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在基于增强现实的制造工作流程中使用人工智能辅助学习技术。

Using Artificial Intelligence Assisted Learning Technology on Augmented Reality-Based Manufacture Workflow.

作者信息

Li Mingchao, Chen Yuqiang

机构信息

School of Artificial Intelligence, Dongguan Polytechnic, Dongguan, China.

出版信息

Front Psychol. 2022 Jun 29;13:859324. doi: 10.3389/fpsyg.2022.859324. eCollection 2022.

Abstract

The manufacturing process is defined by the synchronous matching and mutual support of the event logic and the task context, so that the work task can be completed perfectly, by executing each step of the manufacturing process. However, during the manufacturing process of the traditional production environment, on-site personnel are often faced with the situation that on-site advice is required, due to a lack of experience or knowledge. Therefore, the function of the manufacturing process should be more closely connected with the workers and tasks. To improve the manufacturing efficiency and reduce the error rate, this research proposes a set of manufacturing work knowledge frameworks, to integrate the intelligent assisted learning system into the manufacturing process. Through Augmented Reality (AR) technology, object recognition technology is used to identify the components within the line of sight, and the assembly steps are presented visually. During the manufacturing process, the system can still feedback to the user in animation, so as to achieve the function equivalent to on-the-spot guidance and assistance when a particular problem is solved by a specialist. Research experiments show that the operation of this intelligent assisted learning interface can more quickly recognize how the manufacturing process works and can solve problems, which greatly resolves the issue of personnel with insufficient experience and knowledge.

摘要

制造过程由事件逻辑与任务上下文的同步匹配和相互支持来定义,以便通过执行制造过程的每个步骤来完美完成工作任务。然而,在传统生产环境的制造过程中,由于缺乏经验或知识,现场人员经常面临需要现场指导的情况。因此,制造过程的功能应与工人和任务更紧密地联系起来。为了提高制造效率并降低错误率,本研究提出了一套制造工作知识框架,将智能辅助学习系统集成到制造过程中。通过增强现实(AR)技术,利用目标识别技术识别视线范围内的部件,并直观呈现装配步骤。在制造过程中,系统仍能以动画形式向用户反馈,从而在专家解决特定问题时实现等同于现场指导和协助的功能。研究实验表明,这种智能辅助学习界面的操作能够更快地识别制造过程的工作方式并解决问题,极大地解决了经验和知识不足人员的问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32c9/9278276/d7b1277faf95/fpsyg-13-859324-g0001.jpg

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