Quantitative Evaluation of Draught Survey Through Correlation Test of Quarter Mean: A Case Study on a Coal Bulk Carrier

Denny Murdany Muchsin; Rahmad Setya Darmawan

doi:10.12962/j25481479.v8i4.19162

Quantitative Evaluation of Draught Survey Through Correlation Test of Quarter Mean: A Case Study on a Coal Bulk Carrier

Denny Murdany Muchsin, Rahmad Setya Darmawan

Abstract

Complicated draught survey activities both at the data collection stage and the calculation stage, especially at sea, make it difficult for surveyors to accurately inform coal cargo volumes. However, in practice, most coal bulk-carrier surveyors can provide precise information on coal cargo volumes between ports up to a difference of less than 0.5%. This difference is not enough to be used as the only parameter in supervising draught survey activities. More effective monitoring needs to be done so that data reliability can be validated. This study aims to propose a new method of off-site surveillance of draught survey activities through correlation tests with a case study on a bulk-carrier ship less than 10 years old in all coal shipments at one of coal-fired power plant during year 2021. The results of the study show that based on the correlation test of Pearson (2-tailed), Spearman (2-tailed), and Kendall (2-tailed), during coal shipments in 2021 both at loading ports and at unloading ports, the interpretation of the quarter-mean as independent variable is at least strongly correlated with both displacement and displacement corrected for density, while the correlation of quarter mean with both net displacement and constant is not significant (negligible).

Keywords

bulk carrier; coal; draught survey

Full Text:

PDF

References

“SNI 7986:2014 Penentuan kuantitas muatan kapal pada kegiatan transportasi mineral dan batubara,” Badan Standardisasi Nasional. 2014.

PLN Divisi Batubara, “Standard Operation Procedure (SOP) Penerimaan dan Pembongkaran Batubara PLTU Jawa Bali dan PLTU Luar Jawa Bali.” 2019.

R. Canımoğlu, U. Yıldırım, and G. M. İnegöl, “Analysis of Draught Survey Errors by Extended Fuzzy Analytic Hierarchy Process,” Journal of ETA Maritime Science, vol. 9, no. 1, 2021, doi: 10.4274/jems.2021.64872.

H. Li, Y. Bao, and Z. Xu, “Study on the algorithm of draft survey error based on fuzzy comprehensive evaluation method and weighting emphasis method,” ACTA Metrologica Sinica, vol. 35, no. 1, p. 67, 2014.

H. X. Li, Y. F. Bao, and Z. Y. Xu, “Study on the algorithm of draft survey error based on fuzzy comprehensive evaluation method and weighting emphasis method,” Jiliang Xuebao/Acta Metrologica Sinica, vol. 35, no. 1, 2014, doi: 10.3969/j.issn.1000-1158.2014.01.14.

Committee on Energy Working Party on Coal UN ECE, Code of Uniform Standards and Procedures for the Performance of Draught Survey of Coal Cargoes. 1992.

H. W. Gu, W. Zhang, and W. H. Xu, “Digital Measurement System for Ship Draft Survey[J],” Applied Mechanics & Materials, vol. 333–335, p. 312, 2013.

T. Tsujii, H. Yoshida, and Y. Iiguni, “Automatic draft reading based on image processing [J],” Optical Engineering, vol. 55, no. 10, p. 104, 2016.

M. Syam, M. Rifani, and R. D. Jayanti, “ANALISIS UMUR EKONOMIS DAN UMUR TEKNIS KAPAL PENUMPANG MILIK PT. PELAYARAN NASIONAL INDONESIA (PERSERO),” JURNAL VENUS, vol. 7, no. 14, pp. 65–96, 2019.

W. J. Dibble, P. Mitchell, N. O. E. P. A. Staff, and N. of E. P. & I. Association, Draught Surveys: A Guide to Good Practice. in Loss prevention guides. North of England P&I Association Limited, 2009. [Online]. Available: https://books.google.co.id/books?id=f89CcAAACAAJ

D. M. Muchsin and R. S. Darmawan, “Evaluasi Konstan Kapal Pengangkut Curah sebagai Supervisi Teknis Draught Survey: Studi Kasus pada PLTU Batu Bara,” TRAKSI, vol. 23, no. 1, 2023.

K. R. Das and A. Imon, “A brief review of tests for normality,” American Journal of Theoretical and Applied Statistics, vol. 5, no. 1, pp. 5–12, 2016.

P. Schober, C. Boer, and L. A. Schwarte, “Correlation coefficients: appropriate use and interpretation,” Anesth Analg, vol. 126, no. 5, pp. 1763–1768, 2018.

M. H. Kutner, C. J. Nachtsheim, J. Neter, and W. Li, Applied linear statistical models, vol. 5. McGraw-Hill Irwin Boston, 2005.

C. Croux and C. Dehon, “Influence functions of the Spearman and Kendall correlation measures,” Stat Methods Appt, vol. 19, pp. 497–515, 2010.

J. C. Caruso and N. Cliff, “Empirical size, coverage, and power of confidence intervals for Spearman’s rho,” Educ Psychol Meas, vol. 57, no. 4, pp. 637–654, 1997.

DOI: http://dx.doi.org/10.12962/j25481479.v8i4.19162