229 publications from this institution
Enabling higher levels of autonomy while ensuring safety requires an increased ability to identify and handle internal faults and unforeseen changes in the environment. This article presents an approach to improve this ability for a robotic system executing a series of independent tasks by using a dynamic decision network (DDN). A simulation case study of an industrial inspection drone performing contact-based inspection is used to demonstrate the capabilities of the resulting system. The case study demonstrates that the system is able to infer the presence of internal faults and the state of the environment by fusing information over time. This information is used to make risk-informed decisions enabling the system to proactively avoid failure and to minimize the consequence of faults. Lastly, the case study demonstrates that evaluating past states with new information enables the system to identify and counteract previous sub-optimal actions.
<p>This article develops and experimentally tests a supervisory risk controller used to increase the safety of drone operations. Its task is to monitor the state of the drone and environment and to use this information to automatically change safety-critical parameters in real-time during operation. </p> <p>A case study of a tethered industrial inspection drone is considered. A system theoretic process analysis (STPA) is performed to identify how the system can fail. A Dynamic Decision Network (DDN), used as an online risk model, is built based on the results of the STPA. An optimization approach is used to choose an optimal parameter configuration that ensures an acceptable risk level.</p> <p>Through experimental tests, it is demonstrated how the supervisory risk controller is able to identify the state of the drone and the environment by combining information from multiple measurements over time and how it chooses values for the maximum speed, safety distance, and maximum vertical acceleration that produces an acceptable risk level. The parameters are updated during flight based on the output from the supervisory risk controller. When no parameter set can ensure an acceptable risk level then a recommendation of aborting the mission is sent to the human operator.</p> <p>Video of the experimental results can be found at https://youtu.be/RKhG9bguRJY</p>
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Failures in critical infrastructures may be hazardous to population, economy, and national security. There can be strong interdependencies between various infrastructures, but these interdependencies are seldom accounted for in current risk and vulnerability analyses. To reduce probability and mitigate consequences of infrastructure failures, these interdependencies have to be assessed. The objective of this paper is to present a method for assessing interdependencies of critical infrastructures, as part of a cross-sector risk and vulnerability analysis. The method is based on a relatively simple approach applicable for practitioners, but may be extended for more detailed analyses by specialists. Examples from a case study with the Emergency Preparedness Group of the city of Oslo, Norway, are included.
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No abstract is provided for this article.
Assessing the technical condition and remaining useful life of aging equipment is crucial for the life extension of O&G facilities. In order to perform a reliable assessment, models describing the degradation of the equipment are necessary. However, the use of accurate physical models for this purpose may be challenging. Some reasons are that the equipment can be exposed to various degradation mechanisms, which may be influenced by different operating conditions, and that the operational data may be scarce. This paper presents a systematic approach for modelling different degradation mechanisms, assessing the technical condition of a component, and quantifying the expected remaining useful life. The quantification is performed using a Bayesian network. Finally, the application of the proposed model is illustrated with the analysis of a fire water pump.
Systems engineering principles in fisheries management may structure and improve the decision-making process. Sustainability in the fishing fleet is comprised of economic, environmental, and social dimensions. Even though the total system value may be constituted by economic factors and technical factors, non-market issues, such as environmental and social issues, have an increasingly important impact on the economic performance of a system or company. Life cycle cost (LCC) is related to the systems engineering process, because economic considerations are very important in the process of creating systems. LCC involves evaluation of all future costs related to the life cycle of a system. The main objective of this article is to discuss the usefulness of LCC as a method to enhance sustainable designs of fishing vessels for ship owners, and to improve the decision-bases for fisheries management.
Vessel losses of command (e.g., propulsion, electrical power, or steering failure) can serve as the initiating event for significant maritime accidents, such as grounding. It is therefore important to estimate the frequency of such events for navigational risk assessments. Despite the existence of previous studies, new data have become available that may reveal more precise and useful information for risk estimations and accident prevention. This paper analyzes two databases of vessel losses of command within Norway's economic exclusive area over a five year period. The study utilizes a novel database of incidents observed by the Norwegian Coastal Administration's (NCA) Vessel Traffic Services (VTS), in addition to incidents reported to IHS Markit over the same five year period. Automatic identification system (AIS) data is used to construct activity metrics of vessel activity, which are used to compute vessel loss of command incidence rates for ship types. To account for under-reporting, capture–recapture methods are used to calculate adjusted incidence-rates. The duration of each incident is recorded and used to construct distributions of repair times. Probabilities of towing and anchoring are computed for ship types and incident location. The results indicate that previous studies may have underestimated the incidence of vessel loss of command. Using the best-case scenario, cargo ships and tankers suffer losses of command more frequently than other ship types. Significant under-reporting of losses of command was observed in the IHS Markit database.
Air emissions from fishing vessels must be reduced to comply with progressively stringent environmental regulations. Among the available solutions, liquefied natural gas (LNG) fuel may represent a promising solution, particularly from an environmental perspective. However, the use of LNG as a marine fuel creates different types of hazards than those that exist for traditional fuels. In addition, the increased complexity, safety requirements, and space required for LNG installation increase the capital cost. This article uses a systems engineering approach to clarify the technical aspects of LNG-fuelled systems, their potential implementation costs, and the expertise and training required to operate them safely. Ship owners can use such an approach to aid decision-making and trade-off analyses. Naval architects may also benefit from better information management. Finally, crews may better understand the logic behind the safety actions they are instructed to take.
Abstract This chapter presents methods for analysing interdependencies in critical infrastructures. In general, there are three groups of methods for analysing interdependencies; (1) conceptual, (2) model and simulation and (3) empirical and knowledge-based approaches. Examples of methods belonging to these groups are presented. The latter part of the chapter discusses challenges related to modelling, focusing on how to deal with complexity, trade-offs between abstraction and fidelity, choice of consequence measures and obtaining information.
