Systematic Analysis of Multi-Source Inspection Database via Ship Smart Audit System
Keywords:Ship inspection, Smart audit, Cognitive mapping, Statistical analysis, M-SCAT
This study proposes a methodology to deeply analyze the multi-source inspection/audit findings gathered from a ship fleet to promote and implement proactive measures systematically. In addition to the ship audit reports of Company-A operating 16 bulk carriers in the Black Sea and the Mediterranean, the multi-source inspection database also consists of benchmarking datasets of different fleets. The Ship Smart Audit System (SSAS), including data collection, causation, analysis and prioritization, and implementation phases, is developed to strengthen the maritime regulatory compliance. Particularly, the Marine Systematic Cause Analysis Technique (M-SCAT), Cognitive Mapping (CM), and Pareto analysis are integrated into methodological background of the study. The SSAS is demonstrated with 5,000 findings from the benchmarking dataset and, subsequently, over 1,900 findings from the Company-A. Then, cause priorities, root cause trends, preventive actions, and audit item preferences are identified as an interconnected process of the ship management company. Consequently, the study encourages maritime executives to increase the effectiveness of pre-inspection and internal audit implementations.
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