Petri-net based safety analysis of process systems

Brake is a safety critical system for railway vehicles and brake failures have caused many catastrophic accidents in the history. Detailed accident investigation reports are available and National Transportation Safety Board (NTSB) also makes safety recommendations to Federal Railroad Administration and the industry. However, there is limited research on how to improve the brake safety from the perspective of design, system integration and safety analysis. In this paper, a framework for braking safety design and analysis is introduced, which includes four parts: failure alarming system, safety design, safety analysis and preventative maintenance. For failure alarming, according to the severity level, the failures will be notified to the operator, to Operation Control Center (OCC) or saved for the maintainer. For safety design, redundant design for fail-safe feature, automatic braking, brake release, weight control, ergonomics design for easy operation and maintenance are discussed and several application examples are illustrated. In the safety analysis section, Preliminary Hazard Analysis (PHA) as a semi-quantitative analysis, Failure Modes, Effects, and Criticality Analysis (FMECA) as a bottom-up method and Fault Tree Analysis as a top-down method are used. The hazards details, system assurance actions and closure references are recorded in the Hazard Tracking Log (HTL) to ensure all the safety related items are well tracked and documented. Preventative Maintenance (PM) which is regularly performed on the brake components to lessen the likelihood of failing is also discussed in combination with the reliability prediction and safety analysis for a balance of safety and economy. The safety design framework and principles introduced in this paper can also be applied into other railway systems, such as Propulsion, Signaling, Doors, etc. and may provide insights to similar industries such as automotive, energy and so on.

Dynamic safety analysis of process systems using nonlinear and non-sequential accident model

The growing size and complexity of software in embedded systems poses new challenges to the safety assessment of embedded control systems. In industrial practice, the control software is mostly treated as a black box during the system's safety analysis. The appropriate representation of the failure propagation of the software is a pressing need in order to increase the accuracy of safety analyses. However, it also increase the effort for creating and maintaining the safety analysis models (such as fault trees) significantly. In this work, we present a method to automatically generate Component Fault Trees from Continuous Function Charts. This method aims at generating the failure propagation model of the detailed software specification. Hence, control software can be included into safety analyses without additional manual effort required to construct the safety analysis models of the software. Moreover, safety analyses created during early system specification phases can be verified by comparing it with the automatically generated one in the detailed specification phased.

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.

Despite the increasing number of accidents in process industry caused by human error, there are still too few efforts devoted to this area. This is mainly caused by people's tendency to overestimate human's capability in interacting with their working environment and moreover by the unavailability of reliable analysis methods.Because of the current lack of adequate methods, human factors (HF) analysis is not widely performed in process industry. Some HF techniques developed in the process industry were examined regarding their practical applicability and were unfortunately proved to be unsuitable for an elaborate HF analysis. Therefore, a new approach was developed, which provides a systematic way in performing a qualitative HF analysis to achieve a safer operation and decrease the number of human failure events.HF consideration during the design of a process plant is the key to minimize accidents caused by human error in process industry. Thus, an approach to incorporate HF into design phase is described in this article, which can help achieving a safer operation as early as possible with minimized costs. © 2009 American Institute of Chemical Engineers Process Saf Prog 2009

Recent Railway Industry Accidents: Learning Points for the Process Industries

Safety analysis is a key activity for the development of railway transportation systems. The analysis is used not only to determine whether new systems do not expose the general public to unduly high levels of risks, but also to inform the development process itself through identification and allocation of appropriate requirements. Whilst inadequate and inaccurate safety analysis may have potentially catastrophic consequences, it is rarely validated in practice. This paper presents a case for validation of safety analysis of the railway systems along with a technical approach to such validation. The approach is based on the concept of Failure Injection and the Lightweight Refinement relation. The paper further argues that the safety analysis validation should be embedded in a wider uncertainty management framework and shows how this can be made consistent with the spirit of the existing safety standards of the railway domain.

Architectural design modeling has emerged as a discipline in a complex system development. To implement early safety analysis, techniques for architectural design have been extended to concern the safety property. Various safety standard profiles, quantitative and qualitative analysis methods are proposed for assessment. However, few of them focuses on the feedback of the safety properties or analysis results on the adjustment to improve original architecture. In this paper, we present an approach to combine safety analysis with architecture modeling. First, we extend the meta-model of our architecture description language - Breeze/ADL with safety elements for design. Second, safety specifications are generated from Breeze/ADL, and then to be converted into Open FTA for FTA (Fault Tree Analysis). Our Breeze/ADL also supports rule definitions to adjust the architecture, to cope with safety problems. Moreover, model checking will be applied to verify the correctness of the adjustment. Finally, the tool Breeze/SA demonstrates the feasibility of our approach.