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This article presents the process used to develop safety envelopes and subsea traffic rules for autonomous remotely operated vehicles (AROVs) used in subsea inspection, maintenance, and repair (IMR) operations. Preventing loss of subsea assets and the AROV is the overall goal of the proposed safety envelopes and subsea traffic rules. Currently, no such envelopes and rules exist. The safety envelope for the AROV is constructed using an Octree method. The proposed subsea traffic rules are derived by combining existing traffic regulations in marine and aviation industries. The proposed safety envelopes and traffic rules are tested using both a novel modular open robot simulation engine (MORSE) based underwater simulator and in the laboratory. The results from the laboratory tests show that the proposed safety envelopes and subsea traffic rules can be used during simulated or real IMR operations to recommend subsea traffic rules to the AROV and the human supervisor.
The risk caused by DP vessels in offshore marine operations is not negligible, due to wide applications of DP vessels in complex marine operations, and the sharp increase of DP vessel population. The DP accidents/incidents on the Norwegian Continental Shelf (NCS) that have occurred after 2000 indicate a need for improving safety of DP operations, which calls for new risk reduction measures. The focus of this paper is particularly on the offshore loading operations with DP shuttle tanker in offloading from floating production storage and offloading (FPSO) vessels on the NCS, but the results may be relevant also for other types of DP vessels in offshore oil and gas operations. In the paper, Man, Technology and Organization (MTO) analysis is applied to investigate the cause and barrier failures of nine reported accidents/incidents occurring over a 16-year period (2000–2015). MTO is based on three methods, including structured analysis by use of an event- and cause-diagram, change analysis by describing how events have deviated from earlier events or common practice, and barrier analysis by identifying technological and administrative barriers which have failed or are missing. The results are categorized into technical failures, human failures, organizational failures, as well as a combination of failures. The main finding is that the majority of the accidents are caused by the combination of technical, human and organizational failures. Critical root causes, results of change analysis and barrier analysis, and combination of failures are focused in the discussion. Recommendations of potential safety improvements are made on the aspects of the assessment of the actual system function, barrier management for marine systems, risk information to support different decision-makings, and the development of an on-line risk monitoring and decision supporting system.
Autonomous marine systems, such as autonomous ships and autonomous underwater vehicles, gain increased interest in industry and academia. Expected benefits of autonomous marine system in comparison to conventional marine systems are reduced cost, reduced risk to operators, and increased efficiency of such systems. Autonomous underwater vehicles are applied in scientific, commercial, and military applications for surveys and inspections of the sea floor, the water column, marine structures, and objects of interest. Autonomous underwater vehicles are costly vehicles and may carry expensive payloads. Hence, risk models are needed to assess the mission success before a mission and adapt the mission plan if necessary. The operators prepare and interact with autonomous underwater vehicles to carry out a mission successfully. Risk models need to reflect these interactions. This article presents a Bayesian belief network to assess the human–autonomy collaboration performance, as part of a risk model for autonomous underwater vehicle operation. Human–autonomy collaboration represents the joint performance of the human operators in conjunction with an autonomous system to achieve a mission aim. A case study shows that the human–autonomy collaboration can be improved in two ways: (1) through better training and inclusion of experienced operators and (2) through improved reliability of autonomous functions and situation awareness of vehicles. It is believed that the human–autonomy collaboration Bayesian belief network can improve autonomous underwater vehicle design and autonomous underwater vehicle operations by clarifying relationships between technical, human, and organizational factors and their influence on mission risk. The article focuses on autonomous underwater vehicle, but the results should be applicable to other types of autonomous marine systems.
Marine system accidents have a relatively high frequency worldwide. In Norwegian waters loss of installations has been avoided the last 20 years, but several near-misses and severe incidents confirm that the risk level is not insignificant. Barriers should prevent undesired events or reduce consequences should such events occur. The main purpose of barrier management is to establish and maintain the necessary barriers. It includes the processes, systems, solutions and measures needed to ensure implementation and follow-up of barriers. Petroleum Safety Authority has emphasized the need to develop barrier strategies during the last few years, and this has been particularly emphasized for topside systems and barrier functions to prevent and/or mitigate the consequences of hydrocarbon (HC) leaks. Insofar, the same focus on barrier management has not been put on marine systems and structural hazards. Risk associated with ballast systems, anchoring systems and dynamic positioning is at a level where further improvements should be made. Independent barrier elements and/or functions are required in order to provide substantial risk reduction. Some suggestions for independent barriers are discussed in this paper.
This article introduces Quality Function Deployment (QFD) as a method for improving the environmental performance of the Norwegian fishing fleet. Systems engineering has been introduced as a feasible process for handling sustainability issues in the fisheries, because it contains methods for general system design, operation, and support in a life-cycle perspective. QFD is related to systems engineering as a method for translating stakeholder needs into detailed system requirements at each life-cycle stage. Eco-QFD extends the scope of QFD, and combines QFD, Life-Cycle Cost (LCC), and Life-Cycle Analysis (LCA) to evaluate environmental effects and costs in the system development process. The article assesses the usefulness of Eco-QFD in fisheries management decision-making regarding sustainability in the fishing fleet, and for shipyards in their design of fishing vessels. It is concluded that Eco-QFD may be difficult to use for fisheries management in its present form, due to the complexity of sustainability, and the time and efforts demanded to carry out the analyses. Nevertheless, the structuring of the stakeholder needs and requirements may contribute to improved understanding of the decision-situation.
