Fábio Medeiros da Silva Coelho

Researcher

Centro de Estudos de Gestão do Instituto Superior Técnico

ORCID CIÊNCIA VITAE ResearcherID Scopus

Keywords: Industry 4.0 | Logistics | Operations Research

Publications

In-House Logistics Operations Enhancement in the Automobile Industry Using Simulation

Springer Proceedings in Mathematics and Statistics | 2021

R. Macedo

F. Coelho

S. Relvas

A.P. Barbosa-Povoa

Towards an Integrated Decision-Support Framework for the New Generation of Manufacturing Systems

Springer Proceedings in Mathematics and Statistics | 2021

M. Vieira

F. Coelho

C. Da Silva

B. Mota

J. Guapo

R. Macedo

B. Gonçalves

S. Moniz

T. Pinto-Varela

A. Carvalho

S. Relvas

A.P. Barbosa-Povoa

Simulation-based decision support tool for in-house logistics: the basis for a digital twin

Computers and Industrial Engineering | 2021

F. Coelho

S. Relvas

A.P. Barbosa-Povoa

Simulation of an order picking system in a manufacturing supermarket using collaborative robots

Proceedings - European Council for Modelling and Simulation, ECMS | 2018

Fábio Coelho

S. Relvas

A.P. Barbosa-Póvoa

Statistical Survey on Inspection, Diagnosis, and Repair of Architectural Concrete Surfaces

Journal of Performance of Constructed Facilities | 2017

Cátia Da Silva

Fábio Coelho

Jorge De Brito

José Silvestre

Clara Pereira

C.D. Silva

F. Coelho

et Al.

Research Groups

OpLog – Operations, Logistics and Supply Chain Management

OpLog branch of CEGIST conducts multidisciplinary research driven by the challenges faced in industry and services organizations regarding the management of their operations, logistics and overall supply chain.

Projects

DM4 MANUFACTURING PROJECT

The main objective of the DM4Manufacturing project is the integrated development of advanced robotics with decision making methodologies to maximize the productivity of the factories of the future. Robots will be able to collaborate with humans in a shared workspace in the shop-floor, creating a co-working partnership, and will receive manufacturing orders in a completely flexible manufacturing scenario.