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The remote control ship is considered to be the most likely implementation of maritime autonomous surface ships (MASS) in the near-term future. With collaborative control from onboard controllers and operators ashore, ships may operate in three navigation control modes (NCMs), manual, autonomous, and remote control, based on different levels of control authority. The scientific selection of the appropriate NCM for MASS under multiple driving modes is crucial for ensuring ship navigation safety and holds significant importance for operators and regulatory authorities overseeing maritime traffic within specific areas. To aid in selecting the proper NCM, this study introduces a risk-based comparison method for determining optimal control modes in specific scenarios. Firstly, safety control paths and processes for MASS under different NCMs are constructed and analyzed using system-theoretic process analysis (STPA). By analyzing unsafe system control actions, key Risk Influencing Factors (RIFs) and their interrelationships are identified. Secondly, a Hidden Markov Model (HMM) process risk assessment model is developed to infer risk performance (hidden state) through measuring RIF states. Cloud modeling with expert judgments is utilized to parameterize the HMM while addressing inherent uncertainty. Lastly, the applicability of the proposed framework was verified through simulation case studies. Typical navigation scenarios of conventional ships in coastal waters were chosen, and real-time data collected by relevant sensors during navigation were used as simulation inputs. Results suggest that in the same scenario, process risks differ among the analyzed NCMs. Traffic complexity, traffic density, and current become the primary factors influencing navigation risks, and it is necessary to select the appropriate NCM based on their real-time changes. [ABSTRACT FROM AUTHOR]

Safety-critical systems, such as the railway signal system, are subject to potentially high costs from failures, including loss of life and property damage. The use of new technology, including communication-based train control (CBTC) systems with software and computers, has changed the types of accidents that occur. Software-related issues and dysfunctional interactions between system components controlled by the software are increasingly the cause of incidents. Developing a “safe” safety-critical system requires accurate and complete safety requirements, which are the foundation of system development. Traditional hazard analysis techniques are insufficient for identifying the causes of accidents in modern railway signaling systems. Systems-Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to address these limitations. Building upon this foundation, a hierarchical approach to safety requirement development has been further developed. This approach combines STPA analysis with a hierarchical modeling approach to establish traceability links from safety requirements to specific architectures, refine and allocate system-level safety requirements to relevant subsystems, and abstract safety requirements at higher hierarchical levels to enable easy changes to lower-level implementations. This paper employs the aforementioned methodology within the context of the CBTC system, thereby enhancing risk management and hazard analysis, enabling early insights, and facilitating the generation of safety requirements of CBTC System.

The remote control ship is considered to be the most likely implementation of maritime autonomous surface ships (MASS) in the near-term future. With collaborative control from onboard controllers and operators ashore, ships may operate in three navigation control modes (NCMs), manual, autonomous, and remote control, based on different levels of control authority. The scientific selection of the appropriate NCM for MASS under multiple driving modes is crucial for ensuring ship navigation safety and holds significant importance for operators and regulatory authorities overseeing maritime traffic within specific areas. To aid in selecting the proper NCM, this study introduces a risk-based comparison method for determining optimal control modes in specific scenarios. Firstly, safety control paths and processes for MASS under different NCMs are constructed and analyzed using system-theoretic process analysis (STPA). By analyzing unsafe system control actions, key Risk Influencing Factors (RIFs) and their interrelationships are identified. Secondly, a Hidden Markov Model (HMM) process risk assessment model is developed to infer risk performance (hidden state) through measuring RIF states. Cloud modeling with expert judgments is utilized to parameterize the HMM while addressing inherent uncertainty. Lastly, the applicability of the proposed framework was verified through simulation case studies. Typical navigation scenarios of conventional ships in coastal waters were chosen, and real-time data collected by relevant sensors during navigation were used as simulation inputs. Results suggest that in the same scenario, process risks differ among the analyzed NCMs. Traffic complexity, traffic density, and current become the primary factors influencing navigation risks, and it is necessary to select the appropriate NCM based on their real-time changes.

