scholarly journals Switchable Glass Enabled Contextualization for a Cyber-Physical Safe and Interactive Spatial Augmented Reality PCBA Manufacturing Inspection System

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4286
Author(s):  
Joel Murithi Runji ◽  
Chyi-Yeu Lin

Augmented reality (AR) has been demonstrated to improve efficiency by up to thrice the level of traditional methods. Specifically, the adoption of visual AR is performed widely using handheld and head-mount technologies. Despite spatial augmented reality (SAR) addressing several shortcomings of wearable AR, its potential is yet to be fully explored. To date, it enhances the cooperation of users with its wide field of view and supports hands-free mobile operation, yet it has remained a challenge to provide references without relying on restrictive static empty surfaces of the same object or nearby objects for projection. Towards this end, we propose a novel approach that contextualizes projected references in real-time and on demand, onto and through the surface across a wireless network. To demonstrate the effectiveness of the approach, we apply the method to the safe inspection of printed circuit board assembly (PCBA) wirelessly networked to a remote automatic optical inspection (AOI) system. A defect detected and localized by the AOI system is wirelessly remitted to the proposed remote inspection system for prompt guidance to the inspector by augmenting a rectangular bracket and a reference image. The rectangular bracket transmitted through the switchable glass aids defect localization over the PCBA, whereas the image is projected over the opaque cells of the switchable glass to provide reference to a user. The developed system is evaluated in a user study for its robustness, precision and performance. Results indicate that the resulting contextualization from variability in occlusion levels not only positively affect inspection performance but also supersedes the state of the art in user preference. Furthermore, it supports a variety of complex visualization needs including varied sizes, contrast, online or offline tracking, with a simple robust integration requiring no additional calibration for registration.

1984 ◽  
Vol 40 ◽  
Author(s):  
Donald S. Stone ◽  
Thomas R. Homa ◽  
Che-Yu Li

AbstractGrain boundary cavity growth in solder joints during thermal fatigue is analyzed. The stress cycle profile is estimated based on a geometrically simplified model of a ceramic chip carrier - printed circuit board assembly and a state variable equation for plastic flow in the solder.


2021 ◽  
Author(s):  
Haopeng Hu ◽  
Xiansheng Yang ◽  
Yunjiang Lou

Abstract Increasing demand for higher production flexibility and smaller production batch size pushes the development of manufacturing expertise towards robotic solutions with fast setup and reprogram capability. Aiming to facilitate assembly lines with robots, the learning from demonstration (LfD) paradigm has attracted attention. A robot LfD framework designed for skillful small parts assembly applications is developed, which takes position, orientation and wrench demonstration data into consideration while utilizes impedance control to deal with the motion error. In view of constraints in industrial assembly applications, we propose a robot LfD framework where policy learning is carried out with separated assembly demonstration data to avoid potential under-fitting problem. With the proposed assembly policies, reference orientation and wrench trajectories are generated as well as coupled with the position data to boost their generalization and robust performance. Effectiveness of the proposed LfD framework is validated by a printed circuit board assembly experiment with a 7-DOF torque-controlled robot.


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