Identyfikatory
Języki publikacji
Abstrakty
Background: With socio-economic development, an increase in waste generation is observed. In view of its negative impact on the environment and human health, it is becoming increasingly important to follow the waste hierarchy and perform research on reverse logistics. It is crucial to maximize the efficiency of the separation of the waste mixture into fractions which can be returned to the material cycle in the economy. The separation process is carried out in systems such as waste sorting plants, which are characterized by complexity and variable input waste stream composition. Therefore, research in this field is usually based on simplifying assumptions and static input-output data and limited in scope. There is a lack of studies dedicated to the real-time control of these systems. Methods: We propose a Digital Twin framework for waste sorting systems to address the limitations of solutions available in the literature and to standardize the development of cyber-physical waste stream control systems. The proposed approach includes one of the key technologies of Industry 4.0, so it is in line with the Reverse Logistics 4.0 concept. Results: The main components of the Digital Twin considered were a sensor-based waste stream monitoring system, a physical model of the sorting system, a simulation model and its integration with the physical model. The deployment of a Digital Twin in line with the presented framework is demonstrated using the example of a selected plastic waste sorting plant. Conclusions: Based on the proposed approach, it is possible to include waste stream features (heterogeneity, composition uncertainty and high variability) in logistics decision-making in detail and in real time. The implementation of a Digital Twin can reduce the amount of waste sent to landfill and significantly increase the achieved recovery rates, thus increasing the amount of waste being reused and thereby contributing to the transformation to a circular economy.
Wydawca
Czasopismo
Rocznik
Tom
Strony
297--306
Opis fizyczny
Bibliogr. 29 poz., fot., rys., tab.
Twórcy
autor
- Department of Technical Systems Operation and Maintenance, Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland
autor
- Department of Technical Systems Operation and Maintenance, Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland
Bibliografia
- 1. Agrawal S., Singh R. K., Murtaza Q., 2015, A literature review and perspectives in reverse logistics, Resources, Conservation and Recycling, 97, 76–92. https://doi.org/10.1016/j.resconrec.2015.02.009
- 2. Al-Athamin E. A., Hemidat S., Al-Hamaiedeh H., Aljbour S. H., El-Hasan T., Nassour A., 2021, A techno-economic analysis of sustainable material recovery facilities: The case of Al-Karak solid waste sorting plant, Jordan, Sustainability (Switzerland), 13(23). https://doi.org/10.3390/su132313043
- 3. Ardolino F., Berto C., Arena U., 2017, Environmental performances of different configurations of a material recovery facility in a life cycle perspective, Waste Management, 68, 662–676. https://doi.org/10.1016/j.wasman.2017.05.039
- 4. Arena U., Di Gregorio F., 2014, A waste management planning based on substance flow analysis, Resources, Conservation and Recycling, 85, 54–66. https://doi.org/10.1016/j.resconrec.2013.05.008
- 5. Ashkiki A. R., Felske C., McCartney D., 2019, Impacts of seasonal variation and operating parameters on double-stage trommel performance, Waste Management, 86, 36–48. https://doi.org/10.1016/j.wasman.2019.01.026
- 6. Cherubini F., Bargigli S., Ulgiati S., 2009, Life cycle assessment (LCA) of waste management strategies: Landfilling, sorting plant and incineration, Energy, 34(12), 2116–2123. https://doi.org/10.1016/j.energy.2008.08.023
- 7. Cimpan C., Maul A., Wenzel H., Pretz T., 2016, Techno-economic assessment of central sorting at material recovery facilities - The case of lightweight packaging waste, Journal of Cleaner Production, 112, 4387–4397. https://doi.org/10.1016/j.jclepro.2015.09.011
- 8. Eriksen M. K., Damgaard A., Boldrin A., Fruergaard Astrup T., 2018, Quality Assessment and Circularity Potential of Recovery Systems for Household Plastic Waste, Journal of Industrial Ecology, 23(1). https://doi.org/10.1111/jiec.12822
- 9. Feil A., Thoden van Velzen E. U., Jansen M., Vitz P., Go N., Pretz T., 2016, Technical assessment of processing plants as exemplified by the sorting of beverage cartons from lightweight packaging wastes, Waste Management, 48, 95–105. https://doi.org/10.1016/j.wasman.2015.10.023
- 10. Gutowski T., Dahmus J., Albino D., Branham M., 2007, Bayesian material separation model with applications to recycling, IEEE International Symposium on Electronics and the Environment, 233–238. https://doi.org/10.1109/ISEE.2007.369400
