다변량 관리도를 활용한 선박 메인 엔진의 이상 관리 상한선 결정에 관한 연구
A Case Study on the Establishment of Upper Control Limit to Detect Vessel’s Main Engine Failures using Multivariate Control Chart
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Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel’s main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel’s main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel’s main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel’s availability and provide a basis for a condition-based maintenance that can support proactive management of vessel’s main engine in the future.
Abstract
Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel’s main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel’s main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel’s main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel’s availability and provide a basis for a condition-based maintenance that can support proactive management of vessel’s main engine in the future.
참고문헌 (18)
- Boullosa, D., "Monitoring through T2 hotelling of cylinder lubrication process of marine diesel engine", Applied Thermal Engineering, 110, pp.32~38 (2017)
- Chen, Q., "Synthesis of T2 and Qstatistics for process monitoring", Control Engineering Practice, 12(6), pp.745~755 (2004)
- Chongfuangprinya, P., "Integration of support vector machines and control charts for multivariate process monitoring", Journal of Statistical Computation and Simulation, 81(9), pp.1157~1173 (2011)
- Chou, Y. M., "The control chart for individual observations from a multivariate non-normal distribution", Communications in statistics - Theory and methods, 30(8-9), pp.1937~1949 (2001)
- Efron, B., "An introduction to the Bootstrap", pp.1993, Chapman & Hall
- Gkerekos, C., "Ship machinery condition monitoring using performance data through supervised learning", Proceedings of the Smart Ship Technology, pp.105~111 (2017), The Royal Institute of Naval Architects
- Jang, D. H., "Development of maintenance system for vessels and plants", Bulletin of the Society of Naval Architects of Korea, 39(2), pp.234~243 (2011)
- Lamaris, V. T., "A general purpose diagnostic technique for marine diesel engines– Application on the main propulsion and auxiliary diesel units of a marine vessel", Energy Conversion and Management, 51(4), pp.740~753 (2010)
- Lazakis, I., "Advanced ship systems condition monitoring for enhanced inspection, maintenance and decision making in ship operations", Transportation Research Procedia, 14, pp.1679~1688 (2016)
- 이장명, "CAN의 분산 선행대기 열 기법을 이용한 선박 엔진 모니터링 시스템", 제어.로봇.시스템학회 논문지, 18(1), pp.13~20 (2012), 제어·로봇·시스템학회
- Lowry, C. A., "A review of multivariate control charts", IIE Transactions, 27(6), pp.800~810 (1995)
- Mokashi, A. J., "A study of reliability-centred maintenance in maritime operations", Marine Policy, 26(5), pp.325~335 (2002)
- Orosa, J. A., "In Applications and Experiences of Quality Control", JSNAK, 55(6) (2018)
- Phaladiganon, P., "Bootstrap-based T2 multivariate control charts", Communications in Statistics-Simulation and Computation, 40(5), pp.645~662 (2011)
- Pillay, A., "A maintenance study of fishing vessel equipment using delay-time analysis", Journal of Quality in Maintenance Engineering, 7(2), pp.118~128 (2001)
- Raptodimos, Y., "Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications", Ships and Offshore Structures, pp.1~8 (2018)
- Runger, G. C., "Contributors to a multivariate statistical process control chart signal", Communications in Statistics—Theory and Methods-Policy & Management, 25(10), pp.2203~2213 (1996)
- Shewhart, W. A., "Quality control charts", Bell Labs Technical Journal, 5(4), pp.593~603 (1926)
