Understanding safety and production risks in rail engineering planning and protection

Much of the published human factors work on risk is to do with safety and within this is concerned with prediction and analysis of human error and with human reliability assessment. Less has been published on human factors contributions to understanding and managing project, business, engineering and other forms of risk and still less jointly assessing risk to do with broad issues of ‘safety’ and broad issues of ‘production’ or ‘performance’. This paper contains a general commentary on human factors and assessment of risk of various kinds, in the context of the aims of ergonomics and concerns about being too risk averse. The paper then describes a specific project, in rail engineering, where the notion of a human factors case has been employed to analyse engineering functions and related human factors issues. A human factors issues register for potential system disturbances has been developed, prior to a human factors risk assessment, which jointly covers safety and production (engineering delivery) concerns. The paper concludes with a commentary on the potential relevance of a resilience engineering perspective to understanding rail engineering systems risk. Design, planning and management of complex systems will increasingly have to address the issue of making trade-offs between safety and production, and ergonomics should be central to this. The paper addresses the relevant issues and does so in an under-published domain – rail systems engineering work.     

Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals

This paper aims to enhance tangibility of the resilience engineering concept by facilitating understanding and operationalization of weak resilience signals (WRSs) in the rail sector. Within complex socio-technical systems, accidents can be seen as unwanted outcomes emerging from uncontrolled sources of entropy (functional resonance). Various theoretical models exist to determine the variability of system interactions, the resilience state and the organization’s intrinsic abilities to reorganize and manage their functioning and adaptive capacity to cope with unexpected and unforeseen disruptions. However, operationalizing and measuring concrete and reliable manifestations of resilience and assessing their impact at a system level have proved to be a challenge. A multi-method, ethnographic observation and resilience questionnaire, were used to determine resilience baseline conditions at an operational rail traffic control post. This paper describes the development, implementation and initial validation of WRSs identified and modeled around a ‘performance system boundary.’ In addition, a WRS analysis function is introduced to interpret underlying factors of the performance WRSs and serves as a method to reveal potential sources of future resonance that could comprise system resilience. Results indicate that performance WRSs can successfully be implemented to accentuate relative deviations from resilience baseline conditions. A WRS analysis function can help to interpret these divergences and could be used to reveal (creeping) change processes and unnoticed initiating events that facilitate emergence that degrades rail-system resilience. Establishing relevant change signals in advance can contribute to anticipation and awareness, enhance organizational learning and stimulate resilient courses of action and adaptive behavior that ensures rail operation reliability.     

Can You Handle the Headaches? Analyzing and Optimizing the Effectiveness of the Incident Management Process

Abstract

Recovering from incidents in a timely appropriate manner is vital to maintaining operational efficiency, controlling costs, and keeping users happy and productive. A key to quick recovery is having an incident management process in place. An analysis of the incident management process can offer insight into how effectively the process supports problem detection and isolation and systems restoration. An analysis of the incident management process can contribute to systems and application resilience, the capacity to keep failures from dramatically affecting users.     

Resilience analysis of service-oriented collaboration process management systems

Collaborative business process management allows for the automated coordination of processes involving human and computer actors. In modern economies, it is increasingly needed for this coordination to be not only within organizations but also to cross organizational boundaries. The dependence on the performance of other organizations should, however, be limited, and the control over the own processes is required from a competitiveness perspective. The main objective of this work is to propose an evaluation model for measuring a resilience of a service-oriented architecture (SOA) collaborative process management system. In this paper, we have proposed resilience analysis perspectives of SOA collaborative process systems, i.e., overall system perspective, individual process model perspective, individual process instance perspective, service perspective, and resource perspective. A collaborative incident and maintenance notification process system is reviewed for illustrating our resilience analysis. This research contributes to extend SOA collaborative business process management systems with resilience support, not only looking at quantification and identification of resilience factors, but also considering ways of improving the resilience of SOA collaborative process systems through measures at design and runtime.     

