Cátia Alves

Dr. Cátia Alves

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 June 2015 in International Journal of Technology and Design Education
Verified
Journal Article
Closed access
PDF file
GPGoran Putnik
Goran Putnik
ECEric Costa
Eric Costa
CACátia Alves
Cátia Alves
Helio CastroHelio Castro
Helio Castro
Leonilde VarelaLeonilde Varela
Leonilde Varela
VSVaibhav Shah
Vaibhav Shah

1 January 2013 in Procedia CIRP
Verified
Journal Article
Open access
LFLuís Ferreira
Luís Ferreira
GPGoran Putnik
Goran Putnik
Maria Manuela Cruz-CunhaMaria Manuela Cruz-Cunha
Maria Manuela Cruz-Cunha
ZPZlata Putnik
Zlata Putnik
Helio CastroHelio Castro
Helio Castro
Leonilde VarelaLeonilde Varela
Leonilde Varela

16 January 2022 in International Journal for Quality Research
Verified
Journal Article
Closed access
GMGustavo Marchisotti
Gustavo Marchisotti
JFJose Rodrigues Filho
Jose Rodrigues Filho
SFSérgio Luiz Braga França
Sérgio Luiz Braga França
RTRoberto Toledo
Roberto Toledo
Helio CastroHelio Castro
Helio Castro
GPGoran Putnik
Goran Putnik

1 January 2018 in Procedia CIRP
Verified
Journal Article
Open access
LFLuís Ferreira
Luís Ferreira
GPGoran Putnik
Goran Putnik
NLNuno Lopes
Nuno Lopes
WGWiley Garcia
Wiley Garcia
MCMaria M. Cruz-Cunha
Maria M. Cruz-Cunha
ZPZlata Putnik
Zlata Putnik

1 January 2013 in Procedia CIRP
Verified
Journal Article
Open access
Helio CastroHelio Castro
Helio Castro
GPGoran Putnik
Goran Putnik
Maria Manuela Cruz-CunhaMaria Manuela Cruz-Cunha
Maria Manuela Cruz-Cunha
LFLuís Ferreira
Luís Ferreira
VSVaibhav Shah
Vaibhav Shah
CACátia Alves
Cátia Alves

1 January 2021 in FME Transactions
Verified
Journal Article
Open access
PDF file
CACátia Alves
Cátia Alves
GPGoran Putnik
Goran Putnik
Leonilde VarelaLeonilde Varela
Leonilde Varela
Production scheduling can be affected by many disturbances in the manufacturing system, and consequently, the feasible schedules previously defined became obsolete. Emerging of new technologies associated with Industry 4.0, such as Cyber-Physical Production Systems, as a paradigm of implementation of control and support in decision making, should embed the capacity to simulate different environment scenarios based on the data collected by the manufacturing systems. This paper presents the evaluation of environment dynamics effect on production scheduling, considering three scheduling models and three environment scenarios, through a case study. Results show that environment dynamics affect production schedules, and a very strong or strong positive correlation between environment dynamics scenarios and total completion time with delay, over three scheduling paradigms. Based on these results, the requirement for mandatory inclusion of a module for different environment dynamics scenarios generation and the corresponded simulations, of a Cyber-Physical Production Systems architecture, is confirmed.