229 publications from this institution
Automation and increasing complexity mean that operators have to handle data and alarms and emergent decisions under the pressure of unexpected and rapidly changing hazardous situations. Position loss during marine operations may lead to serious accidents, such as collision, loss of well integrity, etc. An online risk model aims at assisting operators in dynamic positioning operations to successfully recover the vessel's position in a good timing. The objective of this paper is to identify generic scenarios of position loss during operational phase and the information that is needed for successful recovery action. The results show that position loss normally involves of complex human machine interactions, generally in two patterns. Based on the findings, it has been recognized that risk model considering time aspect is of vital importance to develop an online risk model for DP operations.
This paper presents a risk management framework (RMF) for unmanned underwater vehicles (UUV). UUV are tethered or untethered vehicles operating in hazardous surroundings. The RMF, as one of the first for UUV, emphasizes the need for considering human and organizational factors impact on risk. A case study on risk assessment has been carried out, covering the risk of loss and mission abort of an autonomous underwater vehicle. It is based on a case study of the Applied Underwater Robotics Laboratory of NTNU, which operates several UUV. The assessment applies human reliability analysis, fault tree analysis, and event tree analysis. The case study identified measures for risk reduction, such as improvement and adaptation of procedures for maintenance, planning of missions, and fault recognition and solving.
This paper presents a method for developing and testing a risk-based control system, as a first step towards including the human supervisor explicitly in the design of the system. The result is a control system with improved decision-making capabilities compared to existing control systems. The methodology presented in the paper uses the Systems Theoretic Process Analysis (STPA) to analyse the risks of an autonomous ship within its concept of operations (CONOPS), and a Human-STPA (H-STPA) is used to analyse human responsibilities and involvement. The STPA results are then used to construct a Bayesian belief network (BBN)-based risk model to assess the operational risk of the ship. This is represented as a risk cost, describing the expected cost of consequences caused by potential hazardous events. This cost is combined with fuel costs, operations costs, and the potential loss of income if new missions are not undertaken using a supervisory risk controller (SRC). The SRC is capable of making decisions about how the ship should be safely operated and notifies the human supervisor in due time when it is necessary for them to take control. The last part of the methodology presented in this paper is testing the control system using a set of verification objectives based on results from the STPA and H-STPA. A case study involving an autonomous cargo ship with a human supervisor located in a remote operation center (ROC) is included; it shows that the proposed control system can operate the ship safely in different conditions and situations. By designing the SRC to notify the human supervisor before it reaches its operational limit, the ship is able to operate in a wider range of conditions compared to when just the autonomous control system is in charge. Hence, the proposed methodology shows promising results and provides useful insights related to shared control for autonomous ships.
This paper describes the implementation of dynamic safety envelopes for Autonomous Remotely Operated Vehicles (AROVs). A safety envelope is defined as a three-dimensional spatial area around the AROV, which forms a virtual protective barrier against collision with known and unknown obstacles in the subsea environment. The Octree method is used to setup the cuboidal shape of the proposed safety envelope. A Fuzzy Inference System (FIS) is modeled to derive the size of the dynamic safety envelope. The three inputs of the proposed FIS are vehicle velocity, probability of acoustic sensor failure and time to collision risk indicator. A user interface allows for verification and visualization of the resulting dynamic safety envelope during live laboratory tests. The results show that similar to vehicular envelopes in other industries, dynamic safety envelopes can be implemented on AROVs. The proposed dynamic safety envelope may be used to model the behavior of AROVs when confronted with different collision scenarios.
No abstract is provided for this article.
Development of early warning indicators to prevent major accidents – to ‘build safety’ – should rest on a sound theoretical foundation, including basic concepts, main perspectives and past developments, as well as an overview of the present status and ongoing research. In this paper we have established the theoretical basis for development of indicators used as early warnings of major accidents. Extensive work on indicators have been carried out in the past, and this could and should have been better utilized by industry, e.g., by focusing more on major hazard indicators, and less on personal safety indicators. Recent discussions about safety indicators have focused on the distinction between leading and lagging indicators; however, a discussion on terms should not impede the development of useful indicators that can provide (early) warnings about potential major accidents.