Performance optimization of integrated job-driven and resilience factors by means of a quantitative approach

Job-driven factors affect overall productivity and describe the characteristics influencing human performance. Resilience engineering (RE) is the capability of systems and groups to cope with disturbances and disruptions to enhance their performance. This study employs data envelopment analysis (DEA) approach to optimize the overall performance of a ceramic tile company by considering resilience and job-driven factors. The required data were collected via a standard questionnaire whose reliability was examined by statistical methods. In this regard, sensitivity analysis was performed to determine the most important factors. DEA results showed that job stress, job burnout, and management commitment play a central role in the investigated system. The overall results indicated that job-driven factors have a higher weight than resilience factors. This is one of the first studies that concurrently examine job-driven and resilience factors. Second, the present study uses DEA method in a ceramic tile manufacturer to achieve optimum performance. Third, the weights of all factors are computed for optimum redesign and re-engineering. Fourth, decision-makers may identify weak areas and strong points of their systems with respect to job-driven and resilience factors.     

Performance optimization of integrated resilience engineering and lean production principles

This paper conducts performance assessment from integrated resilience engineering (IRE) and lean production points of view. This is the first study that evaluates the impact of integrated resilience engineering (IRE) on lean production principles. Second, this study considers integrated impact of lean production by a unique intelligent algorithm. The proposed algorithm is composed of radial basis function (RBF), multi-layer perceptron (MLP) and adaptive neuro-fuzzy inference system (ANFIS). Moreover, the algorithm is capable of handling both crisp and fuzzy data due to the existence of intelligent approach. The proposed algorithm is equipped with verification and validation mechanism through conventional regression, statistical methods and data envelopment analysis. To demonstrate the applicability of the study, a real-world pipe manufacturer is considered as our case study. The results showed that “pull system” and “fault tolerant” among lean and IRE factors, respectively have been implemented inappropriately, while other factors are either suitably executed or ineffective.     

Challenges to multiteam system leadership: an analysis of leadership during the management of railway disruptions

Rail traffic is controlled by operators working in multiple control centres. Although each of these control centres enjoy quite some autonomy and authority, their activities are highly interdependent. This is especially the case during the management of disruptions. In this study, we look at the role of leader teams with system-wide responsibilities and the task of synchronizing the control centres’ activities. Research on leadership in this multiteam setting of networked control centres, which operate in a dynamic and time-compressed environment, is limited. Hence, this study explores the behaviours and functions of these leader teams during the management of two large-scale disruptions in the Dutch railway system. We will show how various factors influence the ability to provide leadership within this specific real-world context. This study demonstrates that combining insights from the literature on multiteam systems and resilience engineering can contribute to our knowledge of the critical challenges of control in polycentric adaptive systems.

     

Incident Command Skills in the Management of an Oil Industry Drilling Incident: a Case Study

The successful management of a complex, hazardous event in many domains demands a high level of incident command skills. In the oil and gas exploration and production industry, these skills were required by members of an Incident Management Team (IMT) established to respond the failure of a drilling riser in the Gulf of Mexico. When an incident occurs, members of an industrial IMT form an interdisciplinary, interdependent, but ad‐hoc team. As actual experience of dealing with major incidents of this nature is relatively rare, IMT members have to rely on emergency exercises in training, along with existing domain‐specific knowledge. Following a serious incident on an offshore drilling rig, semi‐structured interviews with the on‐shore strategic and tactical level IMT members (n=7) were conducted. These interviews have resulted in the identification and definition of incident command skills for members of an industrial IMT, namely decision making, situation awareness, communication, leadership, and teamwork, all of which can be affected by stress, as well as organisational factors that influenced the outcome of the incident. Limitations in current incident management training were identified, namely the need for specific incident command skills training. A framework is suggested around which specific incident command skills training can be structured. Key learnings from this case study are also presented which can provide guidance for the training and preparation of industrial incident management teams.     

