building Materials Selection,” J. Artif. Intell. Archit., vol. 3, no. 2, pp. 105–121, 2024, doi: https://doi.org/10.24002/jarina.v3i2.9293.
[9] S. Liao, W. Sun, and H. Zheng, “Source Tracing of Raw Material Components in Wood Vinegar Distillation Process Based on Machine Learning and Aspen Simulation,” pp. 1–16, 2025.
[10] Sushardi et al., “The selection of environmentally friendly wood for raw materials in the creative industries,” Syst. Rev. Pharm., vol. 11, no. 11, pp. 523–528, 2020, doi: https://doi.org/10.31838/srp.2020.11.75.
[11] C. Goldhahn, E. Cabane, and M. Chanana, “Sustainability in wood materials science: An opinion about current material development techniques and the end of lifetime perspectives,” Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., vol. 379, no. 2206, 2021, doi: https://doi.org/10.1098/rsta.2020.0339.
[12] J. A. Tjondro and B. Suryoatmono, “Konsep Perencanaan Struktur Pada Draft SNI Kayu 2012,” 1st Indones. Struct. Eng. Mater. Symp., no. June, 2022.
[13] S. Mohan, K. Venkatachalapathy, and P. Sudhakar, “An intelligent recognition system for identification of wood species,” J. Comput. Sci., vol. 10, no. 7, pp. 1231–1237, 2014, doi: https://doi.org/10.3844/jcssp.2014.1231.1237.
[14] S. Dan and W. Dwianto, “Fire Resistance Properties of Five Wood Species Laminated with Carbon Phenolic Spheres (CPS) Tested by Cone Calorimeter (Subyakto dan Wahyu Dwianto) Sifat Ketahanan Api Lima Jenis Kayu dengan Pelapisan Carbon Phenolic Spheres (CPS) yang Diuji dengan Cone ,” pp. 46–50.
[15] D. E. Carvalho, M. P. Rocha, R. T. Junior, and R. J. Klitzke, “Production costs in the log processing of eucalyptus spp. Wood,” An. Acad. Bras. Cienc., vol. 92, no. July, pp. 1–9, 2020, doi: https://doi.org/10.1590/0001-3765202020180486.
[16] P. Vilkovský, I. Klement, and T. Vilkovská, “The Impact of the Log-Sawing Patterns on the Quantitative and Qualitative Yield of Beech Timber (Fagus sylvatica L.),” Appl. Sci., vol. 13, no. 14, 2023, doi: https://doi.org/10.3390/app13148262.
[17] J. Kováč and M. Mikleš, “Research on individual parameters for cutting power of woodcutting process by circular saws,” J. For. Sci., vol. 56, no. 6, pp. 271–277, 2010, doi: https://doi.org/10.17221/94/2009-jfs.
[18] D. Elustondo, N. Matan, T. Langrish, and S. Pang, “Advances in wood drying research and development,” Dry. Technol., vol. 41, no. 6, pp. 890–914, 2023, doi: https://doi.org/10.1080/07373937.2023.2205530.
[19] N. Liang and J. Xiao, “Sensors & Transducers Design of Automatic Production Line Training System Based on PLC,” vol. 155, no. 8, pp. 271–277, 2013.
[20] N. Saleh et al., “Implementation of Automatic Cutting Saw Machine,” Int. Res. J. Mod. Eng. Technol. Sci., no. 06, pp. 2739–2752, 2023, doi: https://doi.org/10.56726/irjmets42089.
[21] R. Gadale, M. Pisal, S. Tayade, and S. V Kulkarni, “PLC based automatic cutting machine,” Int. J. Eng. Tech. Res., vol. 3, no. 3, pp. 280–282, 2015.
[22] S. Avramidis, C. Lazarescu, and S. Rahimi, “Basics of Wood Drying,” Springer Handbooks, no. April, pp. 679–706, 2023, doi: https://doi.org/10.1007/978-3-030-81315-4_13.
[23] S. PrakashM and S. HariSJ, “Design and Optimisation of 3 Axis CNC Wood Carving Machine,” Int. J. Innov. Sci. Res. Technol., vol. 2, no. 10, 2017, [Online]. Available: www.ijisrt.com29.
