Technological innovations and new areas of application introduce new challenges related to safety and control of risk in the maritime industry. Dynamic-positioning systems (DP systems) are increasingly used, contributing to a higher level of autonomy and complexity aboard maritime vessels. Currently, risk assessment and verification of DP systems are focused on technical reliability, and the main effort is centered on design and demonstration of redundancy in order to protect against component failures. In this article, we argue that factors, such as software requirement errors, human errors, including unsafe or too late decision-making, and inadequate coordination between decision makers, also should be considered in the risk assessments. Hence, we investigate the feasibility of using a systems approach to analyzing risk in DP-systems and present an adapted version of the system-theoretic process analysis (STPA). A case study where the STPA is applied to a DP system is conducted to assess whether this method significantly expands the current view on safety of DP systems. The results indicate that the reliability-centered approaches, such as the failure mode and effect analysis (FMEA), sea-trials and hardware-in-theloop (HIL) testing, are insufficient and that their view on safety is too narrow. The article shows that safety constraints can be violated in a number of manners other than component failures for DP systems, and hence, STPA complements the currently applied methods.
Abstract-Both marine surface vehicles and underwater vehicles are often equipped with cranes, robotic manipulators or similar equipment. Much attention is given to modeling of both the dynamics of marine vehicles and the dynamics of manipulators, cranes and other equipment. However, less attention is given to the interconnected behaviour of the vehicle and the equipment, even though such equipment may have a considerable impact on the vehicle dynamic behaviour, and therefore risk, or conversely, the vehicle may have a considerable impact on the equipment dynamic behaviour. With main focus on ships equipped with cranes, this paper presents a framework for modeling the interconnected dynamics of rigid body systems, based on Lagrangian dynamics. The resulting equations of motion are implemented as a bond graph template to which any subsystem of interest, such as actuators, hydrodynamics, and controllers may be interfaced. An example on how this framework can be used in order to develop a high fidelity simulator of an offshore installation vessel with a heavy duty crane is presented. This work represents the first bond graph implementation of crane and vessel dynamics where the interconnections are modeled according to true physical rigid body principles without non-physical limitations such as diagonal mass-inertia matrix.
The design and function allocation of control in complex technological systems have mainly been technology driven, resulting in increased automation. A human or user perspective is rarely taken in the technological development. The pertaining attitude seems to be that increased automation will reduce the occurrence of human error and thereby ensure safer design and operation. Increased levels of automation, however, may come with a cost of reduced situation awareness for the human operator. This is also the case in the design of the dynamic positioning (DP) system for vessels. Accident statistics show that the frequency of collisions in certain DP operations is above the acceptance criteria and that a combination of technical and human failures were the main causes in nearly all accidents. This article underlines the importance of considering the role of the human operator and human reliability in the design and operation of DP systems. It presents a functional model of the DP system, and discusses current function allocation of control and its impact on operators' situation awareness and performance. This article concludes with recommendations regarding function allocation of control and visualization of operational risk to enhance operator performance and reliability.
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