Abstract
Environmental concerns, economic benefits, and government legislations are forcing industries to improve their environmental performance. Life Cycle Assessment (LCA) is a tool to assess environmental impacts associated with a product, process, or service and is widely accepted in industry and academia. However, challenges to adopting LCA in the industry include complexity, expertise, efforts, and costs involved in Life cycle inventory (LCI) data collection. Micro, Small, and Medium-sized Enterprises (MSMEs) find this even more challenging. In this study, we expanded and used a conceptual model for Smart Manufacturing Systems (SMS model) to address the challenges of data collection in a shoe-making factory. The model maps each element of the factory in detail, while LCA provides the guidelines about which pieces of data help perform LCA. The data collected was used to model the foreground system, while data from the ecoinvent 3.7 database was used to model the background systems. Then, LCA was performed on a packaged pair of shoes (functional unit) using the open LCA software for two scenarios: (1) foreground system modelling without SMS model; (2) foreground system modelling with SMS model. The results using the ReCiPe 2016 midpoint impact assessment method and uncertainty analysis using Monte Carlo simulations showed significant differences in environmental impacts in most categories that pointed to the usefulness of using the proposed modelling approach for LCI data collection.
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Special thanks to the management of the Shoe factory (name not disclosed) for giving us their valuable time and access to the factory.
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Kaushal, I., Chakrabarti, A. System Modelling for Collecting Life Cycle Inventory (LCI) Data in MSMEs Using a Conceptual Model for Smart Manufacturing Systems (SMSs). Int. J. of Precis. Eng. and Manuf.-Green Tech. 10, 819–834 (2023). https://doi.org/10.1007/s40684-022-00489-x
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DOI: https://doi.org/10.1007/s40684-022-00489-x