Adaptive Neuro-Fuzzy Inference System Approach for Sustainability Assessment in Paper Industry
محورهای موضوعی : Fuzzy sets theorySalman Akhoundzadeh 1 , Mansour Soufi 2 , Seyedeh Ameneh Sajjadi 3 , Mehdi Fadaei 4
1 - Department of Industrial Management, Ra.C., Islamic Azad University, Rasht, Iran
2 - Department of Industrial Management, Ra.C., Islamic Azad University, Rasht, Iran
3 - Department of Agronomy, Ra.C., Islamic Azad University, Rasht, Iran
4 - Department of Industrial Management, Ra.C., Islamic Azad University, Rasht, Iran
کلید واژه: Sustainability, Paper Industry, Adaptive Neuro-Fuzzy Inference System (ANFIS), Green Production,
چکیده مقاله :
Paper industry, as one of the largest consumers of natural resources, faces increasing pressure to adopt sustainable practices that balance economic growth, environmental responsibility, and social well-being. Traditional evaluation methods often fall short in capturing the sector’s complex interdependencies and nonlinear dynamics. This study introduces a hybrid framework based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to assess the sustainability performance of Iranian paper manufacturing companies. A comprehensive set of 93 indicators in three sustainability indicators was identified through the literature review and expert consultation. Principal Component Analysis (PCA) was employed to refine these into 24 critical indicators, which were subsequently used to structure the ANFIS model in MATLAB. The model was trained and validated using survey data from industry professionals across multiple companies, with results demonstrating. In this study, Gaussian membership functions were selected for all input and output variables. Fuzzy rules were developed to link social, environmental, and economic sustainability dimensions, each with five membership functions. One main and three sub-models for social (5 inputs), environmental (10 inputs), and economic (9 inputs) sustainability. Data from 144 respondents across four companies, split into 70% training, 15% testing, and 15% validation, trained the model using a hybrid learning method, achieving acceptable error thresholds after 60 epochs. Validation confirmed reliability, with testing and validation errors of 0.00163 and 0.00097, respectively, and boundary tests showed logical responses. The model evaluated Setareh Shomal’s sustainability, scoring social (0.58), environmental (0.61), and economic (0.65), highlighting strengths in customer satisfaction and operational efficiency and weaknesses in energy consumption and employee safety. It is recommended that future organizational efforts prioritize improving working conditions and employee health, optimizing energy and water consumption, and reducing environmental pollutants, in order to achieve greater balance across the three core pillars of sustainability.
Paper industry, as one of the largest consumers of natural resources, faces increasing pressure to adopt sustainable practices that balance economic growth, environmental responsibility, and social well-being. Traditional evaluation methods often fall short in capturing the sector’s complex interdependencies and nonlinear dynamics. This study introduces a hybrid framework based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to assess the sustainability performance of Iranian paper manufacturing companies. A comprehensive set of 93 indicators in three sustainability indicators was identified through the literature review and expert consultation. Principal Component Analysis (PCA) was employed to refine these into 24 critical indicators, which were subsequently used to structure the ANFIS model in MATLAB. The model was trained and validated using survey data from industry professionals across multiple companies, with results demonstrating. In this study, Gaussian membership functions were selected for all input and output variables. Fuzzy rules were developed to link social, environmental, and economic sustainability dimensions, each with five membership functions. One main and three sub-models for social (5 inputs), environmental (10 inputs), and economic (9 inputs) sustainability. Data from 144 respondents across four companies, split into 70% training, 15% testing, and 15% validation, trained the model using a hybrid learning method, achieving acceptable error thresholds after 60 epochs. Validation confirmed reliability, with testing and validation errors of 0.00163 and 0.00097, respectively, and boundary tests showed logical responses. The model evaluated Setareh Shomal’s sustainability, scoring social (0.58), environmental (0.61), and economic (0.65), highlighting strengths in customer satisfaction and operational efficiency and weaknesses in energy consumption and employee safety. It is recommended that future organizational efforts prioritize improving working conditions and employee health, optimizing energy and water consumption, and reducing environmental pollutants, in order to achieve greater balance across the three core pillars of sustainability.
Alfi, S., Taleghani, M., Vatanparast, M. R., & Homayounfar, M. (2022). Studying the fundamentals and concepts of sustainability of small and medium-sized businesses based on financial indicators. Agricultural Marketing and Commercialization Journal, 6(1), 194–210.
Alfi, S., Taleghani, M., Vatanparast, M. R., & Homayounfar, M. (2023). A dynamic model for assessing the sustainability of small and medium sized enterprises. Journal of Optimization in Industrial Engineering, 17(2), 1–13.
Attar, M., Gilaninia, S., & Homayounfar, M. (2016). A study of the effect of green supply chain management's components on the performance of the pharmaceutical distribution companies system in Iran. Arabian Journal of Business and Management Review, 5(8), 48–54.