This chapter defines and discusses important concepts like risk, uncertainty, vulnerability and interdependency. In the literature, these concepts are used in various ways and there exists no common accepted terminology. Therefore, these terms are defined to provide a basis for consistent use throughout this book.
Autonomous systems operation will in the foreseeable future rely on the interaction between software, hardware and humans. Efficient interaction and communication between these agents are crucial for safe operation. Conventional methods for hazard identification and safety assessment focus often on one of the aspects of the system only, e.g., human reliability, software failures, or equipment reliability. The method Human-System Interaction in Autonomy (H-SIA) was recently proposed, focusing on autonomous ships operation and collision scenarios. H-SIA provides a framework for analyzing autonomous ship operation as an entirety, rather than each agent separately. The method comprised initially of two main elements: An Event Sequence Diagram (ESD) and a Concurrent Task Analysis (CoTA). While the ESD models the events that can take place following an initiating event, the CoTA models which tasks the agents must perform for these events to succeed. This paper extends H-SIA to include the paths to failure, through the development of Fault Trees (FTs), which is necessary for risk analysis and identification of risk reduction measures. The FTs development of H-SIA introduces novelties in comparison to common FTs: (i) they model the system as whole, (ii) they are generic and can accommodate a diversity of systems designs; (iii) they lead to basic failure events. The FTs allows for identification of failure events arising through interaction between autonomous ship and human operators, as well as failure propagation through these agents. The basic failure events are applicable for different autonomous concepts. A case study on autonomous ship collision demonstrates the use of the extended method. The case study illustrates H-SIA’s applicability to different designs and levels of autonomy, its potential for identification of failure events, and its use in risk assessments.
Today's society is completely dependent on critical networks such as water supply, sewage, electricity, ICT and transportation. Risk and vulnerability analyses are needed to grasp the impact of threat
No abstract is provided for this article.
No abstract is provided for this article.
The cod resources in the Barents Sea constitute the most important fisheries in Norway. In order to reduce resource allocation conflicts among different gear and vessel groups and to ensure profit for all participants throughout the value chain, the sector is thoroughly organized. The institutions established to ensure long-term sustainability, have been developed within the framework of a joint Norwegian–Russian fisheries management regime. However, due to a very high fishing mortality, the cod stock is now under severe pressure. In addition, a major part of the cod fisheries is highly seasonal and unable to be a stable supplier to neither the land-based industry nor demanding international markets. In parallel, cod farming is expected to become a new emerging industry, with potential to copy the success of farmed Atlantic salmon. Many actors within the cod fisheries fear the future competition from the growing cod farming sector. With reference to important attributes that characterize the cod fisheries and cod farming, this paper discusses how a future farming industry may affect the traditional cod fisheries. Moreover, we discuss how the fisheries may be forced to organize in the future to encounter the expected competition from cod farming.
Finfish farming is the most common aquaculture mode in Europe. In Norway, the industry faces sustainability challenges. One major challenge is fish escape, which is a threat to both the environment and the industry's reputation. The more complex the operation, the greater the risk of escape, and their safety management needs improvement. A recommended strategy is to implement a safety indicator programme to monitor the risk levels before, during, and after an operation. The main objective of this study is to identify risk influencing factors (RIFs) and develop safety indicators for fish farm operations based on accident reports, using a qualitative graphical network to visualise and systematise causal chains. We have used a six-step methodology to develop safety indicators that can be applied to the case of fish escape: 1) The study was limited to fish escape accidents caused by the hazardous events hole in the net and submerged net. 2) Operations of high risk were identified, and chains of events were established, starting with these operations and ending with the accident (fish escape), based on fish escape report data and accident analyses. 3) A qualitative Bayesian network (BN) was drawn to specify the influence between the contributing causes and conditions in the causal chains. 4) RIFs were identified based on the BN (seven environmental, four organisational, eight operational, and 12 technical). 5) Safety indicators were developed to measure the condition of the RIFs. Update frequency of indicators, methods of measurement, and recommended states were also suggested. 6) The safety indicators were evaluated according to the chosen quality criteria. Based on the resulting list of safety indicators, we suggest a safety indicator programme for the operation fish crowding. The causal chains, RIFs, and safety indicators can also be used as a supplement in internal audits and quality improvement work, development of preventive measures, and training of fish farm personnel.