Lithium-ion battery energy storage system (BESS) has rapidly developed and widely applied due to its high energy density and high flexibility. However, the frequent occurrence of fire and explosion accidents has raised significant concerns about the safety of these systems. To evaluate the safety of such systems scientifically and comprehensively, this work focuses on a MW-level containerized lithium-ion BESS with the system-theoretic process analysis (STPA) method. The work identified 53 unsafe control actions and corresponding loss scenarios. By combining loss scenarios and expert evaluation opinions, the key risk factors for system operation are obtained. Finally, this work proposed corresponding countermeasures and suggestions to address the key risk factors and improve the safety and reliability of the entire system operation. This work discusses the operational risks of MW-class containerized lithium-ion BESS and provides technical guidance for engineers in system designs, safe operations, and engineering applications. [ABSTRACT FROM AUTHOR]

A cyber-physical system (CPS) integrates communication and automation technologies into the operational processes of physical systems. Nowadays, as a complex CPS, an intelligent connected vehicle (ICV) may be exposed to accidental functional failures and malicious attacks. Therefore, ensuring the ICV’s safety and security is crucial. Traditional safety/security analysis methods, such as failure mode and effect analysis and attack tree analysis, cannot provide a comprehensive analysis for the interactions between the system components of the ICV. In this work, we merge system-theoretic process analysis (STPA) with the concept phase of ISO 26262 and ISO/SAE 21434. We focus on the interactions between components while analyzing the safety and security of ICVs to reduce redundant efforts and inconsistencies in determining safety and security requirements. To conquer STPA’s abstraction in describing causal scenarios, we improved the physical component diagram of STPA-SafeSec by adding interface elements. In addition, we proposed the loss scenario tree to describe specific scenarios that lead to unsafe/unsecure control actions. After hazard/threat analysis, a unified risk assessment process is proposed to ensure consistency in assessment criteria and to streamline the process. A case study is implemented on the autonomous emergency braking system to demonstrate the validation of the proposed method.

As a part of self-diagnosis functions, the instrumentation signal quality bit (SQB) is widely introduced in engineering applications, especially in nuclear power plant (NPP) distributed control systems (DCSs). However, the introduction of SQB significantly increases the DCS software complexity and may potentially be unsafe against its design intention. To reduce unscheduled shutdown accidents caused by potential unsafety, it is necessary to conduct a systematic safety analysis on the SQB. Therefore, this paper selects a CPR1000 NPP unscheduled shutdown accident as the research object to abstractly model and reproduce. The system-theoretic process analysis method is applied to analyze the SQBs involved in the unscheduled shutdown accident, which provides a way to identify the behavior of the system components, the interactions between them, and the safety constraints from the perspective of the whole NPP. Therefore, the weaknesses and potential factors affecting safe NPP operation are located, and countermeasures can be proposed. The safety analysis process can inform the identification of potentially unsafe scenarios and complement the verification and validation of the DCS software. Finally, the NPP economy should be improved while maintaining its reliable and safe operation. [ABSTRACT FROM AUTHOR]

The industrial zones are increasingly invaded by groups of mobile robots that are the most capable to perform complex tasks by collaborating and cooperating together. The operation of a mobile robot within a dynamic and high-risk environment with strong interaction between robot-robot and human-robot is of a certain complexity of control and safety. Such type of systems requires a safety and hazard investigation to verify if it is able to operate under certain operating conditions, while still ensuring the control and collaboration between mobile robots and human. This paper presents an approach that combines aspects of System-Theoretic Process Analysis (STPA) and Bowtie for safety assessment purposes. The approach we propose is used for a case related to multi-robot systems considering the coordinating, cooperating and collaborating aspects. At first, a risk identification study is done using STPA to extract a set of risk scenarios related to different types of hierarchical coordination architectures in addition to their factors. Afterward, an evaluation of the obtained scenarios is performed by the Bowtie method. The aim of our study is to better compare different control approaches of a multi-agent system. The combination offers detailed hazard identification. It further provides a classification of risks which helps to improve STPA outcomes thus facilitate decision-making over the suitable approach.

Hazard analysis methods such as HAZOP and STPA have proven to be effective methods for assurance of system safety for years. However, the dimensionality and human factors uncertainty of many assistive robotic applications challenges the capability of these methods to provide comprehensive coverage of safety issues from interdisciplinary perspectives in a timely and cost-effective manner. Physically assistive tasks in which a range of dynamic contexts require continuous human–robot physical interaction such as e.g., robot-assisted dressing or sit-to-stand pose a new paradigm for safe design and safety analysis methodology. For these types of tasks, considerations have to be made for a range of dynamic contexts where the robot-assistance requires close and continuous physical contact with users. Current regulations mainly cover industrial collaborative robotics regarding physical human–robot interaction (pHRI) but largely neglects direct and continuous physical human contact. In this paper, we explore limitations of commonly used safety analysis techniques when applied to robot-assisted dressing scenarios. We provide a detailed analysis of the system requirements from the user perspective and consider user-bounded hazards that can compromise safety of this complex pHRI.

