229 publications from this institution
No abstract is provided for this article.
Sustainable fisheries are the main objective of Norwegian fisheries management. Despite powerful management tools, sustainability in the fisheries sector is not an easy task. There is no formal definition of the concept, and operationalization is vague. In recent years, private actors and non-governmental organizations (NGOs) have increased their impact on defining sustainability in the fisheries, which has reduced the power of the traditional fisheries management to determine its content. The lack of a clear strategy for fisheries management to increase sustainability makes it timely to address three research questions: (i) what is meant by “sustainable fisheries”, (ii) to what extent has the institutionalization of the Norwegian fisheries management channeled the sustainability concept towards specific trajectories, and (iii) what are the options and hard choices available to increase sustainability in the Norwegian fisheries in the future? These questions are investigated in this article.
Understanding risk-influencing factors (RIFs) associated with the occurrence of maritime accidents is important to prevent their future occurrence, identify high-risk ships, and properly influence policy. However, current methods often suffer from selection bias or do not account for variations in ship exposure, leading to biased or incomplete assessments. This study addresses these gaps by incorporating AIS-derived activity metrics as offset variables in regression analysis. This transformation of the dependent variable leads to the analysis of accident rates. The method is applied to ship losses of command (i.e., loss of propulsion, loss of electrical power, or loss of directional control / steering) by cargo ships in Norwegian waters from 2017 to 2021. Significant variables influencing the rate of loss of command include ship’s flag state, ship manager domicile, number of inspection deficiencies, propulsion redundancy, and the use of a single fuel onboard. Inspection deficiencies and sailing with a flag of convenience are associated with increased rates. Sailing with a Norwegian ship manager, propulsion redundancy, and a single fuel type onboard are associated with decreased rates. Incorporating measures of ship activity as exposure significantly improves the overall model fit, leading to better identification of RIFs associated with the occurrence of ship losses of command. Sensitivity analyses using sailed distance as exposure and the Cox proportional hazards model demonstrate overall robustness. The results are beneficial for identifying high-risk ships from the perspective of vessel traffic management and can be used for decision-making. The method has promising potential for the future analysis of RIFs associated with other types of maritime accidents.
Autonomous and unmanned ships are approaching reality. One of several unsolved challenges related to these systems is how to perform safety verification. Although this challenge represents a many-faceted problem, which must be addressed at several levels, it seems likely that simulatorbased testing of high-level computer control systems will be an important technique. In the field of reliability verification and testing, design verification refers to the process of verifying that specified functions are satisfied over the life of a system. A basic requirement for any autonomous ship is that it has to be safe. In this paper, we propose to use the Systems-Theoretic Process Analysis (STPA) to (i) derive potential loss scenarios for autonomous ships and safety requirements to prevent them from occurring, and (ii) to develop a safety verification program, including test cases, intended to verify safety. Loss scenarios and associated safety requirements are derived using STPA. To derive a safety verification program, these unsafe scenarios and safety requirements are used to identify key variables, verification objectives, acceptance criteria and a set of suitable verification activities related to each scenario. The paper describes the proposed methodology and demonstrates it in a case study. Test cases for simulator-based testing and practical sea-trials are derived for autonomous ships. The case study shows that the proposed method is feasible as a way of generating a holistic safety verification program for autonomous ships.
Maritime Autonomous Surface Ships (MASS) are the subject of a diversity of projects and some are in testing phase. MASS will probably include operators working in a shore control center (SCC), whose responsibilities may vary from supervision to remote control, according to Level of Autonomy (LoA) of the voyage. Moreover, MASS may operate with a dynamic LoA. The strong reliance on Human-Autonomous System collaboration and the dynamic LoA should be comprised on the analysis of MASS to ensure its safety; and are shortcomings of current methods. This paper presents the Human-System Interaction in Autonomy (H-SIA) method for MASS collision scenarios, and illustrates its application through a case study. H-SIA consists of an Event Sequence Diagram (ESD) and a concurrent task analysis (CoTA). The ESD models the scenario in a high level and consists of events related to all system's agents. The CoTA is a novel method to analyse complex systems. It comprises of Task Analysis of each agent, which are preformed concurrently, and uses specific rules for re-description. The H-SIA method analyses the system as whole, rather than focus on each component separately, allowing identification of dependent tasks between agents and visualization of propagation of failure between the agents’ tasks.
