Manufacturing e-quality through integrated web-enabled computer vision and robotics

Chiou, Richard; Mookiah, Prathaban; Kwon, Yongjin

doi:10.1007/s00170-008-1747-3

Cited by 15 publications

(10 citation statements)

References 17 publications

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“…So, the use of robots contributes to meet the demanding quality requirements (Jefferson et al, 2013) on several segments of industry. Technologies such as vision systems help robot accuracy on different industrial processes (Chiou et al, 2009). The application of sensors and IoT technologies are allowing to perform machining processes with robotic manipulators (Barbosa et al, 2019; Cordes et al, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

Barbosa

Silva

2020

Concurrent Engineering

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This paper lays emphasis on a proposal of a tailor-made roadmap that manages the knowledge related to automation skills to be applied during the concurrent engineering phase. The approach of this Research and Development (R&D) roadmap is a particular guideline in a structured form that uses the concepts of Plan-Do–Check–Act (PDCA) method integrated to other quality tools and know-how in robotization, for management of this specific knowledge. This research work aims to guide the staff (project managers, engineers and technicians) who work multidisciplinary in concurrent engineering environment about the robot’s implementation steps and significant tips related to the deployment phases that can be beneficial when this proposed roadmap is applied. Also, it was developed to assist the robot’s installation and their validation on shop floor, aiming the best class of industrial processes regarding the automation. The main contribution and novelty of this paper is to propose a R&D roadmap that drives and assists the multidisciplinary work teams since the identification of robotization opportunities till the assurance of quality requirements established for the concerned process, in addition to a continuous improvement program to carry it on. Besides that, this work provides a high relevance in terms of knowledge management related to robotization expertise, spread of practical skills in concurrent engineering context and an unprecedented innovative contribution at science frontier.

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Section: Literature Reviewmentioning

confidence: 99%

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

Barbosa

Silva

2020

Concurrent Engineering

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“…Recent literature on the topic suggests that CBIR technology has reached a level of maturity that could be effectively applied to a variety of real‐world problems. Nevertheless, the practical application of systems using CBIR methods is limited to a few domains, such as law enforcement (Chung, Wang, & Chen, ; Jain, Lee, Jin, & Gregg, ; Klare, Li, & Jain, ; Shah, Javed, & Shafique, ) and manufacturing (Banerjee & Zetu, ; Chiou, Mookiah, & Kwon, ; Kerr, Pengilley, & Garwood, ; Lu, Li, & Yu, ). This is an unfortunate situation, given that there is a variety of professional domains for which image retrieval and use are critical components (Conniss, Ashford, & Graham, ; Eakins & Graham, ).…”

Section: Introductionmentioning

confidence: 99%

Content‐based image retrieval methods and professional image users

Beaudoin

2015

Asso for Info Science & Tech

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This article reports the findings of a qualitative research study that examined professional image users' knowledge of, and interest in using, content-based image retrieval (CBIR) systems in an attempt to clarify when and where CBIR methods might be applied. The research sought to determine the differences in the perceived usefulness of CBIR technologies among image user groups from several domains and explicate the reasons given regarding the utility of CBIR systems for their professional tasks. Twenty participants (archaeologists, architects, art historians, and artists), individuals who rely on images of cultural materials in the performance of their work, took part in the study. The findings of the study reveal that interest in CBIR methods varied among the different professional user communities. Individuals who showed an interest in these systems were primarily those concerned with the formal characteristics (i.e., color, shape, composition, and texture) of the images being sought. In contrast, those participants who expressed a strong interest in images of known items, images illustrating themes, and/or items from specific locations believe concept-based searches to be the most direct route. These image users did not see a practical application for CBIR systems in their current work routines.

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“…In addition to the 3D virtual environment, the I/O models of the PLC need to be developed properly to complete the simulation. Furthermore, the workflow to implement virtual commissioning in physical laboratories or shops is discussed [8][9] . This project demonstrates the result of simulation to evaluate the functionality of the virtual workcell.…”

Section: Simulation Softwarementioning

confidence: 99%

Modeling and Experimental Verification of PLC Codes in a Robotics and Mechatronics Course

Chiou¹,

Kwon²,

Kizirian³

et al.

2011 ASEE Annual Conference &Amp; Exposition Proceedings

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Dr. Richard Chiou's background is in mechanical engineering with an emphasis on manufacturing. Dr. Chiou is currently an associate professor in the Goodwin School of Technology and Professional Studies at Drexel University. His areas of research include machining, mechatronics, and internet based robotics and automation. He has secured many research and education grants from the NSF, the SME Education Foundation, and industries. Yongjin (James) Kwon, Ajou University Robin Kizirian, Drexel University Robin Kizirian completed his M.S. degree in Computer Engineering at Drexel University in Philadelphia and his B.S. degree in Computer Engineering with a minor in Computer Science at the University of Hartford in Connecticut. He is currently serving as a research assistant at the Engineering Technology department at Drexel University. Robin has been involved in various projects funded by Pfizer, NASA,

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Manufacturing e-quality through integrated web-enabled computer vision and robotics

Cited by 15 publications

References 17 publications

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

R&D roadmap for process robotization driven to the digital transformation of the industry 4.0

Content‐based image retrieval methods and professional image users

Modeling and Experimental Verification of PLC Codes in a Robotics and Mechatronics Course

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