The industrial zones are increasingly invaded by groups of mobile robots that are the most capable to perform complex tasks by collaborating and cooperating together. The operation of a mobile robot within a dynamic and high-risk environment with strong interaction between robot-robot and human-robot is of a certain complexity of control and safety. Such type of systems requires a safety and hazard investigation to verify if it is able to operate under certain operating conditions, while still ensuring the control and collaboration between mobile robots and human. This paper presents an approach that combines aspects of System-Theoretic Process Analysis (STPA) and Bowtie for safety assessment purposes. The approach we propose is used for a case related to multi-robot systems considering the coordinating, cooperating and collaborating aspects. At first, a risk identification study is done using STPA to extract a set of risk scenarios related to different types of hierarchical coordination architectures in addition to their factors. Afterward, an evaluation of the obtained scenarios is performed by the Bowtie method. The aim of our study is to better compare different control approaches of a multi-agent system. The combination offers detailed hazard identification. It further provides a classification of risks which helps to improve STPA outcomes thus facilitate decision-making over the suitable approach. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPSs) represent a systems category developed and promoted in the maritime industry to automate functions and system operations. In this study, a novel Combinatorial Approach for Safety Analysis is presented, which addresses the traditional safety methods[ limitations by integrating System Theoretic Process Analysis (STPA), Events Sequence Identification (ETI) and Fault Tree Analysis (FTA). The developed method results in the development of a detailed Fault Tree that captures the effects of both the physical components/subsystems and the software functions' failures. The quantitative step of the method employs the components' failure rates to calculate the top event failure rate along with importance metrics for identifying the most critical components/functions. This method is implemented for an exhaust gas open loop scrubber system safety analysis to estimate its failure rate and identify critical failures considering the baseline system configuration as well as various alternatives with advanced functions for monitoring and diagnostics. The results demonstrate that configurations with SOx sensor continuous monitoring or scrubber unit failure diagnosis/prognosis lead to significantly lower failure rate. Based on the analysis results, the advantages/disadvantages of the novel method are also discussed. This study also provides insights for better safety analysis of the CPSs. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPSs) represent a systems category developed and promoted in the maritime industry to automate functions and system operations. In this study, a novel Combinatorial Approach for Safety Analysis is presented, which addresses the traditional safety methods’ limitations by integrating System Theoretic Process Analysis (STPA), Events Sequence Identification (ETI) and Fault Tree Analysis (FTA). The developed method results in the development of a detailed Fault Tree that captures the effects of both the physical components/subsystems and the software functions’ failures. The quantitative step of the method employs the components’ failure rates to calculate the top event failure rate along with importance metrics for identifying the most critical components/functions. This method is implemented for an exhaust gas open loop scrubber system safety analysis to estimate its failure rate and identify critical failures considering the baseline system configuration as well as various alternatives with advanced functions for monitoring and diagnostics. The results demonstrate that configurations with SOx sensor continuous monitoring or scrubber unit failure diagnosis/prognosis lead to significantly lower failure rate. Based on the analysis results, the advantages/disadvantages of the novel method are also discussed. This study also provides insights for better safety analysis of the CPSs.

The maritime industry is currently ongoing into a digital transformation to develop cleaner, safer and smarter transport services. Establishing such services requires identifying and assessing new emerging risks such as software and design flaws. Thus, suitable hazard identification and risk analysis methods must be developed and implemented for these complex services. This study aims to develop a novel risk analysis methodology by integrating Systems Theoretic Process Analysis, Bayesian Network, Noisy-OR gates, Parent divorcing technique and Sub-modelling. The effectiveness of the proposed methodology is demonstrated through a case study of Remote pilotage operation. The results show that the methodology can be applied to complex operations to assess the propagation of risks from a single fault or failure in a system to the hazards, accidents and incidents, and ultimately the losses. Furthermore, it is demonstrated how the remote pilotage risk model can support pilots and pilotage companies in real-time decision-making by estimating the likelihood of losses in case of a single fault or failure. • Proposing a methodology for risk analysis using an STPA-based Bayesian network. • Integrating Noisy-OR, PDT, and Sub-models for large-scale BN development. • Assessing risks in Remote pilotage operation using the proposed methodology. [ABSTRACT FROM AUTHOR]

In this paper, an adaptation of the system-theoretic process analysis (STPA) approach to a sociotechnical system of monitoring and tracking diabetes mellitus (DM) is proposed. Several human controllers such as the patient, physicians, other healthcare providers, and people in the social environment were considered in the hierarchical safety control structure. During the identification of the causal factors (causal scenarios) for the unsafe control actions of the human controllers, the three-phase approach proposed by France (2017) as well as the interaction problems between the subsystems in the hierarchical safety control structure were considered, and the implementation of the basic safety design procedure was included in the methodology for the improvement of system. A dynamic STPA methodology is also proposed as an extension to the basic methodology. [ABSTRACT FROM AUTHOR]