Assessing Project Progress Planning using Control Diagrams and Neural Network Prediction for Shipbuilding Projects in an Ecuadorian Shipyard

Gerardo Caceres

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 in accordance with the shipyard behaviour.

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