Sensor-based modeling of problem-solving in virtual reality manufacturing systems
Sensor-based modeling of problem-solving in virtual reality manufacturing systems
复制标题
虚拟现实制造系统中基于传感器的问题解决建模
DOI：
10.1016/j.eswa.2022.117220
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发表时间：
2022
影响因子：
8.5
通讯作者：
Yang, Hui
中科院分区：
文献类型：
--
作者：
Zhu, Rui;Aqlan, Faisal;Zhao, Richard;Yang, Hui
问题解决是在解决路径不确定的情况下实现目标的过程。近年来，技术的进步改变了工程领域中问题的性质和解决方法。强大的解决问题的能力对于工程师评估新问题并快速实施解决方案至关重要。解决工程问题的技能首先在学校接受教育，通常通过笔试进行评估。然而，在考试中取得高分并不代表在现实世界的工程问题中有足够的解决问题的能力。在真实的世界中，如果没有足够的解决问题的技能，就可能导致代价高昂的后果。因此，评价和加强工科学生在实际问题中的问题解决能力势在必行。随着技术的快速进步，虚拟现实（VR）和眼动跟踪的可用性促进了工程问题解决的研究。VR创造的沉浸式环境使学生能够更好地理解和解决现实世界的工程问题。另一方面，眼动追踪可以研究信息处理过程中的基本认知过程。将VR仿真与数据驱动的眼动建模相结合，以评估和提高工程问题解决能力至关重要。在本文中，我们集成了传感技术（即，眼动跟踪）和虚拟现实（VR）来模拟制造系统中的问题解决。一种新的数据驱动模型，集成了信号检测理论（SDT）与冲突和错误（C&E）的量化工程问题解决技能。首先，我们在VR游戏环境中模拟制造系统。学生们被赋予一个组装问题，以生产满足VR制造系统中某些特定要求的汽车玩具，同时在整个组装过程中收集眼动跟踪数据。其次，眼动追踪数据进行了分析与SDT模型来量化解决问题的技能。第三，开发了联合SDT-C&E模型来分析眼动跟踪数据，并与SDT模型生成的结果进行基准测试。实验结果表明，SDT-C&E联合模型比SDT模型更能有效地量化工科学生的问题解决能力。
Problem-solving is the process to achieve a goal when the solution path is uncertain. Recently, technological advancements have changed problems’ characteristics and their solutions in engineering fields. Strong problem-solving skills are essential to allow engineers to assess new problems and quickly implement solutions. Engineering problem-solving skills are first educated in schools and usually evaluated through written exams. However, high grades in exams do not represent sufficient problem-solving skills in real-world engineering problems. Decision making with insufficient problem-solving skills in real world may result in costly consequences. Therefore, it is imperative to evaluate and reinforce problem-solving skills of engineering students in real-world problems. With the rapid technological advancements, availability of virtual reality (VR) and eye-tracking facilitates the study of engineering problem-solving. The immersive environment created by VR enables students to better understand and solve real-world engineering problems. On the other hand, eye-tracking allows for studying fundamental cognitive processes during information processing. It is critical to integrate VR simulation with data-driven modeling of eye movements to evaluate and enhance engineering problem-solving skills. In this paper, we integrate sensing technology (i.e., eye-tracking) and virtual reality (VR) to model problem-solving in manufacturing systems. A novel data-driven model that integrates signal detection theory (SDT) with Conflict & Error (C&E) is developed to quantify engineering problem-solving skills. First, we simulate a manufacturing system in a VR game environment. Students are given an assembly problem to produce a car toy that satisfies some particular requirements in the VR manufacturing system while eye-tracking data are collected throughout the assembly process. Second, eye-tracking data are analyzed with a SDT model to quantify problem-solving skills. Third, a joint SDT-C&E model is developed to analyze eye-tracking data and benchmark with results generated from the SDT model. Experimental results show that the joint SDT-C&E model is more effective to quantify problem-solving skills of engineering students than the SDT model.
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DOI：
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