以大數據分析建立船殼退化狀況的預測模型

Translated title of the contribution: ESTABLISHING A PREDICTION MODEL OF HULL DEGRADATION USING BIG DATA ANALYSIS

H. J. Shaw, J. R. Chang

Research output: Contribution to journalArticlepeer-review

Abstract

The study aims to analyze six vessels by statistical tools and find the relationship of main engine mass flow rate with relevant variables. According to the model of fitting fuel consumption, we compare to predicted values and real values, and look for the time points of the hull deterioration and infer the maintenance period. It makes that people can notice the hull status and improve the energy efficiency in the voyage. Thus, this model not only reduces the impact on shipping but considers the fuel cost. In the same ship, segments with similar voyages are grouped into one group for modeling. The shipping variables can be transformed by principal component analysis and fitted predicted model by the regression with auto-regressive integrated moving average error. In similar voyages, we predict the mass flow rate for other voyages and compute the mean absolute percentage error in the real values of the same voyage. It detects whether the hull is degraded, and the maintenance is useful or not. As a result, we can find the necessary maintenance from the monitoring charts. Besides, we can give suggestions for the maintenance period.

Translated title of the contributionESTABLISHING A PREDICTION MODEL OF HULL DEGRADATION USING BIG DATA ANALYSIS
Original languageChinese (Traditional)
Pages (from-to)67-75
Number of pages9
JournalJournal of Taiwan Society of Naval Architects and Marine Engineers
Volume40
Issue number2
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Mechanical Engineering

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