[24] S. Yaghoubi and F. Rabiei, “A profound evaluation of different strategies to improve surface roughness of manufactured part in wood-CNC machining process,” J. Eng. Res., no. May, 2024, doi: https://doi.org/10.1016/j.jer.2024.05.033.
[25] M. Tosun and S. D. Sofuoglu, “Determination of Processing Characteristics of Wood Materials Densified By Compressing,” Maderas Cienc. y Tecnol., vol. 25, no. 25, pp. 1–16, 2023, doi: https://doi.org/10.4067/s0718-221x2023000100427.
[26] M. Salzberger, T. Klein, M. Hemmerling, and T. Konstantinou, “Shape-Changing Wood Joints in Crafts and Industry and Their Potential for Building Construction and Wood Culture,” Int. J. Wood Cult., vol. 4, no. 1, pp. 58–95, 2024, doi: https://doi.org/10.1163/27723194-bja10031.
[27] A. Jesús de-los-Aires-Solís and F. Gonzalez-Quintial, “A wood-wood joining system suitable for digital fabrication and its application in the design of a ‘wood-only’ spatial module,” Front. Archit. Res., vol. 12, no. 3, pp. 523–540, 2023, doi: https://doi.org/10.1016/j.foar.2022.12.005.
[28] C. R. Frihart, J. Konnerth, A. Frangi, C. Gottlöber, R. Jockwer, and F. Pichelin, Joining and Reassembling of Wood. 2023.
[29] S. Kijmongkolvanich, S. Seviset, and S. Egwutvongsa, “Development of Geometric Shape Wood Joint Technique Into the Creation of Thai Lanna Teak Furniture with An Environmentally Friendly Process in Thailand,” Kurd. Stud., vol. 11, no. 2, pp. 1473–1492, 2023, doi: https://doi.org/10.58262/ks.v11i02.102.
[30] I. M. Ibnu, A. Siswanto, Y. P. Prihatmaji, and S. Nugroho, “Typology of wood joint geometry in basemah highland vernacular architecture, south sumatra, indonesia,” J. Des. Built Environ., vol. 23, no. 1, pp. 1–18, 2023, doi: https://doi.org/10.22452/jdbe.vol23no1.1.
[31] M. Budakci, L. Gurleyen, H. Cinar, and S. Korkut, “Effect of wood finishing and planing on surface smoothness of finished wood,” J. Appl. Sci., vol. 7, no. 16, pp. 2300–2306, 2007, doi: https://doi.org/10.3923/jas.2007.2300.2306.
[32] N. L. K. R. Kerdiati, “Understanding Wood Finishing Using the Japanese Wood Burning Technique (Shou Sugi Ban) in Architecture,” J. Aesthetics, Des. Art Manag., vol. 1, no. 1, pp. 15–23, 2021, doi: https://doi.org/10.58982/jadam.v1i1.100.
[33] R. S. Williams, D. Railings, and W. Cleaners, “Chapter 16 - Finishing of Wood,” Wood Handb. - Wood as an Eng. Mater., pp. 1–39, 2010.
[34] P. Bekhta, T. Krystofiak, B. Lis, and N. Bekhta, “The Impact of Sanding and Thermal Compression of Wood, Varnish Type and Artificial Aging in Indoor Conditions on the Varnished Surface Color,” Forests, vol. 13, no. 2, 2022, doi: https://doi.org/10.3390/f13020300.
[35] I. Çetiner, A. A. Var, and H. Çetiner, “Görüntü işleme teknikleri ile ahşap yüzey analizi,” 2014 22nd Signal Process. Commun. Appl. Conf. SIU 2014 - Proc., no. April, pp. 393–396, 2014, doi: https://doi.org/10.1109/SIU.2014.6830248.
[36] A. Sioma, “Quality control system of wooden flanges based on vision measurement system,” Wood Res., vol. 64, no. 4, pp. 637–646, 2019.
