十种建筑机器人的安全、质量、进度和成本影响。

Construction robotics Pub Date : 2022-01-01 Epub Date: 2022-06-27 DOI:10.1007/s41693-022-00072-5
Cynthia Brosque, Martin Fischer
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引用次数: 10

摘要

机器人在结构化制造环境中提高了生产率、质量和安全性,同时降低了生产成本。在过去的十年里,计算和传感技术的进步已经开始使机器人能够在建筑等非结构化环境中工作。目标:考虑到这一新的现实,本研究旨在量化现有建筑机器人的影响。方法:本研究评估了10个现场施工机器人对来自欧洲、亚洲、南美和美国的11家承包商的12个建筑项目的安全、质量、进度和成本影响。结果:机器人显示出将重复性现场工作减少25%至90%的潜力,并将危险任务的时间平均减少72%。平均而言,精度提高了55%,返工减少了50%以上。机器人平均减少作业时间2.3次,中位数为1.4次。成本降低了13%,其中6个案例降低了成本,但4个案例增加了总成本。对比结果还强调了在哪些项目条件下(产品、组织和过程),机器人比传统方法表现得更好。结论:即使在世界范围内机器人部署的相对早期阶段,对十个例子的一致评估表明,该技术在一系列机器人类型,移动性,自主性,规模,商业模式和位置方面已经具有很大的前景。未来的工作将利用相同的比较方法扩大机器人案例研究的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Safety, quality, schedule, and cost impacts of ten construction robots.

Safety, quality, schedule, and cost impacts of ten construction robots.

Safety, quality, schedule, and cost impacts of ten construction robots.

Safety, quality, schedule, and cost impacts of ten construction robots.

Introduction: Robots have increased productivity, quality, and safety in structured manufacturing environments while lowering production costs. In the last decade, advances in computing and sensing have started to enable robots in unstructured environments such as construction.

Objectives: Given this new reality, this research aims to quantify the impacts of existing construction robots.

Methods: This study evaluates the Safety, Quality, Schedule, and Cost impacts of ten on-site construction robots for 12 construction projects spanning 11 contractors from Europe, Asia, South America, and the United States.

Results: The robots showed the potential to reduce repetitive site work between 25 and 90% and reduce time spent on hazardous tasks by 72% on average. On average, accuracy was improved by 55%, and rework was reduced by over 50%. Robots reduced the schedule on average 2.3 times with a median of 1.4x. The cost was reduced by 13%, with six cases that reduced it but four that increased the total costs. The comparative results also highlight under what project conditions (Product, Organization, and Process) could the robot perform better than the traditional method.

Conclusion: Even at this relatively early stage of robot deployment worldwide, the consistent evaluation of ten examples showed how promising the technology already is for a range of robot types, mobility, autonomy, scale, business models, and locations. Future work will expand the number of robot case studies utilizing the same comparison method.

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