Abstract
For manufacturing companies to prosper in the long term, they must demonstrate contribution to sustainable development by implementing greener practices using approaches such eco-efficiency and circular economy; i.e., creating social and economic value while minimising the environmental impact of production through efficient, closed-loop circulation of resources. In addition, industrial digitalization presents new opportunities to unlock new ways to measure complex systems’ performance and systematically improve towards circular economy and sustainability. This paper presents the results of a feasibility study aiming to develop a practical toolkit to implement environmental sustainability concepts at factory level. To achieve the project objective, we focused on data handling practices for environmental performance management, including process mapping, data inventory, data quality assessment, and gap analysis to identify existing strengths and define areas of improvement to boost the environmental performance of production systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sterner, T., et al.: Policy design for the anthropocene. Nat. Sustain. 2, 14–21 (2019). https://doi.org/10.1038/s41893-018-0194-x
Steffen, W., et al.: Planetary boundaries: GUIDING human development on a changing planet. Science 347(6223), 1259855 (2015). https://doi.org/10.1126/science.1259855
Clift, R., et al.: The challenges of applying planetary boundaries as a basis for strategic decision-making in companies with global supply chains. Sustain 9 (2017). https://doi.org/10.3390/su9020279
Sarkis, J., Rasheed, A.: Greening the manufacturing function. Bus. Horiz. 38, 17–27 (1995). https://doi.org/10.1016/0007-6813(95)90032-2
Weisz, H., Suh, S., Graedel, T.E.: Industrial ecology: The role of manufactured capital in sustainability. Proc. Natl. Acad. Sci. U. S. A. 112, 6260–6264 (2015). https://doi.org/10.1073/pnas.1506532112
Baumann, H., Cowell, S.J.: An evaluative framework for conceptual and analytical approaches used in environmental management. Greener Manag. Int. 26, 109–122 (1999)
Robèrt, K.-H.: Tools and concepts for sustainable development, how do they relate to a general framework for sustainable development, and to each other? J. Clean. Prod. 8, 243–254 (2000). https://doi.org/10.1016/S0959-6526(00)00011-1
Finnveden, G., Moberg, A.: Environmental systems analysis tools - An overview. J. Clean. Prod. 13, 1165–1173 (2005). https://doi.org/10.1016/j.jclepro.2004.06.004
Syu, F.S., et al.: Usability and Usefulness of circularity indicators for manufacturing performance management. Procedia CIRP 105, 835–840 (2022)
Lunt, P., Ball, P., Levers, A.: Barriers to industrial energy efficiency. Int. J. Energy Sect. Manag. 8, 380–394 (2014). https://doi.org/10.1108/IJESM-05-2013-0008
Vatankhah Barenji, A., Liu, X., Guo, H., Li, Z.: A digital twin-driven approach towards smart manufacturing: reduced energy consumption for a robotic cell. Int. J. Comput. Integr. Manuf. 34, 844–859 (2021). https://doi.org/10.1080/0951192X.2020.1775297
Bärring, M., Johansson, B., Stahre, J.: Digital technologies enabling data of production systems for decision support. Smart Sustain. Manuf. Syst. 4(2), 62−79 (2020).https://doi.org/10.1520/SSMS20190034
Gadaleta, M., Pellicciari, M., Berselli, G.: Optimization of the energy consumption of industrial robots for automatic code generation. Robot. Comput. Integr. Manuf. 57, 452–464 (2019). https://doi.org/10.1016/j.rcim.2018.12.020
Despeisse, M., Bekar, E.T.: Challenges in data life cycle management for sustainable cyber-physical production systems. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds.) APMS 2020. IAICT, vol. 592, pp. 57–65. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-57997-5_7
Levitin, A., Redman, T.: Quality dimensions of a conceptual view. Inf. Process. Manag. 31, 81–88 (1995). https://doi.org/10.1016/0306-4573(95)80008-H
Tao, F., Qi, Q., Liu, A., Kusiak, A.: Data-driven smart manufacturing. J. Manuf. Syst. 48, 157–169 (2018). https://doi.org/10.1016/j.jmsy.2018.01.006
Rüegg, J., et al.: Completing the data life cycle: Using information management in macrosystems ecology research. Front. Ecol. Environ. 12, 24–30 (2014). https://doi.org/10.1890/120375
Yoon, V.Y., Aiken, P., Guimaraes, T.: Managing organizational data resources: quality dimensions. Inf. Resour. Manag. J. 13, 5–13 (2000). https://doi.org/10.4018/irmj.2000070101
Costa, C., Santos, M.Y.: Big data: state-of-the-art concepts, techniques, technologies, modeling approaches and research challenges. IAENG Int. J. Comput. Sci. 44, 285–301 (2017)
Chen, A.J.W., Boudreau, M., Watson, R.T.: Information systems and ecological sustainability. J. Syst. Inf. Technol. 10, 186–201 (2008). https://doi.org/10.1108/13287260810916907
Despeisse, M., Chari, A., González Chávez, C.A., Monteiro, H., Machado, C.G., Johansson, B.: A systematic review of empirical studies on green manufacturing: eight propositions and a research framework for digitalized sustainable manufacturing. Prod. Manuf. Res. 10, 727–759 (2022). https://doi.org/10.1080/21693277.2022.2127428
Despeisse, M.: How environmentally sustainable is the on-going industrial digitalization? global trends and a Swedish perspective. In: Advances in Transdisciplinary Engineering, pp. 316–328 (2022)
Joung, C.B., Carrell, J., Sarkar, P., Feng, S.C.: Categorization of indicators for sustainable manufacturing. Ecol. Indic. 24, 148–157 (2013). https://doi.org/10.1016/j.ecolind.2012.05.030
Acerbi, F., Taisch, M.: A literature review on circular economy adoption in the manufacturing sector. J. Clean. Prod. 273 123086 (2020). https://doi.org/10.1016/j.jclepro.2020.123086
Acerbi, F., Sassanelli, C., Taisch, M.: A conceptual data model promoting data-driven circular manufacturing. Oper. Manag. Res. 15, 838–857 (2022). https://doi.org/10.1007/s12063-022-00271-x
Ellen MacArthur Foundation: Circularity Indicators: An Approach to Measuring Circularity . Methodology (2019)
Walden, J., Steinbrecher, A., Marinkovic, M.: Digital product passports as enabler of the circular economy. Chem.Ing.Tech. 93, 1717–1727 (2021). https://doi.org/10.1002/cite.202100121
Berger, K., Schöggl, J.P., Baumgartner, R.J.: Digital battery passports to enable circular and sustainable value chains: conceptualization and use cases. J. Clean. Prod. 353, 131492 (2022). https://doi.org/10.1016/j.jclepro.2022.131492
Despeisse, M., Ball, P.D., Evans, S., Levers, A.: Industrial ecology at factory level: a prototype methodology. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 226, 1648−1664 (2012). https://doi.org/10.1177/0954405412449937
Acknowledgements
This work was supported by Swedish innovation agency Vinnova and the strategic innovation programme Produktion2030 under grant no. 2022–02460. The work was carried out within Chalmers’ Area of Advance Production. The support is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 IFIP International Federation for Information Processing
About this paper
Cite this paper
Despeisse, M. et al. (2023). Developing Data Models for Smart Environmental Performance Management in Production. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-031-43688-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-43688-8_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-43687-1
Online ISBN: 978-3-031-43688-8
eBook Packages: Computer ScienceComputer Science (R0)
