Abstract
Various types of data are produced by the shipbuilding and offshore industry. As the number of ships and offshore structures that were built over time increased, an enormous amount of data, called big data, had to be handled. However, it is difficult to handle effectively such big data with the existing methodology for data storage and processing. Therefore, big data technology needs to be applied to the systems of shipyards, such as the product lifecycle management system. On the other hand, the construction of an offshore structure requires a lot of piping, and there are many materials as much as piping. For a shipyard that executes multiple projects at once, it is not easy to correlate so much piping material. A piping designer should check all materials based on his or her understanding of the design characteristics. However, depending on the maturity of the designer, it can be difficult to handle such large data manually; as a result, there can be errors in piping design. In this study, a big data framework applicable to the shipyard is proposed and used for the analysis. That is, the association analysis of piping materials of an offshore structure is performed based on the big data framework that can process a large amount of data to assist piping designers. As an application, after analyzing the material data for one offshore structure, the applicability of this study was evaluated through the results. We believe this study can help piping designers.
