Evaluation of an Augmented Reality Instruction for a Complex Assembly Task

i-com ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 63-72
Author(s):  
Johannes Funk ◽  
Ludger Schmidt
Keyword(s):  
Augmented Reality ◽  
Knowledge Transfer ◽  
Manual Assembly ◽  
Complex Assembly ◽  
Assembly Task ◽  
Rail Vehicles ◽  
Instruction Type ◽  
Low Costs ◽  
Nasa Tlx ◽  
Assembly Tasks

Abstract This study compares the use of a marker-based AR instruction with a paper instruction commonly used in manual assembly. Hypotheses were tested as to whether the instruction type affects assembly time, number of errors, usability, and employee strain. Instead of student participants and artificial assembly tasks (e. g. Lego assemblies), the study was conducted with 16 trainees in a real workplace for the assembly of emergency door release handles in rail vehicles. Five assembly runs were performed. Assembly times and assembly errors were determined from recorded videos. Usability (SUS) and strain (NASA-TLX) were recorded with questionnaires. After a slower assembly at the beginning, the AR group assembled significantly faster in the fifth run. The comparable number of errors, usability and strain make marker-based AR applications interesting for knowledge transfer in manual assembly, especially due to the easy entrance and low costs.

scholarly journals Edge Computing Driven Scene-aware Intelligent Augmented Reality for Manual Assembly

2021 ◽  
Author(s):  
Mingyu Fu ◽  
Wei Fang ◽  
Shan Gao ◽  
Jianhao Hong ◽  
Yizhou Chen
Keyword(s):  
Augmented Reality ◽  
Cognitive Load ◽  
High Efficiency ◽  
Computing System ◽  
Edge Computing ◽  
Assembly Process ◽  
Manual Assembly ◽  
Worker Center ◽  
Assembly Operations ◽  
Assembly Tasks

Abstract Wearable augmented reality (AR) can superimpose virtual models or annotation on real scenes, and which can be utilized in assembly tasks and resulted in high-efficiency and error-avoided manual operations. Nevertheless, most of existing AR-aided assembly operations are based on the predefined visual instruction step-by-step, lacking scene-aware generation for the assembly assistance. To facilitate a friendly AR-aided assembly process, this paper proposed an Edge Computing driven Scene-aware Intelligent AR Assembly (EC-SIARA) system, and smart and worker-centered assistance is available to provide intuitive visual guidance with less cognitive load. In beginning, the connection between the wearable AR glasses and edge computing system is established, which can alleviate the computation burden for the resource-constraint wearable AR glasses, resulting in a high-efficiency deep learning module for scene awareness during the manual assembly process. And then, based on context understanding of the current assembly status, the corresponding augmented instructions can be triggered accordingly, avoiding the operator’s cognitive load to strictly follow the predefined procedure. Finally, quantitative and qualitative experiments are carried out to evaluate the EC-SIARA system, and experimental results show that the proposed method can realize a worker-center AR assembly process, which can improve the assembly efficiency and reduce the occurrence of assembly errors effectively.

Biomechanical Evaluation of Passive Back-Support Exoskeletons in a Precision Manual Assembly Task: “Expected” Effects on Trunk Muscle Activity, Perceived Exertion, and Task Performance

2020 ◽  
Vol 62 (3) ◽  
pp. 441-457 ◽  
Author(s):  
Saman Madinei ◽  
Mohammad Mehdi Alemi ◽  
Sunwook Kim ◽  
Divya Srinivasan ◽  
Maury A. Nussbaum
Keyword(s):  
Task Performance ◽  
Muscle Activity ◽  
Perceived Exertion ◽  
Trunk Muscle ◽  
Low Back ◽  
Manual Assembly ◽  
Physical Demands ◽  
Assembly Task ◽  
Assembly Tasks ◽  
And Task

