在一项针对经验丰富工人的案例研究中，评估增强现实数字工作说明与纸质文档在手动、特定对象维修任务中的表现
Evaluating Digital Work Instructions with Augmented Reality versus Paper-based Documents for Manual, Object-Specific Repair Tasks in a Case Study with Experienced Workers
AI总结：
本文针对涡轮叶片特定对象维修任务，提出结合数字工作说明与增强现实的认知辅助系统，并通过十名经验丰富金属工人的对比实验，证明其相较纸质流程可提速21%、降低26%主观负荷。
摘要：
维护、维修和大修行业中的手动维修任务需要经验和特定对象信息。如今，许多此类维修任务仍使用低效的纸质文档执行和记录。认知辅助系统有潜力通过以数字方式提供所有所需信息来降低成本、错误和心理负荷。在本案例研究中，我们提出了一种用于涡轮叶片特定对象维修任务的辅助系统。该辅助系统提供数字工作说明，并使用增强现实显示空间信息。在一项用户研究中，十名经验丰富的金属工人执行一项熟悉的维修任务，我们将新辅助系统的任务完成时间、主观工作负荷和系统可用性与其既有的纸质工作流程进行比较。所有参与者均表示，相比纸质文档，他们更偏好该辅助系统。研究结果表明，使用该辅助系统，手动维修任务的完成速度可提高21%，感知工作负荷降低26%。
英文摘要：
Manual repair tasks in the industry of maintenance, repair, and overhaul require experience and object-specific information. Today, many of these repair tasks are still performed and documented with inefficient paper documents. Cognitive assistance systems have the potential to reduce costs, errors, and mental workload by providing all required information digitally. In this case study, we present an assistance system for object-specific repair tasks for turbine blades. The assistance system provides digital work instructions and uses augmented reality to display spatial information. In a user study with ten experienced metalworkers performing a familiar repair task, we compare time to task completion, subjective workload, and system usability of the new assistance system to their established paper-based workflow. All participants stated that they preferred the assistance system over the paper documents. The results of the study show that the manual repair task can be completed 21 % faster and with a 26 % lower perceived workload using the assistance system.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