Babaei, S. M., & Patel, M. K. (2025). Optimizing energy use in the pulp and paper industry: Pinch, techno-economic, and sensitivity analyses on an innovative heat recovery system. Journal of Cleaner Production, 520, 146109.
Baghersad, M., & Zobel, C. W. (2021). Assessing the extended impacts of supply chain disruptions on firms: An empirical study. International Journal of Production Economics, 231, 107862.
Balea, A., Fuente, E., Monte, M. C., Merayo, N., Campano, C., Negro, C., & Blanco, A. (2020). Industrial application of nanocelluloses in papermaking: A review of challenges, technical solutions, and market perspectives. Molecules, 25(3), 526.
Carolin, F. C., Kamalesh, T., Kumar, P. S., Hemavathy, R. V., & Rangasamy, G. (2023). A critical review on sustainable cellulose materials and its multifaceted applications. Industrial Crops and Products, 203, 117221.
Chavooshi, A., Bahmani, A. A., Darijani, A., Mootab Saei, A., Mehrabi, E., & Gholipour, M. (2012). The role of wood and paper industries management of Iran in sustainable development [In Persian]. Journal of Conservation and Utilization of Natural Resources, 1(3), 79–96.
Daneshvar, A., Homayounfar, M., Fadaei Eshkiki, M., & Doshmanziari, E. (2021). Developing a Model for Performance Evaluaion of Teachers in Electronic Education System Using Adaptive Neuro Fuzzy Inference System (ANFIS). Journal of New Approaches in Educational Administration, 12(4), 176-190.
da Silva Junior, C. J. G., de Medeiros, A. D. M., Cavalcanti, A. K. L. d. H., de Amorim, J. D. P., Durval, I. J. B., Cavalcanti, Y. d. F., Converti, A., Costa, A. F. d. S., & Sarubbo, L. A. (2024). Towards sustainable packaging using microbial cellulose and sugarcane (Saccharum officinarum L.) bagasse. Materials, 17(15), 3732.
Fadaei Eshkiki, M., & Homayounfar, M. (2024). Green supply chain in medicine. In Decision making in healthcare systems (pp. 267–287). Springer.
Foroughi, F., Rezvani Ghomi, E., Morshedi Dehaghi, F., Borayek, R., & Ramakrishna, S. (2021). A review on the life cycle assessment of cellulose: From properties to the potential of making it a low carbon material. Materials, 14(4), 714.
Guan, Y., Li, W., Gao, H., Zhang, L., Zhou, L., & Peng, F. (2021). Preparation of cellulose nanocrystals from deinked waste newspaper and their usage for papermaking. Carbohydrate Polymer Technologies and Applications, 2, 100107.
Ghasemi Hamedan, M., Homayounfar, M., & Taleghani, M. (2025). Resilience appraisal for Iranol Oil Company: Application of adaptive neuro-fuzzy inference system. Journal of Optimization in Industrial Engineering, 38(1), 291.
Hamedi, M. M., Sandberg, M., Olsson, R. T., Pedersen, J., Benselfelt, T., & Wohlert, J. (2025). Wood and cellulose: The most sustainable advanced materials for past, present, and future civilizations. Advanced Materials, 37(22), 2415787.
Homayounfar, M., Fadaei Eshkiki, M., & Sedaghat, R. (2018a). The effect of safety management system practices, ethical leadership and self-efficacy on safety behaviour of workers in hard and harmful jobs in manufacturing industries of … Iranian Journal of Ergonomics, 6(1), 65–74.
Homayounfar, M., Goudarzvand Chegini, M., & Daneshvar, A. (2018b). Prioritization of Green Supply Chain Suppliers Using a hybrid Fuzzy Multi-Criteria Decision-Making approach. Journal of Operational Research and Its Applications, 15(2), 41–61.
Homayounfar, M., Baghersalimi, S., Nahavandi, B., & Izadi Sheyjani, K. (2018c). Agent-based simulation of National Oil Products Distribution Company’s supply network in the framework of a complex adaptive system in order to achieve an optimal inventory level. Industrial Management Journal, 10(4), 607–630.
Homayounfar, M., Kamali-Chirani, F., Chobar, A. P., & Daneshvar, A. (2025). Modeling the resilience of startups in the COVID-19 pandemic using the system dynamics approach. Journal of Safety Science and Resilience, 6(3), 100185.
Kamali Chirani, F., & Homayounfar, M. (2023). Investigating the factors affecting the resilience of startups in Iran during the COVID-19 pandemic using thematic analysis. Disaster Prevention and Management Knowledge, 13(3), 356–373.
Kazemi, Z., Homayounfar, M., Fadaei, M., Soufi, M., Salehzadeh, A. (2024). Multi-objective Optimization of Blood Supply Network Using the Meta-Heuristic Algorithms. Journal of Optimization in Industrial Engineering, 17(2), 87-104.
Kharaghani, M., Homayounfar, M., & Taleghani, M. (2023). A System Dynamics Approach for Value Chain Analysis in Pharmaceutical Industry. Journal of Industrial and Systems Engineering, 15(2), 124-139.
