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Implementing innovative gaze analytic methods in design for manufacturing: a study on eye movements in exploiting design guidelines

机译:实施制造设计中的创新凝视分析方法:剥削设计指南的眼球运动研究

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Design guidelines aim to raise awareness of possibilities and limitations in manufacturing. The guidelines intend to support engineers and students to exploit the potential of manufacturing processes and to overcome the challenges of design for manufacturing. However although there are studies which show the benefit of guidelines, it remains unclear how this benefit is achieved or why it is missing. The aim of the present paper is to analyze the visual behavior of engineers and students while working with a design guideline. Gaze stationary and transition entropy are eye tracking metrics that quantitatively describe visual behavior. These metrics have been implemented in fields such as medicine and arts, but not yet in engineering. We conducted a study with 16 engineers and 20 students, who work with a design guideline and then solved an engineering design task. Their performance was classified by the manufacturability and the manufacturing effort of the design outcome, and their scanning patterns were analyzed using innovative eye tracking metrics. The results show that high performing engineers have a significant lower stationary entropy, while high performing students tend to have both high stationary and high transition entropies. While we were not able to show clear group differences, to predict the performance only through visual scanning behavior, gaze entropy remains a feasible metric for interest and curiosity. Furthermore, we adopt a Target Based Analysis for design methods to further investigate in the benefit of design guidelines.
机译:设计指南旨在提高对制造业的可能性和局限性的认识。指导方针打算支持工程师和学生利用制造流程的潜力,并克服制造业设计的挑战。然而,虽然有关于指导方针的好处的研究,但仍然尚不清楚如何实现这种益处或者为什么缺少这一福利。本文的目的是分析工程师和学生的视觉行为,同时使用设计指南。凝视静止和过渡熵是定量描述视觉行为的眼跟踪度量。这些指标已经在诸如医学和艺术等领域实施,但尚未在工程中实施。我们通过16工程师和20名学生进行了一项研究,他们使用设计指南,然后解决了工程设计任务。他们的表现是通过设计结果的可制造性和制造工作来归类的归类,并使用创新的眼跟踪指标进行分析它们的扫描模式。结果表明,高性能工程师具有显着较低的静止熵,而高性能的学生倾向于具有高静止和高过渡熵。虽然我们无法显示明确的群体差异,但仅通过视觉扫描行为预测性能,凝视熵仍然是兴趣和好奇心的可行度量。此外,我们采用了基于目标的设计方法,以进一步调查设计指南。

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