Measuring uncertainty in use of digital technologies using human factors methodology

使用人为因素方法测量数字技术使用的不确定性

• 批准号: 2803351
• 金额: --
• 依托单位: Loughborough University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2803351
• 关键词: Measuring; uncertainty; use; digital; technologies

Measurements within digital technologies can still have enormous variability in setup, use and result processing yet it is highly prevalent for optimisation and throughput in manufacturing and control scenarios. Differences in measurements have a huge impact on quality data and business decisions, with variable measurements contributing a large effect on the quality of manufacturing decisions made for future processes and product release. There is huge variety in how manufacturing quality measurements are setup and optimised, which can vary as a function of the operator and environment. Machine vision and embedded intelligence are becoming more popular options to include to reduce processing times, however, the inherent parameters that define how these are used can cause additional variance due to lack of operator understanding. This project will use uncertainty principles and human factors assessment methods to compare how people interact with digital interfaces, with a quantified contribution to an uncertainty budget. This can define where and what standards can be used to reduce variability. The successful applicant will become a member of the growing Human Factors Engineering Research Group (HFERG), within the Wolfson School. The HFERG brings together a multi-disciplinary team of specialists in cognitive, physical and organisational ergonomics, taking a systems and data led approach. Our focus is on the role of people in a variety of industrial systems, supporting and enhancing wellbeing and effectiveness of the whole system. The post will align to the EPSRC-funded Made Smarter Innovation Centre for People-led Digitisation. The vision of the Centre is to be the world-leaders in providing people-led solutions to support manufacturing to have right-first-time digitalisation. The post will be based at Loughborough but will align to work at the Universities of Bath and Nottingham, with the potential to engage with a range of industry partners to deliver transformative research to unlock digitalisation potential through people-led solutions.

数字技术中的测量在设置、使用和结果处理方面仍然存在巨大的可变性，但它在制造和控制场景中的优化和吞吐量方面非常普遍。测量的差异对质量数据和业务决策产生巨大影响，可变测量对未来流程和产品发布的制造决策的质量有很大影响。制造质量测量的设置和优化方式有很大差异，并且会随着操作员和环境的不同而变化。机器视觉和嵌入式智能正在成为更受欢迎的选项，以减少处理时间，但是，由于操作员缺乏理解，定义这些使用方式的固有参数可能会导致额外的差异。该项目将使用不确定性原理和人为因素评估方法来比较人们如何与数字界面交互，并量化对不确定性预算的贡献。这可以定义在哪里以及使用什么标准来减少变异性。成功的申请者将成为沃尔夫森学院不断壮大的人因工程研究小组 (HFERG) 的成员。 HFERG 汇集了认知、物理和组织人体工程学方面的多学科专家团队，采用系统和数据主导的方法。我们的重点是人们在各种工业系统中的作用，支持和提高整个系统的福祉和有效性。该职位将与 EPSRC 资助的“以人为本的数字化变得更智能”创新中心保持一致。该中心的愿景是成为提供以人为本的解决方案的世界领导者，以支持制造业实现一次成功的数字化。该职位将设在拉夫堡，但将与巴斯大学和诺丁汉大学的工作保持一致，有可能与一系列行业合作伙伴合作，进行变革性研究，通过以人为本的解决方案释放数字化潜力。