[37] M. Kryl, L. Danys, R. Jaros, R. Martinek, P. Kodytek, and P. Bilik, “Wood Recognition and Quality Imaging Inspection Systems,” J. Sensors, vol. 2020, 2020, doi: https://doi.org/10.1155/2020/3217126.
[38] E. Prates, E. da S. Lopes, C. K. Rodrigues, M. K. C. da Silva, and D. A. da Silva, “Productivity and Quality in the Processing Wood Operation for Energy,” Rev. Arvore, vol. 47, pp. 1–9, 2023, doi: https://doi.org/10.1590/1806-908820230000009.
[39] G. Alfredsen, C. Brischke, B. N. Marais, R. F. A. Stein, K. Zimmer, and M. Humar, “Modelling the material resistance of wood-part 1: Utilizing durability test data based on different reference wood species,” Forests, vol. 12, no. 5, pp. 1–19, 2021, doi: https://doi.org/10.3390/f12050558.
[40] I. Teodorescu, R. Erbasu, J. M. Branco, and D. Tapusi, “Study in the changes of the moisture content in wood,” IOP Conf. Ser. Earth Environ. Sci., vol. 664, no. 1, 2021, doi: https://doi.org/10.1088/1755-1315/664/1/012017.
[41] P. Dietsch, S. Franke, B. Franke, A. Gamper, and S. Winter, “Methods to determine wood moisture content and their applicability in monitoring concepts,” J. Civ. Struct. Heal. Monit., vol. 5, no. 2, pp. 115–127, 2015, doi: https://doi.org/10.1007/s13349-014-0082-7.
[42] L. Bragança, M. Cvetkovska, R. Askar, and V. Ungureanu, Creating a Roadmap Towards Circularity in the Built Environment. 2023.
[43] G. Daian and B. Ozarska, “Wood waste management practices and strategies to increase sustainability standards in the Australian wooden furniture manufacturing sector,” J. Clean. Prod., vol. 17, no. 17, pp. 1594–1602, 2009, doi: https://doi.org/10.1016/j.jclepro.2009.07.008.
[44] G. C. de Souza Pinho, J. L. Calmon, D. L. Medeiros, D. Vieira, and A. Bravo, “Wood Waste Management from the Furniture Industry: The Environmental Performances of Recycling, Energy Recovery, and Landfill Treatments,” Sustain., vol. 15, no. 20, p. 14944, 2023, doi: https://doi.org/10.3390/su152014944.
[45] T. Alapieti, E. Castagnoli, L. Salo, R. Mikkola, P. Pasanen, and H. Salonen, “The effects of paints and moisture content on the indoor air emissions from pinewood (Pinus sylvestris) boards,” Indoor Air, vol. 31, no. 5, pp. 1563–1576, 2021, doi: https://doi.org/10.1111/ina.12829.
[46] G. C. de S. Pinho and J. L. Calmon, “LCA of Wood Waste Management Systems: Guiding Proposal for the Standardization of Studies Based on a Critical Review,” Sustain., vol. 15, no. 3, 2023, doi: https://doi.org/10.3390/su15031854.
[47] Pan, X.; Yu, Z.; Yang, Z. A, "Multi-Scale Convolutional Neural Network Combined with a Portable Near-Infrared Spectrometer for the Rapid, Non-Destructive Identification of Wood Species". Forests 15, 556, 2024, doi: https://doi.org/10.3390/f15030556.
[48] V. Pandiyan, W. Caesarendra, T. Tjahjowidodo, and H. H. Tan, "In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm". Journal of manufacturing processes., vol.31, pp. 199-213, 2018, doi: https://doi.org/10.1016/j.jmapro.2017.11.014.
[49] W. Caesarendra, T. Triwiyanto, V. Pandiyan, A. Glowacz, S. D. H. Permana, and T. Tjahjowidodo. "A CNN prediction method for belt grinding tool wear in a polishing process utilizing 3-axes force and vibration data." Electronics., vol. 10, no. 12, 2021, 1429. doi: https://doi.org/10.3390/electronics10121429.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Advance Sustainable Science Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.





