Application of Statistical Process Control on Port State Control

Abstract

Port state control (PSC) inspection is a critical measure in maritime safety, preventing substandard ships from entering ports. However, the current inspection system lacks an effective tool to monitor ship inspections and to identify which factors cause abnormal instances. Although statistical process control (SPC) has been proven an effective tool in process control in various other industries, this study is a pioneer in exploring the application of SPC on maritime inspections. In this paper, the inspection records collected in Taiwan's ports are utilized to construct control charts of inspection deficiencies so as to identify time-independent abnormal instances in inspections. Following that, a cause-and-effect diagram is conducted to trace the cause of those abnormal instances occurring at a specific time period. The results demonstrate that SPC is effective to monitor maritime inspections and is capable of identifying time-dependent abnormal instances. From a managerial and practical perspective, port administrations can use SPC to identify time-dependent abnormal instances and take proactive actions to mitigate the non-random phenomena in PSC inspections. To keep deficiency occurring in a stable and low profile, port administrations need persistent and consistent inspection requirements and avoid non-routine inspections. Meanwhile, inspectors with various specialties and backgrounds require consistent training.