The aquaculture industry in Norway produced 1.3 million metric tons of fish in 2014, and further expansion is expected if the main sustainability challenges related to production and operation are mitigated. Major biological, operational and environmental challenges are parasite infection, fish escape, fish health, human injuries and fatalities. The larger farms, exposed locations, and sustainability challenges related to more production of salmon increases the need for efficient decision support methods and risk management. The combined effect of the technological development, with increased remote operation, autonomy and automation, and the production and operational challenges related to sustainability means that an interdisciplinary and systemic approach integrating risks to the environment, as well as to fish welfare and human safety, is needed. Therefore, the main contents of such a risk management approach are outlined in this paper. Potential users are fish farming companies, but the paper also addresses the need for an industry standard for sustainability and risk performance monitoring, which should be of interest to authorities and the whole industry. The paper concludes that risk management and sustainable development are complementary concepts that benefit each other because efficient risk management is decisive for achieving sustainability in aquaculture.
This article presents an overview of reported fatalities in the Norwegian aquaculture industry focusing on the production of Atlantic salmon and trout, which dominate the fish farming industry in Norway. The data on fatalities from 1982 to 2015 are registered by SINTEF Ocean, which is the only data source available. The fatality data set includes information on the incidents leading to fatalities, activities conducted at the time of fatalities and the time of year the fatalities were registered. The article discusses the fatality trends in light of the characteristics and changes in the Norwegian fish farming industry during the last three decades. This provides useful information for determining the most important current safety challenges and for developing efficient safety management in aquaculture.
No abstract is provided for this article.
This article discusses application of systems engineering principles and trade-off analysis of sustainability in the fishing fleet. Sustainability in the fishing fleet may be characterized by seven attributes measured by performance indicators. Evaluations show that the energy consumption is higher for the Norwegian ocean going fleet than the coastal fleet, whereas the opposite is the case for the number of fatalities. An important part of the systems engineering process is analysis and optimization of system alternatives. Thus, the main objective of the article is to investigate ranking of the sustainability attributes, which implies use of multi-attribute decision-making methods. The analytic hierarchy process was used to interview stakeholders to the fishing fleet about their preferences. The article concludes that if “accident risk” is weighted as the most important attribute, the smallest fishing vessels are not as sustainable as often claimed.
Commercial fishing is the most dangerous of professional callings, widely recognized as a major source of fatalities and injuries per population size within participating nations. The majority of reported fisheries injury accident data from a state is based solely on self-completed reporting formats. These formats are currently significantly limiting in their ability to tease out the incident specifics, being insufficiently detail orientated to adequately capture the range of contributing factors in the events that unfolded onboard. The content of these report forms ultimately determines the depth to which accidents may be probed in the interest of preventative learning. The problem faced by researchers is that the paucity of information on the circumstances of accident occurrences in these records, makes it a matter of gleaning every possible detail from relatively blank canvases. This article aims to focus the diffuse literary knowledge of the deficiencies pertinent to accident reporting in fisheries and subsequent knowledge extraction capabilities. Critiquing current reporting mechanisms, with a view to illustrating the extent of the problems, promoting the necessity for change and provoking discussion on how accident reporting could be improved in the future.
