Cloud-based product-service systems platform for household solid waste classification management
- Author(s): Ming Wan 1, 2 ; Ting Qu 2, 3 ; Manna Huang 1, 2 ; Lianhui Li 4 ; George Q. Huang 2, 5
-
-
View affiliations
-
Affiliations:
1:
School of Management, Jinan University , No.601 Huangpu Avenue West, Guangzhou , People's Republic of China ;
2: Institute of Physical Internet, Jinan University (Zhuhai Campus) , No.206 Qianshan Road, Zhuhai , People's Republic of China ;
3: School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus) , No.206 Qianshan Road, Zhuhai , People's Republic of China ;
4: Ningxia Key Laboratory of Intelligent Information and Big Data Processing , North Minzu University , No.204 Wenchangbei Street, Yinchuan , People's Republic of China ;
5: Department Industrial and Manufacturing Systems Engineering , The University of Hong Kong , Pokfulam Road, Hong Kong , People's Republic of China
-
Affiliations:
1:
School of Management, Jinan University , No.601 Huangpu Avenue West, Guangzhou , People's Republic of China ;
- Source:
Volume 2, Issue 2,
June
2020,
p.
66 – 73
DOI: 10.1049/iet-cim.2019.0062 , Online ISSN 2516-8398
The household solid waste (HSW) classification management plays an important role in reducing and recycling urban garbage in current residential community. However, with the rapid development of urbanisation in developing countries and the continuous increase of urban waste, the traditional waste management modes and technologies cannot satisfy the newly emerged needs of collecting and transporting solid waste in the accurate and effective way. Under this background, this research carries out a preliminary study on the HSW classification system and the resource servitisation. According to the HSW classification process, a cloud-based product-service systems (PSSs) platform, targeting on managing those solid waste management resources such as internet of things enabled smart waste bin, is established. The proposed PSS platform will be illustrated from four layers: physical layer, management layer, service layer and application layer. Additionally, the multi-stakeholders' value analysis of the platform will be provided from five aspects. Finally, a PSS-based real-life case of managing household waste bin is investigated and analysed in order to verify the feasibility of the proposed platform.
Inspec keywords: recycling; waste reduction; environmental science computing; pattern classification; cloud computing
Other keywords: PSS platform; household waste bin; solid waste transportation; smart waste bin; cloud-based product-service systems platform; PSS-based real-life case; management layer; household solid waste classification management; current residential community; physical layer; application layer; solid waste management resources; HSW classification process; urban garbage; service layer; HSW classification system; urban waste
Subjects: Environmental science computing; Environmental issues; Internet software; Recycling; Industrial applications of IT
References
-
-
1)
-
24. Zhang, A., Venkatesh, V.G., Liu, Y., et al: ‘Barriers to smart waste management for a circular economy in China’, J. Cleaner Prod., 2019, 240, p. 118198.
-
-
2)
-
35. Brehm, L., Klein, B.: ‘Applying the research on product-service systems to smart and connected products’. Int. Conf. on Business Information Systems, Springer Cham, 2017, pp. 311–319.
-
-
3)
-
43. Huang, G.Q., Qu, T., Fang, M.J., et al: ‘RFID-enabled gateway product service system for collaborative manufacturing alliances’, CIRP Ann., 2011, 60, (1), pp. 465–468.
-
-
4)
-
25. Zhang, A., Venkatesh, V.G., Wang, J.X., et al: ‘Drivers of industry 4.0 enabled smart waste management in the supply chain operations: A circular economy perspective in China’, Prod. Plan. Control, 2019, Available at: https://www.researchgate.net/publication/337604414_Drivers_of_Industry_40-enabled_smart_waste_management_in_supply_chain_operations_A_circular_economy_perspective_in_China.
-
-
5)
-
44. Huang, G. Q., Zhang, Y. F., Jiang, P. Y.: ‘RFID-based wireless manufacturing for real-time management of job shop WIP inventories’, Int. J. Adv. Manuf. Technol., 2008, 36, (7–8), pp. 752–764.
-
-
6)
-
19. Thürer, M., Pan, Y.H., Qu, T., et al: ‘Internet of things (Iot) driven kanban system for reverse logistics: solid waste collection’, J. Intell. Manuf., 2019, 30, (7), pp. 2621–2630.
-
-
7)
-
30. Qu, T., Chen, X. D., Zhang, Y., et al: ‘Analytical target cascading-enabled optimal configuration platform for production service systems’, Int. J. Computer Integr. Manuf., 2011, 24, (5), pp. 457–470.
