The growing plastic waste problem has been highlighted by nature programmes like the British Broadcasting Corporation (BBC) War on Plastic series with the World Economic Forum (WEF) 2016 report estimating that by 2050, there could be more plastic than fish in the world's oceans. This has prompted the call for a shift from the linear model of tackling the plastic waste issue to that of a Circular Economy model with increasing demand for recycled resin to be incorporated into the plastic production process alongside virgin resin. However, recycled content are often associated with problems like lack of stability between various combinations of virgin/recycle polymers, which may lead to variations in temperature and inconsistency in the ease of flow attributable to the different temperature and pressure regimes under which virgin raw material and recycled feedstock melt and cool. In this paper, our main contribution is a proposed framework for integrating an enhanced AI/DB interface for analysing historical and real time information/data into a joint DSC-TGA system that allows for simultaneous quality control checks and thermal stability tests on different virgin-recycled resin mixing ratios. The database comes equipped with proven estimation methods, testing and statistical analysis results of different resin specimens to serve as a reference point for production engineers in arriving at desired check and test conditions. The information will be particularly useful to plastic product manufacturers when making decisions regarding the right virgin-recycled mix ratio conditions when using different batches of recycled resin or when they switch a supplier.

越来越多的塑料废物问题已被英国广播公司（BBC）的塑料大战系列节目等自然节目所强调，世界经济论坛（WEF）2016年报告估计到2050年，世界海洋中塑料可能比鱼类多。这促使人们呼吁从解决塑料废物问题的线性模型转向循环经济模型，因为对循环再造树脂的需求与原始树脂一起被纳入塑料生产过程中。但是，回收成分通常会带来一些问题，例如各种原始/回收聚合物组合之间缺乏稳定性，这可能会导致温度变化以及易流动性不一致，这归因于原始原料和回收原料在不同温度和压力下的熔化和冷却。在本文中，我们的主要贡献是提出了一个框架提案，该框架将用于分析历史和实时信息/数据的增强型AI / DB接口集成到一个联合DSC-TGA系统中，该系统允许同时对不同处女进行质量控制检查和热稳定性测试。再生树脂的混合比例。该数据库配备了行之有效的估算方法，不同树脂样品的测试和统计分析结果，可作为生产工程师达到所需检查和测试条件的参考点。