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Anis Ben Said
ResearcherPublications, citations & collaboration network
Anis Ben Said is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 8 works, 74 citations, an h-index of 4 and an i10-index of 2.
8
Works
74
Citations
4
h-index
2
i10-index
IDs:OpenAlex
How has Anis Ben Said's publication output changed over time?
ScholarIQpublication output · 2014–2016
Output grew400% over the shown period — from 1 works in 2014 to 5 in 2016.
1
2
5
201420152016
What are the most-cited papers on Anis Ben Said?
ScholarIQmost cited works
Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.
Asma Abu-Samah, Muhammad Kashif Shahzad, Éric Zamaï, Anis Ben Said
IFAC-PapersOnLine. 201541 CitationsOPEN ACCESS
Experts’ knowledge renewal and maintenance actions effectiveness in high-mix low-volume industries, using Bayesian approach
Anis Ben Said, Muhammad Kashif Shahzad, Éric Zamaï, Stéphane Hubac, Michel Tollenaere
Cognition Technology & Work. 201517 Citations
Towards proactive maintenance actions scheduling in the Semiconductor Industry (SI) using Bayesian approach
Anis Ben Said, Muhammad-Kashif Shahzad, Éric Zamaï, Stéphane Hubac, Michel Tollenaere
IFAC-PapersOnLine. 20169 CitationsOPEN ACCESS
A Bayesian network based approach to improve the effectiveness of maintenance actions in Semiconductor Industry
Anis Ben Said, Muhammad Kashif Shahzad, Éric Zamaï, Stéphane Hubac, Michel Tollenaere
PHM Society European Conference. 20146 CitationsOPEN ACCESS
Towards quantified measures of Agility for Production Line Information Systems (PLIS)
M.K. Shahzad, Camilo Cruz Jimenez, Anis Ben Said, Michel Tollenaere
IFAC-PapersOnLine. 20161 CitationsOPEN ACCESS
Related on ScholarIQ
Centre National de la Recherche Scientifique
Institution
Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.
Paper
Experts’ knowledge renewal and maintenance actions effectiveness in high-mix low-volume industries, using Bayesian approach
Paper
Towards proactive maintenance actions scheduling in the Semiconductor Industry (SI) using Bayesian approach
Paper
A Bayesian network based approach to improve the effectiveness of maintenance actions in Semiconductor Industry
Paper
Towards quantified measures of Agility for Production Line Information Systems (PLIS)
Paper