scholarly journals Using Augmented Reality to Cognitively Facilitate Product Assembly Process

10.5772/7129 ◽  
2010 ◽  
Author(s):  
Lei Hou ◽  
Xiangyu Wang
Author(s):  
Javier Gonzalez-Sanchez ◽  
Quincy Conley ◽  
Maria-Elena Chavez-Echeagaray ◽  
Robert K. Atkinson

The assembly process is often very complex and involved, collecting and managing a significant number of parts in an intricate manner. Because the quality of a product is in large part impacted by the assembly process, intuitive and carefully scaffolded guidelines can make a difference in how fast and how accurate an assembler can complete the assembly process. To this end, the authors propose an innovative system that leverages three current and emerging technologies; augmented reality (AR), cloud computing, and mobile devices, to create an Augmented Reality Product Assembly (ARPA) system. This paper describes the total framework for creating the ARPA system. They also discuss how the system leverages augmented reality visualizations for repurposing user-generated assembly guidelines by incorporating cloud-based computing. Although the authors situate ARPA’s use in an industrial setting, it is domain-independent and able to support a wide range of practical and educational applications.


2013 ◽  
Vol 581 ◽  
pp. 106-111 ◽  
Author(s):  
Jozef Novak-Marcincin ◽  
Jozef Barna ◽  
Jozef Torok

This article presents possibilities of precision assembling process by using special tools of the augmented reality (AR) and logical procedures from related areas such as a Computer Aided Design and Planning. These possibilities are implemented in the virtual assembling environment of AR, where engineers and designers can see important information about an exact position and orientation of the single assembly element that creates a part of the entire assembly structure. By means of this the application of AR allows costumer to see the motion process of single assembly item according to its trajectory and prevents the possible mistakes in the assembling processes.


2021 ◽  
Author(s):  
Mingyu Fu ◽  
Wei Fang ◽  
Shan Gao ◽  
Jianhao Hong ◽  
Yizhou Chen

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.


2021 ◽  
pp. 114-118
Author(s):  
Monika Töröková

Intensive research is currently underway into the concept of intelligent assembly, which integrates production processes, people, hardware and information using both real and virtual methods to achieve significant improvements in productivity, delivery time and combined market turnover. This paper describes the use of augmented reality in the assembly process at the workplace, which by integrating hardware and software equipment will enable an innovative assembly workplace for a manufacturing and development company. The assembly workplace will speed up and facilitate assembly and prevent the creation of failures and restrictions during assembly.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chengjun Chen ◽  
Zhongke Tian ◽  
Dongnian Li ◽  
Lieyong Pang ◽  
Tiannuo Wang ◽  
...  

Purpose This study aims to monitor and guide the assembly process. The operators need to change the assembly process according to the products’ specifications during manual assembly of mass customized production. Traditional information inquiry and display methods, such as manual lookup of assembly drawings or electronic manuals, are inefficient and error-prone. Design/methodology/approach This paper proposes a projection-based augmented reality system (PBARS) for assembly guidance and monitoring. The system includes a projection method based on viewpoint tracking, in which the position of the operator’s head is tracked and the projection images are changed correspondingly. The assembly monitoring phase applies a method for parts recognition. First, the pixel local binary pattern (PX-LBP) operator is achieved by merging the classical LBP operator with the pixel classification process. Afterward, the PX-LBP features of the depth images are extracted and the randomized decision forests classifier is used to get the pixel classification prediction image (PCPI). Parts recognition and assembly monitoring is performed by PCPI analysis. Findings The projection image changes with the viewpoint of the human body, hence the operators always perceive the three-dimensional guiding scene from different viewpoints, improving the human-computer interaction. Part recognition and assembly monitoring were achieved by comparing the PCPIs, in which missing and erroneous assembly can be detected online. Originality/value This paper designed the PBARS to monitor and guide the assembly process simultaneously, with potential applications in mass customized production. The parts recognition and assembly monitoring based on pixels classification provides a novel method for assembly monitoring.


Author(s):  
Bin Li ◽  
Qiong Dong ◽  
Jian Dong ◽  
Junfeng Wang ◽  
Wang Li ◽  
...  

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 496 ◽  
Author(s):  
Kamil Židek ◽  
Peter Lazorík ◽  
Ján Piteľ ◽  
Alexander Hošovský

Small series production with a high level of variability is not suitable for full automation. So, a manual assembly process must be used, which can be improved by cooperative robots and assisted by augmented reality devices. The assisted assembly process needs reliable object recognition implementation. Currently used technologies with markers do not work reliably with objects without distinctive texture, for example, screws, nuts, and washers (single colored parts). The methodology presented in the paper introduces a new approach to object detection using deep learning networks trained remotely by 3D virtual models. Remote web application generates training input datasets from virtual 3D models. This new approach was evaluated by two different neural network models (Faster RCNN Inception v2 with SSD, MobileNet V2 with SSD). The main advantage of this approach is the very fast preparation of the 2D sample training dataset from virtual 3D models. The whole process can run in Cloud. The experiments were conducted with standard parts (nuts, screws, washers) and the recognition precision achieved was comparable with training by real samples. The learned models were tested by two different embedded devices with an Android operating system: Virtual Reality (VR) glasses, Cardboard (Samsung S7), and Augmented Reality (AR) smart glasses (Epson Moverio M350). The recognition processing delays of the learned models running in embedded devices based on an ARM processor and standard x86 processing unit were also tested for performance comparison.


2012 ◽  
Vol 220-223 ◽  
pp. 513-516
Author(s):  
Hao Chen ◽  
Tian Yi Gao ◽  
Guang Yu Mu ◽  
Lan Lan Pan

The material tracking management system in the magnetic pump assembly process is studied to the machine shop and assembly shop of a pump company as an example. The system mainly includes production line management module, assembly process management module, material tracking management module and work in process (WIP) tracking management module. In this system, the workshop visual management, real-time status information collecting on-site, materials status monitoring, and product life cycle file establishing are implemented. The functions of product assembly processes tracking can be realized, so that the traceability of the parts, components, WIP and products in the process can be achieved. The system ensures the material supply timely and equipment operation normally in the production processes.


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