해양플랜트 의장품 조달관리를 위한 배관 공정 리드타임 예측 모델에 관한 연구

A Study of Piping Leadtime Forecast in Offshore Plant’s Outfittings Procurement Management

  • 투고 : 2015.10.16
  • 심사 : 2016.01.11
  • 발행 : 2016.02.20


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.




  1. Im, J.S., 2012. Improvement for individual work order process in manufacturing piping spool of offshore facilities. Master's Thesis. University of Ulsan.
  2. Jang, Y.J., 2012. Utilizing Big-data’s Technology in Manufacturing Field. Journal of The Korean Institute of Communication Sciences, 29(11), pp.30-36.
  3. Jung, G.S., 2012. Presumed Influence Factors of Decision-Making of Mega-Projects. Audit and Inspection Research Institue, 19(1), pp.91-124.
  4. Kim, D.J., 2012. Models of local finance decisions using PLS regression analysis : cities and counties in Gyeongnam. Master's Thesis. Gyeongsang National University.
  5. Kim, H.J., 2010. A study on forecasting model of in semiconductor device fabrication. Master's Thesis. Korea University.
  6. Kim, J.S. & Shin, Y.T., 2014. Development Portable Pipe Spool Location-Confirm System Based UHF RFID. KIPS Transactions on Computer and Communication Systems, 3(10), pp.329-336.
  7. Yan, W., 2012. Automatic Generation of Assembly Sequence for the Planning of Outfitting Processes in Shipbuilding. Journal of Ship Production and Design, 28(2), pp.49-59.
  8. Ha, D.G., 2013. Soft sensor design on fractionation process for LNG plant using PLS and variable selection. Master's Thesis. Seoul National University.
  9. Kim, S.S., 2015. The Three Heavy Industries Operating Loss Sharply. Monthly Marintime Korea, 2015(6), pp.84-87.
  10. Lee, H.S., 2013. A case study on improvement of pipe outfitting production process using TOC. Master's Thesis. University of Ulsan.
  11. Lee, H.S. & Im, J.H., 2015. SPSS 22 Manual. 1st Ed. Jyphyuntae: Seoul.
  12. National Information Society Agency(NIA), 2015. 2015 global big data Casebook. National Information Society Agency: Korea.
  13. Okumoto Yasuhisa, 2012. Shipbuilding Technology & Production System. Translated by Kim, Y.S. GS-intervision: Seoul.
  14. Seong, H.G., 2014. A Proposal for Rowth of Offshore Plant Industries. Machinery Industry, 2014(9), pp.41-48.