오민재, 노명일, 박성우, 김성훈, “빅데이터 분석을 이용한 해양 구조물 배관 자재의 소요량 예측”, 대한조선학회 논문집, Vol. 55, No. 3, pp. 243-251, 2018.06.01
| Abstract | In the shipyard, a lot of data is generated, stored, and managed during design, construction, and operation phases to build ships and offshore structures. However, it is difficult to handle such big data efficiently using existing data-handling technologies. As the big data technology is developed, the ship and offshore industries start to focus on the existing big data to find valuable information from it. In this paper, the material requirement estimation method of offshore structure piping materials using big data analysis is proposed. A big data platform for the data analysis in the shipyard is introduced and it is applied to the analysis of material requirement estimation to solve the problems in piping design by a designer. The regression model is developed from the big data of piping materials and verified using the existing data. This analysis can help a piping designer to estimate the exact amount of material requirement and schedule the purchase time. |
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| Publication Date | 2018-06-01 |
| Role | Corresponding Author |
| Category | KCI |
오민재, 노명일, 박성우, 김성훈, “빅데이터 분석을 이용한 해양 구조물 배관 자재의 소요량 예측”, 대한조선학회 논문집, Vol. 55, No. 3, pp. 243-251, 2018.06.01