ArticleJournal of intelligent manufacturing2023
Digital Twin and web services for robotic deburring in intelligent manufacturing.
Article in Journal of intelligent manufacturing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The trial behind it
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Who cites it
3 citing papers in PubMed.
- Digital Twin-Based Intelligent Monitoring System for Robotic Wiring Process.Sensors (Basel, Switzerland) · 2025Article
- Dual-self-learning co-evolutionary algorithm for energy-efficient flexible job shop scheduling problem with processing- transportation composite robots.Scientific reports · 2025Article
- Developing a virtual reality and AI-based framework for advanced digital manufacturing and nearshoring opportunities in Mexico.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of modern manufacturing requires key solutions to enhance the intelligence of manufacturing such as digitalization, real-time monitoring, or simulation techniques. For smart robotic manufacturing, the modern approach regarding robot programming and process planning aims for both high efficiency and energy-awareness. During the design and manufacturing stages, optimization becomes crucial and can be fulfilled by means of appropriate digital manufacturing tools. This paper presents the development of a Digital Twin for a robotic deburring workcell along with the process planning and robot programming. Considering a large size workpiece, a new robot programming solution was implemented, based on image processing to safely re-machine only areas where burrs could not be completely removed in the main deburring routine. The work also covers the development of a new web platform to remotely monitor the robotic workcell, to trigger alerts for unexpected events and to allow the control to authorized personnel enabled by the employment of robot web services following an architectural RESTful style which establishes a communication link to the robot virtual controller. The aim of this research is to integrate the Digital Twin with the innovative proposals of Industry 4.0, offering a project-based model of smart robotic manufacturing and experience concepts such as Cyber-Physical System, digitalization, data acquisition, continuous monitoring, and intelligent solutions in a novel approach. Furthermore, the work covers energy consumption strategies for energy-aware robotic manufacturing. Finally, the results of an energy-efficient motion planning along with signal-based scheduling optimization of the robotic deburring cell are discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.