-
-
8)
-
38. Lazarova-Molnar, S., Mohamed, N., Al-Jaroodi, J.: ‘Data analytics framework for industry 4.0: enabling collaboration for added benefits’, IET Collab. Intell. Manuf., 2019, 1, (4), pp. 117–125.
-
-
9)
-
20. Meng, X., Wen, Z., Qian, Y.: ‘Multi-agent based simulation for household solid waste recycling behavior’, Resour. Conserv. Recycl., 2018, 128, pp. 535–545.
-
-
10)
-
16. Huang, G.Q., Qu, T., Zhang, Y., et al: ‘RFID-enabled product-service system for automotive part and accessory manufacturing alliances’, Int. J. Prod. Res., 2012, 50, (14), pp. 3821–3840.
-
-
11)
-
36. Zheng, P., Chen, C. H.: ‘A hybrid crowdsensing approach with cloud-edge computing framework for design innovation in smart product-service systems’. 48th Int. Conf. Compuers and Industrial Engineering, Auckland, New Zealand, 2018.
-
-
12)
-
3. Kuusiola, T., Wierink, M., Heiskanen, K.: ‘Comparison of collection schemes of municipal solid waste metallic fraction: the impacts on global warming potential for the case of the Helsinki metropolitan area, Finland’, Sustainability, 2012, 4, (10), pp. 2586–2610.
-
-
13)
-
22. Zhang, F., Cao, C., Li, C., et al: ‘A systematic review of recent developments in disaster waste management’, J. Cleaner Prod., 2019, 235, pp. 822–840.
-
-
14)
-
14. Meneses, G.D., Palacio, A.B.: ‘Recycling behavior: a multidimensional approach’, Environ. Behav., 2005, 37, (6), pp. 837–860.
-
-
15)
-
8. Tai, J., Zhang, W., Che, Y., et al: ‘Municipal solid waste source-separated collection in China: a comparative analysis’, Waste Manage. (Oxford), 2011, 31, (8), pp. 1673–1682.
-
-
16)
-
29. Baines, T.S., Lightfoot, H.W., Evans, S., et al: ‘State-of-the-art in product-service systems’, Proc. Inst. Mech. Eng. Part B-J. Eng. Manuf., 2007, 221, (10), pp. 1543–1552.
-
-
17)
-
28. Mont, O.K.: ‘Clarifying the concept of product–service system’, J. Cleaner Prod., 2002, 10, (3), pp. 237–245.
-
-
18)
-
41. Ness, D., Xing, K., Kim, K., et al: ‘An ICT-enabled product service system for reuse of building components’, IFAC-PapersOnLine, 2019, 52, (13), pp. 761–766.
-
-
19)
-
7. Sarbassov, Y., Sagalova, T., Tursunov, O., et al: ‘Survey on household solid waste sorting at source in developing economies: a case study of Nur-Sultan city in Kazakhstan’, Sustainability, 2019, 11, (22), p. 6496.
-
-
20)
-
15. Qu, T., Lei, S.P., Wang, Z.Z., et al: ‘Iot-based real-time production logistics synchronization system under smart cloud manufacturing’, Int. J. Adv. Manuf. Technol., 2016, 84, (1–4), pp. 147–164.
-
-
21)
-
10. Schultz, P.W., Oskamp, S., Mainieri, T.: ‘Who recycles and whenA review of personal and situational factors’, J. Environ. Psychol., 1995, 15, (2), pp. 105–121.
-
-
22)
-
31. Zhang, K., Wan, M., Qu, T., et al: ‘Production service system enabled by cloud-based smart resource hierarchy for a highly dynamic synchronized production process’, Adv. Eng. Inf., 2019, 42, p. 100995.
-
-
23)
-
40. Tao, F., Cheng, J., Qi, Q., et al: ‘Digital twin-driven product design, manufacturing and service with big data’, Int. J. Adv. Manuf. Technol., 2017, 94, (9–12), pp. 3563–3576.
-
-
24)
-
42. Seregni, M., Sassanelli, C., Cerri, D., et al: ‘The impact of Iot technologies on product-oriented PSS: the ‘home delivery’ service case’. 2016 IEEE Second Int. Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), Bologna, 2016, pp. 1–5.
-
-
25)
-
2. Zhang, W., Che, Y., Yang, K., et al: ‘Public opinion about the source separation of municipal solid waste in Shanghai, China’, Waste Manage. Res., 2012, 30, (12), pp. 1261–1271.