This chapter presents an approach for a cross-sector risk and vulnerability analysis (RVA) of critical infrastructures. The RVA is an extended version of a preliminary hazard analysis (PHA) and can be applied to any complex system with only minor adaptations. The analysis has three phases described below: (1) analysis preparation, (2) preliminary risk analysis and (3) detailed risk analyses. The objective of the RVA is to identify hazardous events related to the activity/system as thorough as reasonably practicable. In phase 2, risk is assessed by the analysis group from direct assessments of probabilities and consequences on a semi-quantitative scale, such as low (L), medium (M) and high (H). This is in line with a standard PHA, which aims to identify and assess all major risks, and provide risk-reducing measures, without including detailed risk calculations or analyses. The preliminary risk analysis is then used for screening, and the most critical events are investigated further for various detailed analyses and quantifications. The RVA described here intends to give a complete overview of all risks elements related to the systems under investigation.
This article presents an overview of reported injuries in the Norwegian aquaculture industry focusing on the production of Atlantic salmon and trout, which dominates the fish farming industry in Norway. Two different data sets form the basis for the analysis: (i) occupational injuries reported to the Norwegian Labor and Welfare Administration, and (ii) serious occupational injuries reported to the Norwegian Labor Inspection Authority. The data sets on occupational injuries and serious injuries provide information about mode of injury, type of injury, affected body parts, and time of year of the reported injuries. The results and the injury trends are analyzed and discussed in light of important characteristics and changes in the Norwegian fish farming industry, including underreporting. This information is useful in safety management and for allocating resources for risk-reducing measures.
The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of software failures intro traditional risk analysis currently is difficult. Current methods that attempt software risk analysis, consider the interaction with hardware and software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected software failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional software failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on software is taken, that allows for integration of software failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
The Arctic is a vast area with many future economic possibilities for the oil and gas, shipping and the fishing industries. The climate is harsh, the environment vulnerable, but the potential profits from future expansion in the area are huge. The on-going public debate on the Arctic includes discussions both for and against industrial development in these areas, however the reality is that as resources become scarcer in other parts of the world, Arctic expansion will become inevitable. Therefore adequate preplanning of the activities, understanding of the operational environment and development of barriers against undesired events becomes infinitely more important for sustainable, reliable and safe operation in the future. The fishing fleet has been operating in the Arctic region for decades and while the safety for the fishers is questionable, it is a matter of resources that drove and will continue to drive this expansion. The IMO’s Polar Code for shipping is now under construction and the fishing fleet will have to comply with this and other regulations for future operations in the Arctic. This paper focuses on the maintenance and safety management regimes and requirements of the fishing fleet currently operating in the Arctic. With long distances to service and help, and a short operating season, a reliable system is a mandatory requirement for the economic stability of these operations. Mutual benefits may be gained if operational experiences from fishing can be utilized by the oil and gas industry and ship transport when moving their operations into the arctic areas, whereas the fishing fleet can improve their safety performance through closer alignment with those standardized procedures applied in other industries.
Considering that few or no human operators are directly involved in the operation of Autonomous Marine Systems (AMS), an online risk model is necessary to enhance the intelligence of the AMS, its situation awareness, and decision-making. The current study identifies the criteria for an online risk model for AMS, which can be used to assess its validity and effectiveness. Taking an under-ice Autonomous Underwater Vehicle (AUV) operation as an example, the current work investigates how different risk analysis methods, namely the Preliminary Hazard Analysis (PHA), the Systems Theoretic Process Analysis (STPA), and Procedural Hazard and Operability Analysis (HAZOP), contribute to fulfilling the different criteria for online risk modeling of AMS. The analysis results show that STPA can be considered a good basis for developing an online risk model due to its relatively good coverage of the identified evaluation criteria, especially its ability to handle the interaction between system and software failure. In addition, considering some shortcomings of using STPA and the changing role of human operators in the AMS operation, PHA and Procedural HAZOP can be used as complementary tools. It is expected that the analysis results and conclusions can be adapted to other AMS as well.