- 11. Heidari R., Yazdanparast R., Jabbarzadeh A., 2019, Sustainable design of a municipal solid waste management system considering waste separators: A real-world application, Sustainable Cities and Society, 47(February), 101457. https://doi.org/10.1016/j.scs.2019.101457
- 12. Hossain M. U., Wu Z., Poon C. S., 2017, Comparative environmental evaluation of construction waste management through different waste sorting systems in Hong Kong, Waste Management, 69, 325–335. https://doi.org/10.1016/j.wasman.2017.07.043
- 13. Konstantinidis F. K., Sifnaios S., Tsimiklis G., Mouroutsos S. G., Amditis A., Gasteratos A., 2022, Multi-sensor cyber-physical sorting system (CPSS) based on Industry 4.0 principles: A multi-functional approach, Procedia Computer Science, 217(2022), 227–237. https://doi.org/10.1016/j.procs.2022.12.218
- 14. Küppers B., Seidler I., Koinig G., Pomberger R., Vollprecht D., 2020, Influence of throughput rate and input composition on sensor-based sorting efficiency, Detritus, 9(March), 59–67. https://doi.org/10.31025/2611-4135/2020.13906
- 15. Luttrell G. H., Kohmuench J. N., Mankosa M. J., 2004, Optimization of magnetic separator circuit configurations, Minerals and Metallurgical Processing, 21(3), 153–157. https://doi.org/10.1007/bf03403318
- 16. Mastellone M. L., Cremiato R., Zaccariello L., Lotito R., 2017, Evaluation of performance indicators applied to a material recovery facility fed by mixed packaging waste, Waste Management, 64, 3–11. https://doi.org/10.1016/j.wasman.2017.02.030
- 17. Medina-Mijangos R., Ajour El Zein S., Guerrero-García-Rojas H., Seguí-Amórtegui L., 2021, The economic assessment of the environmental and social impacts generated by a light packaging and bulky waste sorting and treatment facility in Spain: a circular economy example, Environmental Sciences Europe, 33(1). https://doi.org/10.1186/s12302-021-00519-6
- 18. Oliveira Neto R., Gastineau P., Cazacliu B. G., Le Guen L., Paranhos R. S., Petter C. O., 2017, An economic analysis of the processing technologies in CDW recycling platforms, Waste Management, 60(2017), 277–289. https://doi.org/10.1016/j.wasman.2016.08.011
- 19. Pluskal J., Šomplák R., Nevrlý V., Smejkalová V., Pavlas M., 2021, Strategic decisions leading to sustainable waste management: Separation, sorting and recycling possibilities, Journal of Cleaner Production, 278. https://doi.org/10.1016/j.jclepro.2020.123359
- 20. Sarc R., Curtis A., Kandlbauer L., Khodier K., Lorber K. E., Pomberger R., 2019, Digitalisation and intelligent robotics in value chain of circular economy oriented waste management – A review, Waste Management, 95, 476–492.
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- 22. Sun X., Yu H., Solvang W. D., 2022, Towards the smart and sustainable transformation of Reverse Logistics 4.0: a conceptualization and research agenda, Environmental Science and Pollution Research, 29(46), 69275–69293. https://doi.org/10.1007/s11356-022-22473-3
- 23. Tanguay-Rioux F., Legros R., Spreutels L., 2021, On the limits of empirical partition coefficients for modeling material recovery facility unit operations in municipal solid waste management, Journal of Cleaner Production, 293, 126016. https://doi.org/10.1016/j.jclepro.2021.126016
- 24. Tanguay-Rioux F., Spreutels L., Héroux M., Legros R., 2022, Mixed modeling approach for mechanical sorting processes based on physical properties of municipal solid waste, Waste Management, 144(November 2021), 533–542. https://doi.org/10.1016/j.wasman.2022.04.025
- 25. Van Schaik A., Reuter M. A., Boin U. M. J., Dalmijn W. L., 2002, Dynamic modelling and optimisation of the resource cycle of passenger vehicles, Minerals Engineering, 15(11 SUPPL. 1), 1001–1016. https://doi.org/10.1016/S0892-6875(02)00080-8
- 26. Wolf Malima I., Colledani M., Gershwin S. B., Gutowski T. G., 2010, Modeling and design of multi-stage separation systems, Proceedings of the 2010 IEEE International Symposium on Sustainable Systems and Technology, ISSST 2010. https://doi.org/10.1109/ISSST.2010.5507744
- 27. Wolf Malima Isabelle, Colledani M., Gershwin S. B., Gutowski T. G., 2013, A network flow model for the performance evaluation and design of material separation systems for recycling, IEEE Transactions on Automation Science and Engineering, 10(1), 65–75. https://doi.org/10.1109/TASE.2012.2203594
- 28. Zaman A., 2022, Waste Management 4.0: An Application of a Machine Learning Model to Identify and Measure Household Waste Contamination—A Case Study in Australia, Sustainability (Switzerland), 14(5). https://doi.org/10.3390/su14053061
- 29. Zhao Y., Li J., 2022, Sensor-Based Technologies in Effective Solid Waste Sorting : Successful Applications , Sensor Combination , and Future Directions, Environmental Science Technology, 56, 17531–17544. https://doi.org/10.1021/acs.est.2c05874
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Identyfikator YADDA
bwmeta1.element.baztech-2531d66e-3a2a-4752-9e31-c7bf293ed608