Complexity-based task allocation in human-robot collaborative assembly

自动化 机器人 软件部署 任务(项目管理) 工作量 机器人学 计算机科学 人工智能 人机交互 工程类 系统工程 软件工程 机械工程 操作系统
作者
Ali Ahmad Malik,Arne Bilberg
出处
期刊:Industrial Robot-an International Journal [Emerald (MCB UP)]
卷期号:46 (4): 471-480 被引量:126
标识
DOI:10.1108/ir-11-2018-0231
摘要

Purpose Over the past years, collaborative robots have been introduced as a new generation of industrial robotics working alongside humans to share the workload. These robots have the potential to enable human–robot collaboration (HRC) for flexible automation. However, the deployment of these robots in industrial environments, particularly in assembly, still comprises several challenges, of which one is skills-based tasks distribution between humans and robots. With ever-decreasing product life cycles and high-mix low volume production, the skills-based task distribution is to become a frequent activity. This paper aims to present a methodology for tasks distribution between human and robot in assembly work by complexity-based tasks classification. Design/methodology/approach The assessment method of assembly tasks is based on the physical features of the components and associated task description. The attributes that can influence assembly complexity for automation are presented. Physical experimentation with a collaborative robot and work with several industrial cases helped to formulate the presented method. Findings The method will differentiate the tasks with higher complexity of handling, mounting, human safety and part feeding from low-complexity tasks, thereby simplifying collaborative automation in HRC scenario. Such structured method for tasks distribution in HRC can significantly reduce deployment and changeover times. Originality/value Assembly attributes affecting HRC automation are identified. The methodology is presented for evaluating tasks for assigning to the robot and creating a work–load balance forming a human–robot work team. Finally, an assessment tool for simplified industrial deployment.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
at发布了新的文献求助10
刚刚
Orange应助优美访文采纳,获得10
4秒前
5秒前
完美世界应助fumingliang采纳,获得10
9秒前
Qing完成签到,获得积分10
10秒前
xxw完成签到,获得积分10
11秒前
12秒前
Orange应助寂寞的小土鸡采纳,获得10
14秒前
Akim应助shiwg采纳,获得10
16秒前
18秒前
yoyo完成签到 ,获得积分10
18秒前
标致绮露完成签到,获得积分10
19秒前
华仔应助22222采纳,获得10
24秒前
所所应助BBK采纳,获得10
24秒前
25秒前
25秒前
机智的访云完成签到,获得积分10
25秒前
充电宝应助at采纳,获得10
26秒前
Din发布了新的文献求助10
26秒前
27秒前
27秒前
科研通AI2S应助科研通管家采纳,获得10
27秒前
学术通zzz应助科研通管家采纳,获得30
27秒前
27秒前
Jasper应助科研通管家采纳,获得10
28秒前
28秒前
寒来暑往应助科研通管家采纳,获得10
28秒前
28秒前
Ava应助leihai采纳,获得10
29秒前
29秒前
30秒前
吴晨曦发布了新的文献求助10
30秒前
fumingliang发布了新的文献求助10
30秒前
勤奋的日记本完成签到,获得积分10
34秒前
芒狗发布了新的文献求助10
34秒前
善良秋尽完成签到 ,获得积分10
35秒前
37秒前
38秒前
42秒前
标致绮露发布了新的文献求助10
43秒前
高分求助中
Solution Manual for Strategic Compensation A Human Resource Management Approach 1200
Natural History of Mantodea 螳螂的自然史 1000
Glucuronolactone Market Outlook Report: Industry Size, Competition, Trends and Growth Opportunities by Region, YoY Forecasts from 2024 to 2031 800
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Zeitschrift für Orient-Archäologie 500
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 500
Synchrotron X-Ray Methods in Clay Science 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3340523
求助须知:如何正确求助?哪些是违规求助? 2968522
关于积分的说明 8634035
捐赠科研通 2648059
什么是DOI,文献DOI怎么找? 1449976
科研通“疑难数据库(出版商)”最低求助积分说明 671616
邀请新用户注册赠送积分活动 660663