Towards Resilient Rotterdam? Key conditions for a networked approach to managing urban infrastructure risks

Critical infrastructures are increasingly recognized to be playing important roles in urban resilience theory and practice. However, little is known about which governance challenges result from making them an integral part of urban resilience policies and what role city administrations play or could play in the resulting governance arrangements. We address these shortcomings in the scholarly literature by analysing the case of the Dutch city of Rotterdam, which has positioned itself as a front runner with regard to urban resilience. We find that the city administration is limited in its authority and depends on decisions made by other public and private actors, particularly those relating to the integrated management of interconnected infrastructure networks such as those for water and energy provision. We therefore argue that institutionalizing resilience will strongly depend on city administrations’ institutional capacity to manage networks more effectively. For this, we derive key conditions for institutional adjustments in current governance arrangements. Necessary adjustments include redefining roles and responsibilities for cross‐territorial risk management, cross‐sectoral and cross‐departmental budgeting of resilience measures, and integrating local actions and measures with those at regional and national levels of government. Our conclusions call for national and supranational legal reforms to establish uniform procedural rules for urban risk management and contingency planning to provide guidance for municipalities on how to enhance the resilience of their cities and infrastructures.     

Team reflection makes resilience-related knowledge explicit through collaborative sensemaking: observation study at a rail post

Resilience is defined as the ability to adaptively deal with system boundaries in the face of the unexpected and unforeseen (Branlat and Woods in AAAI Fall Sympoisum, 2010. http://www.aaai.org/ocs/index.php/FSS/FSS10/paper/viewPaper/2238). We hypothesize that drawing upon resilience-related knowledge is a prerequisite for such adaptivity. This paper proposes team reflection (Ellis et al. in Curr Dir Psychol Sci 23(1):67–72, 2014) as a macrocognitive function to make the resilience-related knowledge explicit. This knowledge is implicitly available with individual team members active at the sharp end but is never explicitly shared due to invisibility of goal-relevant constraints. To overcome this invisibility, we suggest an application that makes changes in the current rail socio-technical system visible in terms of the three system boundaries, a variation of the originally proposed by Rasmussen (Saf Sci 27(2/3):183–213, 1997): safety, performance and workload. This allows a team of rail signallers to analyse movements towards system boundaries and share knowledge on these movements. An observational study at a rail control post was conducted to assess the value of team reflection in making resilience-related knowledge explicit. For this purpose, we developed a first prototype of the application concerning the performance boundary only. Using naturalistic observations of a team during a week, we observed how they reflected at the end of their shift on salient system changes. A global content analysis was used to show the relevance of the content to resilience and to test the increase in the resilience-related knowledge throughout the observation period. A specific case of a human approaching the rail tracks, as a potential suicide, was analysed in detail. The results show the value of team reflection on system movements towards their boundaries, thus making goal-relevant constrained knowledge explicit within the operational rail environment.

     

Combinatorial optimization of resilience engineering and organizational factors in a gas refinery by a unique mathematical programming approach

This study is an attempt to evaluate the mutual impacts of resilience engineering (RE) and managerial and organizational factors in a large gas refinery. RE is a paradigm for safety management that focuses on how to help people cope with complexity under pressure to achieve success. The data obtained from questionnaire are analyzed by statistical methods and data envelopment analysis (DEA) approach. The results of Cronbach's alpha test show that the data are reliable. The results of DEA demonstrate that learning and flexibility among all RE factors have the greatest impact on managerial and organizational factors. In addition, the organizational factors have a greater influence on RE in comparison with managerial factors. Spearman's test was used to verify the results of this study. This is the first study that identifies the most important factors of integrated managerial and organizational factors and RE through a unique mathematical programming approach in a gas refinery.     

A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network

This paper includes a mesoscopic simulation modelling methodology developed for analysing and evaluating freight train operations in a rail network. The product of this methodology is a simulation rail network model implemented using an event-based simulation computer package called SIMUL 8. For simulation modelling purposes a decomposition approach is used. This approach allows us to separate the rail network under study into its components such as rail lines, rail yards, rail stations, rail terminals and junctions. The components of the rail network are thought of as interconnected queuing systems that interact and influence one another, so that the global impact of freight train operations in a rail network is captured.The products presented in this paper are of interest to rail freight tactical management, where global benefits are pursued.     

