2026-05-31T01:57:53Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/90182024-04-23T00:05:24Zcom_10259_5501com_10259_5086com_10259_2604col_10259_5502

Islam, Syed Osama Bin Lughmani, Waqas Akbar Qureshi, Waqar Shahid Khalid, Azfar Mariscal Saldaña, Miguel Ángel García Herrero, Susana 2024-04-22T11:25:59Z 2024-04-22T11:25:59Z 2019-12 1687-8140 http://hdl.handle.net/10259/9018 10.1177/1687814019897228 1687-8140 Human workers are envisioned to work alongside robots and other intelligent factory modules, and fulfill supervision tasks in future smart factories. Technological developments, during the last few years, in the field of smart factory automation have introduced the concept of cyber-physical systems, which further expanded to cyber-physical production systems. In this context, the role of collaborative robots is significant and depends largely on the advanced capabilities of collision detection, impedance control, and learning new tasks based on artificial intelligence. The system components, collaborative robots, and humans need to communicate for collective decision-making. This requires processing of shared information keeping in consideration the available knowledge, reasoning, and flexible systems that are resilient to the real-time dynamic changes on the industry floor as well as within the communication and computer network infrastructure. This article presents an ontology-based approach to solve industrial scenarios for safety applications in cyber-physical production systems. A case study of an industrial scenario is presented to validate the approach in which visual cues are used to detect and react to dynamic changes in real time. Multiple scenarios are tested for simultaneous detection and prioritization to enhance the learning surface of the intelligent production system with the goal to automate safety-based decisions. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been funded by the project “IMPACTO DE LA INDUSTRIA 4.0 EN LA PREVENCIÓN DE RIESGOS LABORALES. SENSIBILIZACIÓN EN LA INDUSTRIA DE CASTILLA Y LEÓN,” with the reference INVESTUN/18/BU/0005 and supported by funds from Consejeria de Empleo—Junta de Castilla y León. eng SAGE Publications Advances in Mechanical Engineering. 2019, V. 11, n. 12 https://doi.org/10.1177/1687814019897228 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Cyber-physical production system Human-robot collaboration Smart factory Social safety Collaborative robot Tecnología Technology Ingeniería mecánica Mechanical engineering Exploiting visual cues for safe and flexible cyber-physical production systems info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Advances in Mechanical Engineering 11 12