Great efforts have been made in order to manage the fisheries more sustainably, but so far, most of these efforts have failed. This is putting the welfare of current and future generations at risk. The fishing fleets have catching capacity that well exceeds the rate at which ecosystems can produce fish, and thus many fish stocks are being overexploited. One of the objectives of the Norwegian government is to manage the fisheries in accordance with sustainable development. Sustainable development and risk management are frameworks with some mutual qualities. In the Norwegian petroleum industry, risk management of Health- Safety and Environment (HSE) is based on functional or goal-oriented regulations. Functional regulations focus on the result without describing in detail how it may be attained, e.g. an acceptable safety level at a petroleum installation. This paper discusses the possibility of transferring experience and knowledge of risk management and functional regulations from the Norwegian petroleum industry into the Norwegian fisheries management in order to increase sustainability in the fishing fleet. An important research question is the connection between an acceptable sustainability level in the fisheries, and transforming the fisheries regulations into functional regulations based on management objectives.
This article outlines a new approach to reliability, availability, maintainability, and safety (RAMS) engineering and management. The new approach covers all phases of the new product development process and is aimed at producers of complex products like safety instrumented systems (SIS). The article discusses main RAMS requirements to a SIS and presents these requirements in a holistic perspective. The approach is based on a new life cycle model for product development and integrates this model into the safety life cycle of IEC 61508. A high integrity pressure protection system (HIPPS) for an offshore oil and gas application is used to illustrate the approach.
This chapter is intended to assist in the data collectionData collection and development of online risk assessmentOnline risk assessment for automated marine and maritime systemsMarine and maritime systems. Section 3.1 presents the data flowData flow in online risk assessmentOnline risk assessment modelsModel. One of the main steps, in the modeling process, is data collectionData collection and preparationData preparation, which is explained in Sect. 3.2. Lastly, in Sect. 3.3, the quantification processQuantification process of failureFailure probabilitiesProbability/frequencies using the collected data is presented and discussed. In this chapter, a dynamic positioningDynamic positioning (DP) system as an example of an automated complex systemComplex systems is presented to illustrate the process of data collectionData collection and modeling more clearly.
Failures in critical infrastructures can cause major damage to society. Wide-area interruptions (blackouts) in the electricity supply system have severe impacts on societal critical functions and other critical infrastructures, but there is no agreed-upon framework on how to analyze and predict the reliability of electricity supply. Thus, there is a need for an approach to cross-sector risk analyses, which facilitates risk analysis of outages in the electricity supply system and enables investigation of cascading failures and consequences in other infrastructures. This paper presents such an approach, which includes contingency analysis (power flow) and reliability analysis of power systems, as well as use of a cascade diagram for investigating interdependencies. A case study was carried out together with the Emergency Preparedness Group in the city of Oslo, Norway and the network company Hafslund Nett. The case study results highlight the need for cross-sector analyses by showing that the total estimated societal costs are substantially higher when cascading effects and consequences to other infrastructures are taken into account compared to only considering the costs of electricity interruptions as seen by the network company. The approach is a promising starting point for cross-sector risk analysis of electricity supply interruptions and consequences for dependent infrastructures.
Many fisheries have significant challenges related to sustainable development, such as overexploitation and overcapacity in the fishing fleet. Overcapacity leads to increased pressure on fish resources, reduced profitability, and environmental problems such as greenhouse gas (GHG) emissions and acidification fromfuel consumption. Sustainable management of the fish resources is an important objective in Norway, but overcapacity is a problem in several Norwegian fleet segments. Important issues in this respect are whether the traditional management models are able to deal with the capacity development, and whether the role of technology as a relevant discipline in fisheries management is underestimated.The objective of this work has been to integrate a technological perspective into fisheries management in order to improve sustainability in the fishing fleet. The thesis work has been limited to the Norwegian fisheries in Norwegian territorialwaters. Since the main problems addressed in this thesis are sustainability and overcapacity, the system boundaries are limited to the fishing fleet. This means that the marine ecosystem in where the fishing vessels are interacting, is outside the thesis’ boundaries.The main contributions of this thesis are:• Development of a methodological framework that structures fisheries management decision-making, with main emphasis on improved sustainability in the fishing fleet.• Clarification of the concept of sustainability in the Norwegian fishing fleet.• Classification of attributes characterizing sustainability, and a performance evaluation of the different vessel groups in the cod-fishing fleet.• Comparison of two cod-production systems, with focus on sustainability.• Suggestions for how fisheries management can evaluate sustainability on a regular basis.