Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Tiago Coito"'
Autor:
Tiago Coito, Paulo Faria, Miguel S. E. Martins, Bernardo Firme, Susana M. Vieira, João Figueiredo, João M. C. Sousa
Publikováno v:
Automation, Vol 3, Iss 1, Pp 153-175 (2022)
In the last few decades, there has been a growing necessity for systems that handle market changes and personalized customer needs with near mass production efficiency, defined as the new mass customization paradigm. The Industry 5.0 vision further e
Externí odkaz:
https://doaj.org/article/87555af405124393b2a73f14ed5aa001
Autor:
Tiago Coito, Bernardo Firme, Miguel S. E. Martins, Susana M. Vieira, João Figueiredo, João M. C. Sousa
Publikováno v:
Automation, Vol 2, Iss 2, Pp 62-82 (2021)
The simultaneous integration of information from sensors with business data and how to acquire valuable information can be challenging. This paper proposes the simultaneous integration of information from sensors and business data. The proposal is su
Externí odkaz:
https://doaj.org/article/7edbdc4783c2418c864ed02b76d5cc66
Autor:
Miguel S. E. Martins, Joaquim L. Viegas, Tiago Coito, Bernardo Firme, Andrea Costigliola, João Figueiredo, Susana M. Vieira, João M. C. Sousa
Publikováno v:
Journal of Heuristics. 29:177-206
This paper proposes an algorithm for the effective scheduling of analytical chemistry tests in the context of quality control for pharmaceutical manufacturing. The problem is formulated as an extension of a dual resource constrained flexible job shop
Autor:
Tiago Coito, Miguel S.E. Martins, Bernardo Firme, João Figueiredo, Susana M. Vieira, João M.C. Sousa
Publikováno v:
Journal of Manufacturing Systems. 62:270-285
Autor:
Susana M. Vieira, João Figueiredo, Tiago Coito, Bernardo M. Firme, João M. C. Sousa, Miguel S. E. Martins
Publikováno v:
Automation, Vol 2, Iss 4, Pp 62-82 (2021)
Automation
Volume 2
Issue 2
Pages 4-82
Automation
Volume 2
Issue 2
Pages 4-82
The simultaneous integration of information from sensors with business data and how to acquire valuable information can be challenging. This paper proposes the simultaneous integration of information from sensors and business data. The proposal is su
Autor:
Miguel S. E. Martins, João M. C. Sousa, Joaquim L. Viegas, Bernardo M. Firme, Susana M. Vieira, João Figueiredo, Tiago Coito
Publikováno v:
IFAC-PapersOnLine. 53:10810-10815
This paper proposes using reinforcement learning to solve scheduling problems where two types of resources of limited availability must be allocated. The goal is to minimize the makespan of a dual-resource constrained flexible job shop scheduling pro
Autor:
Tiago Coito, Bernardo Firme, Miguel S.E. Martins, Andrea Costigliola, Rafael Lucas, João Figueiredo, Susana M. Vieira, João M.C. Sousa
Publikováno v:
Computers & Industrial Engineering. 171:108387
Autor:
Tiago Coito, João Figueiredo, Miguel S. E. Martins, Susana M. Vieira, João M. C. Sousa, Joaquim L. Viegas, Mariana M. Cunha
Publikováno v:
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Agência para a Sociedade do Conhecimento (UMIC)-FCT-Sociedade da Informação
instacron:RCAAP
Agência para a Sociedade do Conhecimento (UMIC)-FCT-Sociedade da Informação
instacron:RCAAP
As the industry continues to pursue the reduction of downtimes and increases in the efficiency of resource usage, data appears as a valuable business asset, empowering intelligent automation solutions. In order to deal with current challenges in acqu
Autor:
Miguel S. E. Martins, Mariana M. Cunha, Joaquim L. Viegas, João M. C. Sousa, Susana M. Vieira, João Figueiredo, Tiago Coito, Andrea Costigliola
Publikováno v:
IFAC-PapersOnLine. 52:1421-1426
This work presents a novel formulation for quality control laboratory scheduling considering both equipment and analysts as constraints. The problem is modelled as a dual-resource constrained flexible job shop problem. The formulation considers analy
Autor:
João Figueiredo, Susana M. Vieira, Miguel S. E. Martins, Tiago Coito, Bernardo M. Firme, Guilherme Lopes, Joaquim L. Viegas, João M. C. Sousa, Joao C. P. Reis
Publikováno v:
IJCNN
This paper proposes a flexible manufacturing system based on intelligent computational agents. A Multi-Agent System composed of 4 types of reactive agents was designed to control the operation of a real implementation in the Intelligent Automation La