Kharaghani, M., Homayounfar, M., & Taleghani, M. (2024). Value Chains Analysis: Application of Fuzzy Cognitive Map in Pharmaceutical Industry. Journal of System Management, 10(2), 63–78.
Mehri Charvadeh, M., Pourmousa, S., Tajdini, A., Tamjidi, A., & Safdari, V. R. (2022). Effective indicators for the stability of a stable supply chain model in the cellulosic industry by VIKOR method [In Persian]. Iranian Journal of Wood and Paper Science Research, 39(1), 12–26.
Pourmousa, S. (2018). Challenges and Strategies for the Development of the Iranian Corrugated Box Making Industries [In Persian]. Packaging Science and Art, 10(37), 6–13.
Quintana, E., Valls, C., & Roncero, M. B. (2024). Valorization of waste-paper sludge as a sustainable source for packaging applications. Polymer Bulletin, 81, 9321–9345.
Razavinasab, S. J., Fadaei Ashkiki, M., Homayounfar, M., & Ooshaksaraie, M. (2024). Presenting a solution for sustainable control of natural gas usage in the fuel fleet of urban taxis with a system dynamics strategy . Quarterly Energy Economics Review, 18(73), 237–272.
Rincón, A., Hoyos, F. E., & Candelo-Becerra, J. E. (2024). Dynamic modeling of bacterial cellulose production using combined substrate- and biomass-dependent kinetics. Computation, 12(12), 239.
Saberifard, N., Homayounfar, M., Fadaei, M., & Taleghani, M. (2024). A system dynamics model to evaluate the LARG supply chain elements in the automotive industry. Journal of Systems Thinking in Practice, 3(4), 102–131.
Salahi, F., Daneshvar, A., Homayounfar, M., & Pourghader Chobar, A. (2023). Presenting an integrated model for production planning and preventive maintenance scheduling considering uncertainty of parameters and disruption of facilities [In Persian]. Journal of Industrial Management Perspective, 13(1), 105–140.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. Pearson.
Shafieyan, M., Homayounfar, M., & Fadaei, M. (2017). Identification of strategies for sustainable development of rice production in Guilan province using SWOT analysis. International Journal of Agricultural Management and Development, 7(2), 141–153.
Shou, Y., Shao, J., Lai, K. H., Kang, M., & Park, Y. (2019). The impact of sustainability and operations orientations on sustainable supply management and the triple bottom line. Journal of Cleaner Production, 240, 118280.
Soltanifar, M., Zargar, S. M., & Homayounfar, M. (2022). Green supplier selection: A hybrid group voting analytical hierarchy process approach [In Persian]. Journal of Operational Research in Its Applications, 19(273), 113–132.
Soufi, M., Fadaei, M., Homayounfar, M., Gheibdoust, H., & Rezaee Kelidbari, H. (2025). Evaluating the drivers of green supply chain management adoption in Iran's construction industry. Management of Environmental Quality: An International Journal, 36(6), 1626–1649.
Tavakol, P., Nahavandi, B., & Homayounfar, M. (2023a). A dynamics approach for modeling inventory fluctuations of the pharmaceutical supply chain in covid 19 pandemic. Journal of Optimization in Industrial Engineering, 16(1), 105–118.
Tavakol, P., Nahavandi, B., & Homayounfar, M. (2023b). Analyzing the Drivers of Bullwhip Effect in Pharmaceutical Industry’s Supply Chain. Journal of System Management, 9(1), 97–117.
Teng, C. P., Tan, M. Y., Toh, J. P. W., Lim, Q. F., Wang, X., Ponsford, D., Lin, E. M. J., Thitsartarn, W., & Tee, S. Y. (2023). Advances in cellulose-based composites for energy applications. Materials, 16(11), 3856.
Teixeira, S. C., Veloso de Oliveira, T., de Fátima Ferreira Soares, N., & Raymundo-Pereira, P. A. (2025). Sustainable and biodegradable polymer packaging: Perspectives, challenges, and opportunities. Food Chemistry, 470, 142652.
Veleva, V., & Ellenbecker, M. (2001). Indicators of sustainable production: Framework and methodology. Journal of Cleaner Production, 9(6), 519–549.
Verma, J., Petru, M., & Goel, S. (2024). Cellulose based materials to accelerate the transition towards sustainability. Industrial Crops and Products, 210, 118078.
Wang, Y., Wang, Z., Lin, Y., Qin, Y., He, R., Wang, M., Sun, Q., & Peng, Y. (2024). Nanocellulose from agro-industrial wastes: A review on sources, production, applications, and current challenges. Food Research International, 192, 114741.
Zachariah, S. M., Naseem, S., Rizwan, M., Nair, G. G., Grohens, Y., Sadiqa, A., Ahmad, A., & Thomas, S. (2025). Eco-friendly cellulose paper composites: A sustainable solution for EMI shielding and green engineering applications. International Journal of Biological Macromolecules, 292, 139127.
