Experiments for PHM: Needs, developments and challenges

Abstract

Much of the available data associated with seaport operations is uncertain and ambiguous, requiring an approach capable of handling both quantitative and qualitative information. Conventional risk modelling approaches are considered to be inadequate in many circumstances due to the lack of flexibility and an inappropriate structure for addressing the system's risks. This paper proposes a flexible risk assessment approach to facilitating the treatment of uncertainties in seaport operations in a systematic manner. The methodology consists of a fuzzy analytical hierarchy process, an Evidential Reasoning (ER) approach, and fuzzy set theory. The fuzzy analytical hierarchy process is used to analyse the complex structure of seaport operations and determine the weights of significant risk factors while ER is used to synthesise them. The methodology provides a framework for collaborative modelling of the system and allows for a step by step analysis. It could provide managers and infrastructure analysts with a flexible tool in order to enhance the resilience of the seaport system.(FMECA) and Bow-Tie (BT) have been widely used in analysis of critical systems and have contributed greatly to the literature of risk analysis. The aforementioned approaches have some drawbacks which affect their applications. The use of traditional risk assessment approaches to deal with newly arising hazards and threats (e.g. potential terrorist attacks) to maritime infrastructure reveals two major challenges: i) the lack of capability to process diverse data suitable for input into a risk inference mechanism, and ii) the lack of capability to analyse the interactive dependence between risk factors (Yang et al., 2009).One realistic way to analyse a system with unavailable data is to employ subjective assessment using the combination of fuzzy logic and Evidential Reasoning (ER). Compared to the traditional fuzzy inference mechanism (i.e. max-min fuzzy operations), an ER approach has the advantage of avoiding the loss of useful information in its inference processes; hence, it can be suitable for modelling complex systems.The insufficiency of quantitative risk assessment in the maritime-related literature together with the vision to establish a secure and resilient SCMI system has resulted in a need for an integrated risk assessment methodology capable of tackling the uncertainties associated with a system's operation (John, 2013). This paper is organised as follows. Section 2 reviews the existing literature on SCMI systems, and discusses the major risk factors associated with seaport operations. Sections 3 and 4 highlight the decision making techniques that are used for

Collision Risk Modelling of Supply Vessels and Offshore Platforms Under Uncertainty

“…The proposed framework provides the flexibility needed by experts to represent vague information resulting from the lack of quantitative data using experts' opinions. The framework is itemised in the following steps and presented in Figure 1 as derived from the existing literature (John et al, 2016; 2015; John, 2010; 2013): Preliminary system analysis phase. Selection of experts. Estimating weights of experts. Rating phase. Aggregation phase. Defuzzifying state. Converting fuzzy possibilities scores to fuzzy failure probabilities. Estimation of minimal cut sets. Ranking of minimum cut sets.

Figure 1. Flow Chart of the Proposed Methodology.

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A collaborative modelling of ship and port interface operations under uncertainty

“…, E n be scores of experts. Based on equations (5) and (6), the weighting score and factor of experts can be determined as…”

“…Based on the available information in section 'Literature review' and using equations (5) and (6), the weights of the experts can be calculated. The industrial positions, service times, academic qualifications and age of the experts are extracted from Table 2.…”

“…Research conducted by John 4 revealed that the maritime industry has a robust regulatory framework to curb the rate of accidents in shipping operation across the globe, yet accident happen leading to disruption of operations. John et al 5 further revealed that the complexity of the system is caused by the integration of technical, operational, organisational, security and natural events into its everyday operations. In order to analyse maritime systems, conventional modelling techniques such as event tree analysis (ETA), failure mode effect and criticality analysis (FMECA) and bow-tie methodology have been widely used and have immensely contributed to the literature of risk analysis.…”