Objective To assess the efficacy of two different passive back-support exoskeleton (BSE) designs, in terms of trunk muscle activity, perceived low-back exertion, and task performance. Background BSEs have the potential to be an effective intervention for reducing low-back physical demands, yet little is known about the impacts of different designs in work scenarios requiring varying degrees of symmetric and asymmetric trunk bending during manual assembly tasks. Method Eighteen participants (gender balanced) completed lab-based simulations of a precision manual assembly task using a “grooved pegboard.” This was done in 26 different conditions (20 unsupported; 6 supported, via a chair), which differed in vertical height, horizontal distance, and orientation. Results Using both BSEs reduced metrics of trunk muscle activity in many task conditions (≤47% reductions when using BackX™ and ≤24% reductions when using Laevo™). Such reductions, though, were more pronounced in the conditions closer to the mid-sagittal plane and differed between the two BSEs tested. Minimal effects on task completion times or ratings of perceived exertion were found for both BSEs. Conclusion Our findings suggest that using passive BSEs can be beneficial for quasi-static manual assembly tasks, yet their beneficial effects can be task specific and specific to BSE design approaches. Further work is needed, though, to better characterize this task specificity and to assess the generalizability of different BSE design approaches in terms of physical demands, perceived exertion, and task performance. Application These results can help guide the choice and application of passive BSE designs for diverse work scenarios involving nonneutral trunk postures.

scholarly journals Cognitive Interaction Analysis in Human–Robot Collaboration Using an Assembly Task

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1317
Author(s):  
Alejandro Chacón ◽  
Pere Ponsa ◽  
Cecilio Angulo
Keyword(s):  
Interaction Analysis ◽  
Mental Workload ◽  
Cognitive Task ◽  
Physical Work ◽  
Work Skills ◽  
Dexterous Manipulation ◽  
Assembly Task ◽  
Cognitive Interaction ◽  
Human Operators ◽  
Assembly Tasks

In human–robot collaborative assembly tasks, it is necessary to properly balance skills to maximize productivity. Human operators can contribute with their abilities in dexterous manipulation, reasoning and problem solving, but a bounded workload (cognitive, physical, and timing) should be assigned for the task. Collaborative robots can provide accurate, quick and precise physical work skills, but they have constrained cognitive interaction capacity and low dexterous ability. In this work, an experimental setup is introduced in the form of a laboratory case study in which the task performance of the human–robot team and the mental workload of the humans are analyzed for an assembly task. We demonstrate that an operator working on a main high-demanding cognitive task can also comply with a secondary task (assembly) mainly developed for a robot asking for some cognitive and dexterous human capacities producing a very low impact on the primary task. In this form, skills are well balanced, and the operator is satisfied with the working conditions.

Assembly Strategies for Parts with a Plane of Symmetry

Robotica ◽  
1991 ◽  
Vol 9 (2) ◽  
pp. 189-195 ◽  
Author(s):  
N. A. Aspragathos
Keyword(s):  
Large Class ◽  
Position Control ◽  
Hybrid Control ◽  
Robotic System ◽  
Torque Sensor ◽  
Complex Assembly ◽  
Assembly Tasks

SUMMARYThis paper describes the development of assembly strategies based on hybrid force/position control. The assembly strategies developed are confined to the large class of assembly tasks defined as a peg-in-the-hole assembly having a plane of symmetry passing through the axis of insertion.The basic idea to develop a robotic system for programmable assembly is presented. This system can currently operate controlled manipulators with minor modifications, i.e. if a force/torque sensor and proper software for hybrid control are provided.The principles of writing assembly strategies are analysed and examples of more complex assembly tasks than the classic round peg-in-the-hole are discussed in detail.

Development and Evaluation of a PCB‘s Manual Assembly system using Augmented Reality and Total Quality

2021 ◽  
Author(s):  
Rudieri Dietrich Bauer ◽  
Thiago Luiz Watambak ◽  
Salvador Sergi Agati ◽  
Marcelo da Silva Hounsell ◽  
Andre Tavares da Silva
Keyword(s):  
Augmented Reality ◽  
Assembly System ◽  
Total Quality ◽  
Manual Assembly
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