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.
No abstract is provided for this article.
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.
No abstract is provided for this article.
his is an Accepted Manuscript of an article published by Taylor & Francis Group in Safety and Reliability of Complex Engineered Systems – Podofi llini et al. (Eds) September 3, 2015 by CRC Press, available online:http://www.crcnetbase.com/doi/pdf/10.1201/b19094-480
Reducing the operation and maintenance (O&M) cost is a necessity in current offshore wind farms so that the produced power can achieve a competitive price in the market. An offshore wind farm normally comprises a large number of turbines which demand frequent maintenance visits. In addition to making maintenance plans that avoid downtime and production losses, it is important to utilize the expensive resources, such as service vessels, in an efficient way. This article introduces the routing and scheduling problem of a maintenance fleet for offshore wind farms (RSPMFOWF), which is to determine the optimal assignments of turbines and routes to the vessels in terms of cost. Simultaneously considering the characteristics and limitations in this problem, we present the mathematical formulations for the RSPMFOWF. A computational case study is also carried out. The results provide both the optimized cost and detailed arrangements, which can be directly used in maintenance planning.
This chapter presents the challengesChallenges that complex systemsComplex systems face related to riskRisk modeling and human and organizational factorsOrganizational factors, hardware, and software interactionsInteractions. In Sect. 4.2, risk assessmentRisk assessment of software in automated systems is discussed. A conceptual modelModel to evaluate software failuresFailure is proposed, and challengesChallenges regarding quantification and cybersecurity are presented. In Sect. 4.3, risk assessmentRisk assessment of human factorsHuman factor in automated and autonomousAutonomous systems is discussed. Finally, in Sect. 4.4, a general framework is proposed that considers software and human factorsHuman factor along with hardware elements to perform risk assessmentRisk assessment of complex systemsComplex systems. The framework clarifies how the interactionsInteractions between software, human, and hardware could be considered in risk analysisRisk analysis of complex systemsComplex systems.
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.
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.
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 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.
Fisheries management receives valuable, but often fragmented information from academic disciplines such as biology, economics, and social sciences. A multi-disciplinary perspective seems to be necessary if the fisheries are to become sustainable. Globally, overcapacity is considered as the most serious threat to sustainable fisheries, which indicates the need for a stronger integration of technological aspects into fisheries management. This paper discusses application of systems engineering principles and integration of technology into fisheries management. The systems engineering process facilitates implementation of multi-disciplinary information from researchers to fisheries managers in the decision-making towards sustainable fisheries, but may also be used to overcome multi-disciplinary obstacles among scientists. The article concludes that use of systems engineering principles may become a valuable contribution to fisheries management because of increased transparency and reduced risk associated with the decision-making process.
Marine Autonomous Surface Ships (MASS) are tested in public waters. A requirement for MASS to be operated is that they should be at least as safe as conventional ships. Hence, this paper investigates how far the current ship risk models for ship-ship collision, ship-structure collision, and groundings are applicable for risk assessment of MASS. Nine criteria derived from a systems engineering approach are used to assess relevant ship risk models. These criteria aim at assessing relevant considerations for the operation of MASS, such as technical reliability, software performance, human-machine interfaces, operating, and several aspects of communication. From 64 assessed models, published since 2005, ten fulfilled six or more of these criteria. These models were investigated more closely. None of them are suitable to be directly used for risk assessment of MASS. However, they can be used as basis for developing relevant risk models for MASS, which especially need to consider the aspects of software and control algorithms and human-machine interaction.
Path planning is an essential part of autonomous surface vessel (ASV) operations. Risk models can be used to give estimates of risk related to the operation of technical systems, such as ASVs. Combining risk models directly with control systems can be a way to make autonomous systems more capable of assessing and evaluating risk, and in this way allow them to make better decisions. Focusing on path planning, this study aims at investigating how an online risk model used to inform an ASV of risk compares to a static safety domain. The results show that the paths selected when using the risk model can consider different environmental conditions, and the choice of path can be adapted based on how conservative the ASV should be with respect to risk. In this way the risk model provides a more detailed basis for making decisions than the static safety domain.
No abstract is provided for this article.
