Data-driven sustainability evaluation for textile supply chains embedded with IoT - Paliath, Noel Antony (Nanyang Technological University, 2021)
High global emission rates and pressure from consumers and global leaders are putting Supply Chain (SC) stakeholders on the spotlight and challenging them to reimagine conventional standards for SC excellence to reduce their impact on global warming in a measurable manner. However, environmental impact assessment today – particularly Life Cycle Assessment (LCA) –is riddled with uncertainties and requires a revamp. This study has explored the means of lowering this uncertainty and have proposed a high-level technical framework that addressed bottlenecks in a structured manner. This framework leverages on Industry 4.0 (I4.0) technology clusters such as the Internet of Things (IoT), cloud computing and blockchain to improve the quality and quantity of LCA data collection. A case study was conducted on the t-shirt SC using the European Commission’s Product Environmental Footprint Category Rules (PEFCR) to understand the quality of the data collected today. Further analysis of this case study pinpointed the key stages of the SC poised for IoT integration, and is aligned to the proposed framework overall. This has also validated the practicality and design choices of the proposed framework. The proposed framework and the case study provides the foundation for the developmental work surrounding the use of IoT in improving the SC environmental impact visibility at ARTC across the next three years. The IoT framework provides LCA practitioners with a technical roadmap for tapping on the power of IoT and in helping their organisations improve their environmental performance in the most efficient manner. The methods used to analyse the case study – in identifying important trends and the key SC stages that will benefit the most from the use of IoT – can applied on a wide range of SCs in the implementation process. Collectively, these two components of the solution package acts hand-in-hand in helping organisations digitalise the environmental evaluation processes, and reduce the level of uncertainty in conducting LCA. This study has also contributed to a paper published for the 16th IEEE Conference on Industrial Electronics and Application 2021 with Dr Yang Shanshan and team from ARTC.