Four KPIs for the assessment of biofouling effect on ship performance. (1st December 2020)

• Record Type: Journal Article
• Authors: Carchen, Alessandro; Atlar, Mehmet
• Is Part Of: Ocean engineering. Volume 217(2020)
• Publication Date: 2020-12-01
• Subjects: Ship performance -- KPI -- Onboard monitoring -- Biofouling -- Propeller fouling -- Hull roughness; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2020.107971
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Biofouling accumulation on hull and propeller is one of the principal contributors to a ship's service performance losses. Ship Performance Monitoring Systems (SPMSs) are widely regarded as the primary means of monitoring the service performance decay of ships. The effect of fouling can be assessed by observing the change over time of parameters commonly termed Key Performance Indicators (KPI). Common KPIs are power increase and speed loss. These KPIs are, however, not enough to provide a clear perspective of the hydrodynamic vessel performance. This paper introduces three new KPIs in support of the common power increase KPI. These three KPIs need the propeller characteristics (e.g. open water curves) to be known, and one of them is based on the measurement of thrust. The method used to calculate them is described. The derivation of the reference performance baselines is demonstrated in applying this methodology to Newcastle University's Research Vessel "The Princess Royal". The concurrent analysis of all four KPIs is finally shown to provide more robust and detailed information regarding the source of the performance losses and their entity when compared to the real fouling state of this vessel. Highlights: Four KPIs for the estimation of biofouling effect on ship hydrodynamic performance. Derivation of the KPIs and the performance baselines. Full-scale performance monitoring on the R/V 'The Princess Royal' using the proposed approach is presented and commented. Advantages of using the proposed KPIs is demonstrated with real full scale data.