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Author: Gerardo Mena Caceres

Affiliation: Project Management Office, MSc. Global Production Engineering & Management, Global Production Engineering & Management, AV 8ANO, Guayaquil, Ecuador

Keyword(s): Project Management, Data Analysis, Data Prediction, Planning.

Abstract: The planning and scheduling of new shipbuilding projects, as in other engineering disciplines require a certain degree of experience and knowledge in order to provide progress planning of feasible works to achieve the goals of the project and the managerial expectation. As is mentioned, although having experience is necessary; according to current technologies, the use of data analysis and the certainty that in the medium-term future artificial intelligence will be used in decision-making, it is necessary that not only manufacturing be according to the approaches of industry 4.0 but also, project management from its start-up phase to closure uses mechanisms for continuous improvement in a more successful way. This case study focuses on the data analysis of planned and executed projects to estimate acceptable percentages of periodic progress of projects using parameters of reliability engineering and neural network model from ISPP IBM software, in such a way that the planning can be i n accordance with the shipyard behaviour. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Caceres, G. (2020). Assessing Project Progress Planning using Control Diagrams and Neural Network Prediction for Shipbuilding Projects in an Ecuadorian Shipyard. In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL; ISBN 978-989-758-476-3, SciTePress, pages 60-68. DOI: 10.5220/0009993100600068

@conference{in4pl20,
author={Gerardo Mena Caceres.},
title={Assessing Project Progress Planning using Control Diagrams and Neural Network Prediction for Shipbuilding Projects in an Ecuadorian Shipyard},
booktitle={Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL},
year={2020},
pages={60-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009993100600068},
isbn={978-989-758-476-3},
}

TY - CONF

JO - Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL
TI - Assessing Project Progress Planning using Control Diagrams and Neural Network Prediction for Shipbuilding Projects in an Ecuadorian Shipyard
SN - 978-989-758-476-3
AU - Caceres, G.
PY - 2020
SP - 60
EP - 68
DO - 10.5220/0009993100600068
PB - SciTePress