No abstract

3This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.In shipbuilding and offshore plant construction, pipe-stools of various types are installed. Moreover, these are many quantities but they must be installed in a successive manner. Due to these characteristics the pipe-stool installation processes easily tends to cause the schedule delays in the overall production processes. In order to reduce delay, the goal of this study is to predicts production's lead time before manufacturing. Through this predictions it's expected to reduce total production's lead time by improving it's process. First of all, we made MLR(Multiple Linear Regression) and PLSR(Partial Least Square Regression) model to predict pipe-spool's lead time and then compared predictability of MLR and PLSR model. If a explanatory variable is added, it will be possible to predict results precisely.

Production simulation technology is beneficial to solve the complicated and fluctuated problems in a shipyard. It takes too much time and effort to build simulation models in the field, though. This research proposes a feasible method to reduce the difficulties related to simulation modeling for the factory or shop capacity analysis. In addition, a proposed neutral data format for production information is efficient to manage information acquisition for simulation modeling automation. A panel block shop model is contributed to comparison between the conventional technique and the automated one. The automation technique is highly recommended to run a rapid simulation in the shipyard problem.

Since the global financial crisis of 2008, the global shipbuilding industry has changed considerably and placed major Korean shipbuilding companies (mostly common carrier builders) in a precarious position. Current competitiveness in the global shipbuilding industry has been attracted by low labor costs in China. The Korean shipbuilding industry, with heavy industry as the central figure, is attempting to increase its share of offshore plant construction to develop deep-sea resources. This highlights the most outdated part of offshore plant in Korea, the development technology, which includes front-end engineering development and deep-water floaters, unlike in more advanced companies in the United States, where development technology has advanced rapidly. This has prompted the Korean government to invest most of its R&D funds in the areas of product and equipment development. However, mega shipbuilders such as Samsung, Hyundai, and Daewoo have incurred considerable losses at construction stages because of major delays in production. By contrast, international engineering companies have supported development engineering. The considerable financial losses incurred by mega shipbuilders are believed to be caused by a lack of quality management with respect to the massive production quantities and complexities involved in outfitting topside structures. This study investigates a strategy to advance production management specialized for the offshore plant business and describes a robust and sustainable technical roadmap based on current information technologies (IT) and simulation-based management methods