An incident information management framework based on data integration, data mining, and multi-criteria decision making

An effective incident information management system needs to deal with several challenges. It must support heterogeneous distributed incident data, allow decision makers (DMs) to detect anomalies and extract useful knowledge, assist DMs in evaluating the risks and selecting an appropriate alternative during an incident, and provide differentiated services to satisfy the requirements of different incident management phases. To address these challenges, this paper proposes an incident information management framework that consists of three major components. The first component is a high-level data integration module in which heterogeneous data sources are integrated and presented in a uniform format. The second component is a data mining module that uses data mining methods to identify useful patterns and presents a process to provide differentiated services for pre-incident and post-incident information management. The third component is a multi-criteria decision-making (MCDM) module that utilizes MCDM methods to assess the current situation, find the satisfactory solutions, and take appropriate responses in a timely manner. To validate the proposed framework, this paper conducts a case study on agrometeorological disasters that occurred in China between 1997 and 2001. The case study demonstrates that the combination of data mining and MCDM methods can provide objective and comprehensive assessments of incident risks.     

Authority gradients between rail network controllers,train crew and track workers in Australia and New Zealand: motivations and behaviours

Cognition, Technology & Work - The underlying relationship dynamics leading to authority gradients between frontline rail workers are being overlooked despite rail incident investigation...     

Development of a behavioural marker system for incident command in the UK fire and rescue service: THINCS

Non-technical skills in high-reliability industries include decision making, interpersonal communication and personal resilience. It has been argued that these skills are key to effective performance, safety and welfare. However, there is no agreed upon set of such skills or formal means to identify and assess them for incident commanders in the UK fire and rescue service (FRS). The aim of this research was to identify the non-technical skills that underpin effective incident command in the UK FRS, and to develop a behavioural marker system that captures these skills. Our research assessed the current range of training offered in non-technical skills across the UK FRS, and identified the non-technical skills of incident command within the UK FRS through interviews with incident commanders, and workshops with subject-matter experts. The six non-technical skills were: assertive, effective and safe leadership; effective decision making and planning; interpersonal communication; personal resilience; situational awareness; and teamwork and interoperability. A bespoke behavioural marker system, called THINCS, was developed with exemplary behaviours for each skill.     

基于混沌工程的微服务韧性风险识别和分析

微服务架构近年来已成为互联网应用所采用的主流架构模式.然而相比传统的软件架构，微服务架构更加复杂的部署结构使其面临更多能导致系统发生故障的潜在威胁，且微服务架构系统故障的症状也更加多样化.在可靠性等一些传统的软件度量已不能充分体现微服务架构系统故障应对能力的情况下，微服务的开发者们开始使用“韧性”（Resilience）一词描述微服务架构系统的故障应对能力.为了提高微服务架构系统的韧性，开发者们往往需要针对特定的系统环境扰动因素设计应对机制.如何判断一个系统环境扰动因素是否为影响微服务系统韧性的风险因素，以及如何在系统运行发布之前尽可能多地寻找到这些潜在的韧性风险，都是微服务架构系统开发过程中待研究的问题.在作者在先前研究中提出的微服务韧性度量模型的基础上，结合混沌工程，本文提出了针对微服务架构系统的韧性风险识别和分析方法.韧性风险的识别方法通过不断的向微服务架构系统引入随机系统环境扰动并观察系统服务性能的变化，寻找系统潜在的韧性风险，大幅减少了软件风险识别过程中的人力成本.对于识别到的韧性风险，通过收集执行混沌工程过程中的系统性能监控数据，韧性风险分析方法将利用因果搜索算法构建出各项系统性能指标之间的影响链路，并将可能性较高的链路提供给运维人员作为进一步分析的参考.最后，通过在一个微服务架构系统上实施的案例研究展示了本文提出的韧性风险识别和分析方法的有效性.     

