Abstract
The concept of circular economy (CE) aims to close and slow resource loops without neglecting the goals of sustainable development. Recently, the concept received encouraging attention among researchers and business experts to be a convenient solution to move away from the finite linear economy concept to a more sustainable solution. However, this change of paradigm is only possible if we consider systems in a holistic manner and can localize the preventing hurdles.
Value stream mapping (VSM) is a commonly known lean method, used to develop current state visualization of product and information flows within organization, helping to seek weaknesses and improve process flows. The motivation of this paper is a new C-VSM model, which enables its users to evaluate and visualize connected process-chains regarding CE on different levels in a holistic manner. For this purpose, the traditional VSM model was adapted towards the needs and requirements of CE through the application of a new representation method, additional indicators, and an appropriated evaluation system. C-VSM is in line with the current political and industrial objectives to apply CE principles by enabling a holistic reflection and consideration of supply-chains (SCs) on different levels. The model itself is validated through an extensive cross-company case study.
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Funding
This research was funded by the Di-Plast project, which is supported by Interreg NWE. The project aims to improve the uptake of recycled plastic material (rPM) within the packaging and building sectors. Di-Plast aims to improve processes for a more stable rPM material supply and quality.
Find more details about Di-Plast at https://www.nweurope.eu/projects/project-search/di-plast-digital-circular-economy-for-the-plastics-industry/.
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Mangers, J., Minoufekr, M., Plapper, P. (2021). Value Stream Mapping (VSM) to Evaluate and Visualize Interrelated Process-Chains Regarding Circular Economy. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_56
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