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Keywords = on-the-fly repairing

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22 pages, 688 KiB  
Article
On-the-Fly Repairing of Atomicity Violations in ARINC 653 Software
by Eu-teum Choi, Tae-hyung Kim, Yong-Kee Jun, Seongjin Lee and Mingyun Han
Appl. Sci. 2022, 12(4), 2014; https://doi.org/10.3390/app12042014 - 15 Feb 2022
Cited by 3 | Viewed by 2490
Abstract
Airborne health management systems prevent functional failure caused by errors or faults in airborne software. The on-the-fly repairing of atomicity violations in ARINC 653 concurrent software is critical for guaranteeing the correctness of software execution. This paper introduces RAV (Repairing Atomicity Violation), which [...] Read more.
Airborne health management systems prevent functional failure caused by errors or faults in airborne software. The on-the-fly repairing of atomicity violations in ARINC 653 concurrent software is critical for guaranteeing the correctness of software execution. This paper introduces RAV (Repairing Atomicity Violation), which efficiently treats atomicity violations. RAV diagnoses an error on the fly by utilizing the training results of software and treats to control access to the shared variable of the thread where the error has occurred. The evaluation of RAV measured the time overhead by applying methods found in previous works and RAV to five synthesis programs containing an atomicity violation. Full article
(This article belongs to the Special Issue Aircrafts Reliability and Health Management)
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16 pages, 7520 KiB  
Article
Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE
by Momchil Vasilev, Charles N. MacLeod, Charalampos Loukas, Yashar Javadi, Randika K. W. Vithanage, David Lines, Ehsan Mohseni, Stephen Gareth Pierce and Anthony Gachagan
Sensors 2021, 21(15), 5077; https://doi.org/10.3390/s21155077 - 27 Jul 2021
Cited by 34 | Viewed by 9488
Abstract
The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing [...] Read more.
The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs. Full article
(This article belongs to the Special Issue Robotic Non-destructive Testing)
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