Driving the Plastic Circular Economy with Advanced Technology

政府最近概述了一项战略，以尽量减少浪费，促进英国的循环经济。一个特别值得关注的领域是塑料垃圾，它已被列为高风险。这一分类归因于多种因素，包括废物再处理者/出口商数量减少、国内经济市场条件困难以及发展中国家接受废物的意愿降低。我希望利用我的聚合物化学工程知识和我对工艺过程的热情，并将其与从人机交互领域获得的技能相结合。一个跨学科的方法可能会产生解决方案，否则将错过应用单一学科的方法。通过改进数据收集、管理和使用/展示，可以支持塑料向循环经济的过渡。三个关键的兴趣领域是最大限度地收集数据的数量，最大限度地提高收集的数据的质量，并通过更有用的方式表达数据。这将需要各种人机交互领域的应用，包括说服技术，HCI实验研究方法，物联网以及其他领域，如统计分析和机器学习。这个列表不是排他性的。了解和理解塑料和线性制造的优势将使我能够针对这些应用的使用。我希望与工业界密切合作，在整个计划中建立一些副项目。对行业的激励可能是经济、环境和声誉方面的，而研究团队将从教育和数据应用中受益。问题：1)哪些技术可以帮助过渡到塑料循环经济？2)这些技术将如何以及在哪里被证明是最成功的？3)是否有机会与行业直接合作，如何实现？对于每一个项目，我会考虑：1)谁是利益相关者？2)我们如何评估这种干预的影响？目的：1)评估现有技术，探索塑料循环经济。这将包括对软件、技术和实践以及当前倡议和政策的审查。这将包括化学工程和人机交互领域的应用。2)从概念上探索和潜在地开发新的系统、建议或应用，以帮助过渡到塑料循环经济。对于每个主题，我都将从对文献进行全面的评估开始；这将使我了解当前的研究计划。我会与废物管理公司和业界专家联络，了解目前的情况。技术的组合将提供一个广泛的洞察力。随着项目的进展，文档将变得更加正式。后续任务的性质取决于确定的早期因素和辅助项目的可用性。很可能需要收集定量和定性的数据。定性研究将包括访谈和焦点小组，然后使用专题分析进行分析。定量数据可能包括从使用传感器的系统中收集的数据、基于现场的人工实验、从系统原型或调查中获得的用户数据。这个项目潜力巨大。这在一定程度上是由于技术的快速发展，以及公众对向碳中和和塑料循环经济过渡的兴趣增加。在这个阶段，很难确定产业合作的方向，尽管早期的讨论看起来很有希望。

The government has recently outlined a strategy to minimise waste and promote a circular economy for the United Kingdom. A particular area of concern is plastic waste, which has been classified as high risk. This classification has been attributed to a combination of factors including a reduction in number of waste reprocessors/exporters, difficult domestic economic market conditions and a reduced willingness to accept waste in developing nations. I hope to utilize my Chemical Engineering knowledge of polymers and passion I have for technological process and combine that with skills acquired from the field of Human-Computer interaction. An interdisciplinary approach may give rise to solutions that otherwise be missed when applying a single disciplinary approach. Transition to a circular economy for plastic can be supported by improvements in data collection, management, and use/presentation. Three key areas of interest are maximising the quantity of data gathered, maximising the quality of data gathered and by expressing data in ways that are more useful. This will require application from various Human-Computer interaction fields including Persuasive Technology, HCI experimental research methods, and the Internet of Things as well as other areas such as statistical analysis and Machine Learning. This list is not exclusive. Having knowledge and understanding of the advantages of plastics and linear manufacture will allow me to target the use of these applications. I hope to collaborate closely with industry to establish a number of side projects throughout the programme. The incentives for industry may be economic, environmental and reputational, whilst the research team will benefit from education and data application.Questions:1) What technologies can aid transition to a plastic circular economy?2) How and where will these technologies prove most successful?3) Are there opportunities to collaborate directly with industry and how will this be achieved?For each venture, I will consider:1) Who are the stakeholders?2) How can we assess the impact of this intervention? Aims:1) Evaluate existing technologies and explore the plastic circular economy. This will include a review of software, technology and practices as well as current initiatives and policies. This will include applications from the fields of both Chemical Engineering and Human-Computer interaction.2) Explore conceptually and potentially develop novel systems, proposals or applications to aid transition to a plastic circular economy. For each topic, I will begin with conducting a thorough evaluation of literature; this will provide with me insight into current research initiatives. I will liaise with waste management companies and industry experts to appreciate current conditions. A combination of techniques will provide a broad insight. As the project progresses documentation will become more formal. The nature of subsequent tasks are dependent on early factors identified and availability of side projects. It is likely that both quantitative and qualitative data gathering will be required. Qualitative studies will consist of interviews and focus groups before analysing using thematic analysis. Quantitative data will likely involve either data gathering from a system using sensors, manual field based experimentation, user data obtained from system prototyping or surveys. This project has great potential. This is partly due to technology evolving at rapid pace combined with increased public interest in transition to carbon neutrality and a plastic circular economy. At this stage, it is difficult to determine the direction of industrial collaboration although early discussions appear promising.