-
-
26)
-
17. Zhang, Y., Huang, G.Q., Sun, S., et al: ‘Multi-agent based real-time production scheduling method for radio frequency identification enabled ubiquitous shopfloor environment’, Comput. Ind. Eng., 2014, 76, (1), pp. 89–97.
-
-
27)
-
1. Zhang, H., Wen, Z. G.: ‘Residents’ household solid waste (HSW) source separation activity: A case study of Suzhou, China’, Sustainability, 2014, 6, (9), pp. 6446–6466.
-
-
28)
-
32. Zhang, Z., Chai, N., Liu, Y., et al: ‘Base types selection of PSS based on a priori algorithm and knowledge-based ANN’, IET Collab. Intell. Manuf., 2019, 1, (2), pp. 29–38.
-
-
29)
-
37. Ardolino, M., Saccani, N., Gaiardelli, P., et al: ‘Exploring the key enabling role of digital technologies for PSS offerings’. Proc. CIRP 47, Bergamo, Italy, 2016, pp. 561–566.
-
-
30)
-
12. Ekere, W., Mugisha, J., Drake, L.: ‘Factors influencing waste separation and utilization among households in the lake Victoria crescent, Uganda’, Waste Manage. (Oxford), 2009, 29, (12), pp. 3047–3051.
-
-
31)
-
21. Hannan, M.A., Arebey, M., Begum, R.A.., et al: ‘Radio frequency identification (RFID) and communication technologies for solid waste bin and truck monitoring system’, Waste Manage. (Oxford), 2011, 31, (12), pp. 2406–2413.
-
-
32)
-
4. Rousta, K., Bolton, K., Dahlén, L.: ‘A procedure to transform recycling behavior for source separation of household waste’, Recycling, 2016, 1, (1), pp. 147–165.
-
-
33)
-
27. Zheng, P., Wang, Z., Chen, C. H., et al: ‘A survey of smart product-service systems: key aspects, challenges and future perspectives’, Adv. Eng. Inf., 2019, 42, p. 100973.
-
-
34)
-
39. Shi, Y., Han, Q., Shen, W., et al: ‘Potential applications of 5G communication technologies in collaborative intelligent manufacturing’, IET Collab. Intell. Manuf., 2019, 1, (4), pp. 109–116.
-
-
35)
-
23. Misra, D., Das, G., Chakrabortty, T., et al: ‘An Iot-based waste management system monitored by cloud’, J. Mater. Cycles Waste Manage., 2018, 20, (3), pp. 1574–1582.
-
-
36)
-
5. Matsumoto, S.: ‘Waste separation at home: are Japanese municipal curbside recycling policies efficient ?’, Res. Conserv. Recycl., 2011, 55, (3), pp. 325–334.
-
-
37)
-
11. Sidique, S.F., Lupi, F., Joshi, S.V.: ‘The effects of behavior and attitudes on drop-off recycling activities’, Resour. Conserv. Recycl., 2010, 54, (3), pp. 163–170.
-
-
38)
-
33. Elia, V., Gnoni, M.G., Tornese, F.: ‘Assessing the efficiency of a PSS solution for waste collection: a simulation based approach’, Proc. CIRP, 2016, 47, pp. 252–257.
-
-
39)
-
6. Kattoua, M. G., Al-Khatib, I.A., Kontogianni, S.: ‘Barriers on the propagation of household solid waste recycling practices in developing countries: state of Palestine example’, J. Mater. Cycles Waste Manage., 2019, 21, (4), pp. 774–785.
-
-
40)
-
13. Owens, J., Dickerson, S., Macintosh, D.L.: ‘Demographic covariates of residential recycling efficiency’, Environ. Behav., 2000, 32, (5), pp. 637–650.
-
-
41)
-
26. Elia, V., Gnoni, M. G., Tornese, F.: ‘Designing pay-As-you-throw schemes in municipal waste management services: a holistic approach’, Waste Manage. (Oxford), 2015, 44, pp. 188–195.
-
-
42)
-
34. Rymaszewska, A., Helo, P., Gunasekaran, A.: ‘IOT powered servitization of manufacturing-an exploratory case study’, Int. J. Prod. Econ., 2017, 192, pp. 92–105.
-
-
43)
-
9. Mieszkis, K.W., Thomas, F.E.: ‘Source separation of post-consumer waste’, Conserv. Recycl., 1979, 3, (3–4), pp. 413–425.
-
-
44)
-
18. Tao, F., Cheng, Y., Da Xu, L., et al: ‘CCIot-CMfg: cloud computing and internet of things-based cloud manufacturing service system’, IEEE Trans. Ind. Inf., 2014, 10, (2), pp. 1435–1442.
-
-
1)