Model-Based Computational Shipyard Dynamics and Its Applications

Abstract

A ship production system can be represented by various production factors and production management indicators. To manage such a system efficiently, a theory is required to analyze and predict its behavior. The theory should be able to fully express the relationships between production factors and production management indicators. For this purpose, computational shipyard dynamics was proposed by Kim et al. in the Journal of Ship Production and Design (2018). This methodology includes input variables, output variables, and key performance indicator (KPI) functionals, implemented as a simulation model. In this study, a rigorous approach to realize a model of a complex ship production system is presented by embodying previous research. A model-based ship production system theory is defined, which consists of production factors, production management indicators, and the relationships between them, called the simulation-based KPI functionals. The production factors are defined using a six-factor model, and the production management indicators are defined using KPIs that are already used in shipyards so that they are quantitatively measurable. To verify the proposed theory, it was applied to fabrication shop, panel block assembly line, and ship block logistics simulation cases, which are examples that are similar to the job shop, flow shop, and project shop cases, respectively. Introduction 1.1. Background Approximately 40% of shipyards worldwide have been closed over the last decade. The reasons for this are the economic recession and intense competition. Inefficiency in the production system is not a big problem in the marine shipping industry and offshore-plant-related industries when these industries are booming with high demands and sufficient funding. However, when crises approach, unrevealed problems emerge, and low productivity leads to catastrophes at shipyards.