Modelling of human alarm handling response times: a case study of the Ladbroke Grove rail accident in the UK

The purpose of the paper was to address the timeliness of the signaller's intervention in the Ladbroke Grove rail incident in the UK, as well as to consider the utility of human performance time modelling more generally. Human performance response time modelling is a critical area for Human Factors and Ergonomics research. This research applied two approaches to the same problem to see if they arrived at the same conclusion. The first modelling approach used the alarm initiated activity (AIA) model. This approach is useful for indicating general response times in emergency events, but it cannot comment in detail on any specific case. The second modelling approach employed a multi-modal critical path analysis (CPA) technique. The advantage of the latter approach is that it can be used to model a specific incident on the basis of the known factors from the accident inquiry. The results show that the AIA model produced an estimated response time of 17 s, whereas the CPA model produced an estimated response time of 19 s. This compares with the actual response time of the signaller of 18 s. The response time data from both approaches are concordant and suggest that the signaller's response time in the Ladbroke Grove rail accident was reasonable. This research has application to the modelling of human responses to emergency events in all domains. Rather than the forensic reconstruction approach used in this paper, the models could be used in a predictive manner to anticipate how long human operators of safety-critical systems might take to respond in emergency scenarios.     

Modelling of human alarm handling response times: a case study of the Ladbroke Grove rail accident in the UK

The purpose of the paper was to address the timeliness of the signaller's intervention in the Ladbroke Grove rail incident in the UK, as well as to consider the utility of human performance time modelling more generally. Human performance response time modelling is a critical area for Human Factors and Ergonomics research. This research applied two approaches to the same problem to see if they arrived at the same conclusion. The first modelling approach used the alarm initiated activity (AIA) model. This approach is useful for indicating general response times in emergency events, but it cannot comment in detail on any specific case. The second modelling approach employed a multi-modal critical path analysis (CPA) technique. The advantage of the latter approach is that it can be used to model a specific incident on the basis of the known factors from the accident inquiry. The results show that the AIA model produced an estimated response time of 17 s, whereas the CPA model produced an estimated response time of 19 s. This compares with the actual response time of the signaller of 18 s. The response time data from both approaches are concordant and suggest that the signaller's response time in the Ladbroke Grove rail accident was reasonable. This research has application to the modelling of human responses to emergency events in all domains. Rather than the forensic reconstruction approach used in this paper, the models could be used in a predictive manner to anticipate how long human operators of safety-critical systems might take to respond in emergency scenarios.     

Organizational Data Breach: Building Conscious Care Behavior in Incident Response

Organizational and end user data breaches are highly implicated by the role of information security conscious care behavior in respective incident responses. This research study draws upon the literature in the areas of information security, incident response, theory of planned behaviour, and protection motivation theory to expand and empirically validate a modified framework of information security conscious care behaviour formation. The applicability of the theoretical framework is shown through a case study labelled as a cyber-attack of unprecedented scale and sophistication in Singapore’s history to-date, the 2018 SingHealth data breach. The single in-depth case study observed information security awareness, policy, experience, attitude, subjective norms, perceived behavioral control, threat appraisal and self-efficacy as emerging prominently in the framework’s applicability in incident handling. The data analysis did not support threat severity relationship with conscious care behaviour. The findings from the above-mentioned observations are presented as possible key drivers in the shaping information security conscious care behaviour in real-world cyber incident management.     

Analysis of the resilience of team performance during a nuclear emergency response exercise

The current work presents results from a cognitive task analysis (CTA) of a nuclear disaster simulation. Audio-visual records were collected from an emergency room team composed of individuals from 26 different agencies as they responded to multiple scenarios in a simulated nuclear disaster. This simulation was part of a national emergency response training activity for a nuclear power plant located in a developing country. The objectives of this paper are to describe sources of resilience and brittleness in these activities, identify cues of potential improvements for future emergency simulations, and leveraging the resilience of the emergency response system in case of a real disaster. Multiple CTA techniques were used to gain a better understanding of the cognitive dimensions of the activity and to identify team coordination and crisis management patterns that emerged from the simulation exercises.