E-TRACS: Embedding TRACeability in manufacturing construction Steel to aid reuse

** 炼钢是高度能源密集型的，占全球二氧化碳排放量的7%左右，占英国工业二氧化碳/温室气体排放量的14%，相当于英国总排放量的2%（英国议会Postnote no.672，2022）。英国在2021年生产了720万吨钢铁，但却是钢铁净进口国。建筑业占世界钢铁需求的50%（世界钢铁协会，2022年）;英国的这一数字约为35%。尽管钢铁具有再利用的潜力，但建筑业回收了约91%的钢铁废料。这种回收过程消耗大量能源（15000 ℃，占新钢铁所需能源的三分之一），并释放大量的碳/温室气体排放[剑桥大学无碳小组（CUULG），2020]。与回收的约65%相比，再利用的钢材已被证明可以节省95-97%的隐含碳（场外枢纽，2022年）和CUULG已经表明，有潜力高达75%的建筑钢材再利用钢铁是国家战略资产，为英国经济贡献了20亿英镑的GVA，通过再利用钢铁，我们为子孙后代保护了这一资产，并为英国的供应提供了弹性。目前，约80%的废钢出口;由于国内回收能力有限，有870万吨被送往其他国家回收。相反，钢铁可以重复使用，同时为当地带来价值，减少对钢铁生产的需求。然而，重复使用的一个关键挑战是材料的可追溯性。建筑钢材的再利用涉及多个步骤，包括从拆除现场回收，由制造商再加工，测试以确认等级，以及CE认证。这是昂贵和耗时的，当没有材料的历史，因此回收的流行，因为它仍然有助于勾选可持续性框。许多研究（例如，Grau等人，2009年）已经证明，RFID和GPS的可追溯性减少了定位材料，库存和装配工作的时间（在由4800个钢部件组成的2-结构上节省了273，257美元），由于打磨和暴露在恶劣的天气条件下而导致的产品信息丢失的问题使得这些很难付诸实践。向汽车行业等其他人学习，该项目旨在进行可行性研究，以找到最适合的解决方案，在生产过程中跟踪/跟踪建筑钢材，经得起时间的考验。初步探索将包括识别适合跟踪的钢材;合适的跟踪/跟踪系统技术;存储材料历史数据的数据库;移动的应用程序扫描技术;以及机器学习图像识别技术。

**Steelmaking is highly energy-intensive and accounts for around 7% of global CO2 emissions, and 14% of industrial CO2/GHG emissions in the UK, equivalent to 2% of total UK emissions (UK-Parliament Postnote no.672, 2022).**The UK produced 7.2 million tonnes of steel in 2021 but is a net importer of steel. Construction-industry accounts for 50% of world steel demand (World Steel Association, 2022); the figure is around 35% for the UK. Despite steel's reuse potential, the construction industry recycles around 91% of its steel waste. This recycling process consumes massive energy (at 15000c, represents one-third of the energy required for new steel) and releases significant amounts of carbon/GHG emissions \[Cambridge University Use-Less Group (CUULG), 2020\]. Reused steel has been proven to save 95-97% of embodied carbon compared to recycle's circa 65% (Offsite Hub, 2022) and the CUULG has shown there is potential for up to 75% reuse of construction steel (currently 5%).Steel is a national strategic asset contributing £2 billion of GVA to the UK economy, and by reusing steel we are safeguarding this asset for future generations and providing resilience for UK supply. Currently, around 80% of scrap steel is exported; with 8.7Mt being sent for recycling in other countries due to the limited capacity to recycle it domestically. Instead, steel could be reused while bringing value locally and reducing the demand for steel production.However, a key challenge to reuse is material traceability. Construction steel reuse involves multiple steps including recovery from demolition site, reprocessing by fabricators, testing to confirm grade, and CE certification. This is costly and time-consuming when there is no material history hence the prevalence of recycling as it still helps tick the sustainability box. Many studies (e.g., Grau, et al., 2009) have proven that RFID and GPS for traceability reduce the time for locating materials, inventorying and assembly works (saving $273,257 on 2-structures composed of 4800 steel components), the problems of lost product information due to sanding and exposure to harsh weather conditions have made it difficult to put these into practice.Learning from others like the automotive industry, this project aims to conduct a feasibility study on finding the most suitable solution to tracing/tracking construction steel during production that will stand the test of time. Initial explorations will include identifying suitable steel for tracking; suitable trace/track system technologies; databases to host material history data; mobile app scan technologies; and machine-learning image recognition technologies.