• Improved foundation for further research about sustainability in the fisheries. A lot of literature is collected and synthesized.The framework developed is based on the systems engineering process. The nature of sustainability requires a systems perspective. There are different system analysis methods, but from a technological perspective, dealing with multidisciplinary tasks, systems engineering has been selected as the most feasible process. It has a strong focus on stakeholder needs and requirements, and it facilitates frequent evaluations of sustainability, which is important in order to assess management efficiency and goal achievement.Problems regarding sustainability in the fisheries are not only caused by technological development, but have organizational challenges as well. However, in this thesis the focus is within the technological perspective. Systems engineering is not applied as an attempt to change the structure of fisheries management, but as means of suggesting a decision-making process that improves sustainability in the fishing fleet.Fisheries management involves decision-making in situations often characterized by high risks and uncertainties, and it may be difficult to predict the outcomes of the decisions, for example, regarding sustainability in the fishing fleet. A number of tools that are available to support decision-making have been discussed and used in the thesis, such as cost-benefit analysis, risk acceptance criteria, life cycle cost (LCC), the Analytic Hierarchy Process (AHP), and Quality Function Deployment (QFD). Nevertheless, these tools do not provide “correct” answers; they have limitations, they are based on a number of assumptions, and their uses are based on scientific knowledge as well as value judgments involving political, strategic, and ethical issues. This means that these methods leave the decision-makers to apply decision processes outside the practical applications of the analyses, to which the framework offers guiding principles and structure.The main outcome of using systems engineering principles in fisheries management, is that the framework offers a broader analytical perspective to fisheries management and sustainability, which acknowledge that sustainability cannot be distinguished fromthe context. Today, most input to fisheries management come from biology and economy, such as stock assessments and profitability analyses. In systems engineering, information from different scientific disciplines, for example, biology, social sciences, economy, and technology, are necessary input to the analyses and decision processes, because fisheriesmanagement is much more than bio-economics. Application of the systems engineering process in fisheries management, and the inclusion of technology, introduce new perspectives, new disciplines, and new stakeholders into the decision-making process in the fisheries.Based on the framework developed in the thesis, the sustainability performance of the cod-fishing fleet has been evaluated. Sustainability in the fishing fleet may be characterized by seven attributes; accident risk, employment, profitability, quality, catch capacity, bycatch/selection, andGHGemissions/acidification. Indicators have been identified in order to measure the system performance within the attributes. The evaluation shows that there are differences in the performance of the vessel groups. These differences pose a major challenge to fisheries management in their decision-making regarding sustainability in the fleet. The smallest vessels have the lowest fuel consumption (kg fuel/kg fish), but they have a very high accident risk (FAR). The evaluation of cod fishing vs. cod farming shows that the potential growth in the cod farming industry may cause changes in the management system of the cod fisheries, such as a possible shift from the IVQ-systemof today to an ITQ-system.The Norwegian fisheries management lacks frequent evaluations of its policies, and the information and data available about the fisheries are fragmented. Sustainability should be evaluated on a regular basis by use of performance indicators to determine if sustainability increases or decreases. For simplicity, the indicators could be aggregated into a sustainability index showing the overall system performance. Aggregation implies simplification and weighting of the indicators, which means that such an index should be used with care. Sustainability implies a long term perspective when taking decisions, because future generations will be affected. The performance evaluations can give indications of trends, which means that the results can be used to predict consequences in the future, based on the current development.
No abstract is provided for this article.
Purpose The purpose of this paper is to present an approach for measuring the ability of oil and gas production plants to utilize shutdowns opportunistically for maintenance. Design/methodology/approach Key performance indicators have been developed from case studies with two offshore oil and gas installations on the Norwegian Continental Shelf. The key performance indicators measure the quality of the work preparations and the ability to utilize shutdowns opportunistically. Shutdowns may provide opportunities for execution of maintenance, but it is hardly possible to undertake any maintenance work requiring shutdown if the organization is not well prepared and the work is not well planned. Findings The results from testing of the indicators on two oil and gas installations shows that several of the indicators are relevant for determining the quality of preparations, whereas more effort needs to be put into gathering data applicable for monitoring the actual utilization of the shutdowns. Research limitations/implications Production losses, due to turnarounds and unforeseen shutdowns in oil and gas operations, are significant, and the improvement potential is large. The indicators may assist maintenance managers in planning and improving the plant's utilization of shutdowns and may contribute to substantial cost savings. Originality/value The approach in the paper adds important knowledge on how to actually measure the quality of maintenance work planning and execution.
