Human reliability assessments for the maintenance operation of marine systems

Human intervention plays a critical role in the maintenance operations of marine systems. Consequently human factors are identified as one of the main causes of accidents in marine systems especially during maintenance operations. Characterisation and assessments of human factors in the form of Human Reliability Assessment (HRA) is an important step to better understand accident causation during maintenance operations. This would help minimize human errors and enhance overall safety and reliability of the marine systems. The International Maritime Organization (IMO) recommends implementing HRA to quantitatively assess the effect of human errors as a part of quantitative risk analysis of shipping operations. However, HRA for the maintenance operations of marine systems is not given due attention. This PhD research is focused on developing novel methodologies to accurately estimate the Human Error Probability (HEP) during the maintenance operations of marine systems. The developed methodologies will help in better understanding accident causation, estimation of HEPs, and to develop the required strategies to minimize the HEP. This thesis contains seven chapters. The first chapter provides the introduction and general structure of the thesis. Second chapter presents development of a novel methodology to assess the HEP for the maintenance operation of marine systems. The developed methodology is applied to the maintenance procedures of a marine engine as a case study. The results showed that among the 43 considered activities, 'inspection and overhaul of piston/piston rings' have the lowest HEP meaning it has a low consequence for accidents. On the other hand, 'fuel and lubricating oil filters pressure difference checking' and 'renew filter element's activity have the highest HEP indicating it has highest chances of accidents. The third chapter presents a novel monograph as an easy-to-use tool to estimate HEP for marine operations. The developed monograph is applied to the maintenance procedures of a High Pressure (HP) fuel pump for estimating HEP. The results showed that 'inspection of fuel injectors', 'renewing nozzles' and 'testing' has the highest HEP. While the fourth chapter proposes a novel technique by revising and modifying the Human Error Assessment and Reduction Technique (HEART) to assess the HEP during the maintenance activities in marine operations. The developed methodology is applied to the maintenance procedures of a marine engine exhaust turbocharger as a case study. Application of the developed methodology confirms that extreme weather condition, extreme workplace temperature, high ship motion, high level of noise and vibration, and work overload and stress all increase the likelihood of human error as well as likelihood of potential accidents. The fifth chapter presents development of an HEP assessment technique using an advanced probabilistic technique named Bayesian Network (BN). The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. The case study results showed that category A‚ÄövÑvp chief engineer/captain (highest rank) with 10 years or more experience and voyage duration of 1 month has the lowest HEP, and category D‚ÄövÑvp fourth engineer/third officer with 5 years' experience and voyage duration of 4 months has the highest HEPs. As part of the HRA, extensive data collection activity was conducted. The details of this activity and outcome are reported in this thesis. The collected data is analysed for normality and also pair-wise significance test and presented in chapter 6. It helps to study generalization of the data and also to identify the relative importance of the factors. Workload and stress, and ship motion (roll and pitch) are identified to be critical factors affecting human performance on on-board maintenance operations. The collected data played an important role in testing and verifying earlier developed techniques and models. Chapter 7 includes the conclusions of the thesis. This thesis aims to serve as a comprehensive source of knowledge and technique to form a better understanding of human factors associated with maintenance activities in marine operations. It will assist in ensuring implementation of IMO requirement for safe and reliable maintenance activities and marine operations.