Software Product Line Engineering (SPLE) has been proven to reduce development and maintenance costs, improving the time-to-market, and increasing the quality of product variants developed from a product family via systematic reuse of its core assets. SPLE has been successfully used in the development of safety-critical systems, especially in automotive and aerospace domains. Safety-critical systems have to be developed according to safety standards, which demands safety analysis, Fault Tree Analysis (FTA), and assurance cases safety engineering artefacts. However, performing safety analysis, FTA, and assurance case construction activities from scratch and manually for each product variant is time-consuming and error-prone, whereas variability in safety engineering artefacts can be automatically managed with the support of variant management techniques. As safety is context-dependent, context and design variation directly impact in the safety properties changing hazards, their causes, the risks posed by these hazards to system safety, risk mitigation measures, and FTA results. Therefore, managing variability in safety artefacts from different levels of abstraction increases the complexity of the variability model, even with the support of variant management techniques. To achieve an effective balance between benefits and complexity in adopting an SPLE approach for safety-critical systems it is necessary to distinguish between reusable safety artefacts, whose variability should be managed, and those that should be generated from the reused safety artefacts. On the other hand, both industry and safety standards have recognized the use of model-based techniques to support safety analysis and assurance cases. Compositional safety analysis, design optimization, and model-based assurance cases are examples of techniques that have been used to support the generation of safety artefacts required to achieve safety certification. This thesis aims to propose a model-based approach that integrates modelbased development, compositional safety analysis, and variant management techniques to support the systematic reuse and generation of safety artefacts in safety-critical software product line engineering. The approach contributes to reduce the effort and costs of performing safety analysis and assessment for a particular product variant, since such analysis is performed from the reused safety artefacts. Thus, variant-specific fault trees, Failure Modes and Effects Analysis (FMEA), and assurance case artefacts required to achieve safety certification can be automatically generated with the support the model-based safety analysis and assurance case construction techniques.

Methodology development for safety and reliability analysis for electrical mine monitoring systems

Varied aspects of fire and explosion accidents in process industries were reviewed mainly from safety viewpoints. This review consists of (1) introduction, (2) terminology, (3) ignition sources, (4) clasification of explosion; physical explosion, deflagration and detonation with some case studies, (5) effects of explosion, scale law of blast waves and (6) measures for loss prevention.

Occupational Application Modernization of process plants has replaced traditional machine control with sophisticated computerized control, with the work required of control room operators changing from predominantly physical to cognitive. As a result, excessive cognitive workload during an abnormal condition is not an uncommon situation. Almost 70% of accidents in process industries are the result of human error, which is largely modulated by high cognitive workload. A context-dependent methodology using pupillometry was adopted in this study for workload assessment. We found that workload has a significant effect on task performance and subsequent success in handling an abnormal condition. Incorporating contextual information along with pupillometry-based measures was useful to explore the dynamics of variations in workload in depth. In addition, the proposed methodology is a more reliable method for a dynamic environment in which the situation evolves with operator interactions with the process. Technical : Background: Operator workload monitoring has become an important aspect of system engineering due to ever increasing cognitive demands in the control room. Higher cognitive workload, beyond capability, is directly associated with human error in plant operations. Even a small increase in workload during peak demand may result in human error, which can endanger the safety of a process plant. Purpose: Subjective methods are of limited use due to the requirement for near real-time evaluation of cognitive workload. Applications such as process plant control room require the operator to reiterate and re-represent the situation based on the contextual cues from environment. Hence, our objective was to develop and test a methodology that incorporates contextual information in workload measurement using pupillometry. Method: Participants (n = 44) performed simulated process control tasks. Pupil size was recorded using an eye-tracking device. Recorded pupil size was analyzed based on a methodology that incorporates contextual information from the human-machine interface. Events that present new information about the current state of the process were categorized as critical events. Pupil size variation was adopted to provide an estimate of cognitive workload between consecutive critical events. Results: Cognitive workload was associated with process behavior and operator actions. An increase in cognitive workload for specific events was observed when participant actions deteriorated process conditions. We also observed that overall task performance was associated with the frequency of certain events and corresponding variations in pupillary behavior. Conclusion: Incorporating contextual information provides more detailed insights into the dynamics of variations in cognitive workload. The mental representation of a current situation may vary depending on expertise level. The proposed methodology assesses such dynamic mental representations in the form of frequency of critical events and corresponding changes in the cognitive workload that ultimately determines the likelihood of an operator successfully completing a task.

Petri-net based cascading effect analysis of vapor cloud explosions

Automatic safety analysis of control systems

In the first part of the article is a methodology for implementing a model-driven safety analysis of dynamical technology systems. The safety analysis is performed in the development of control system, mainly aiming at critical processes of system operation. I divided my methodology into five steps. These steps of the methodology was carried out in a hierarchical sequence. The objective of the second part of the article is to demonstrate the principle of the SQMD method concept for performing safety analysis on the example of a dynamical system. By SQMD method will be developed a models of safety-critical processes by which they will be carried out on-line monitoring. The method combining qualitative and quantitative procedures of modelling and taking both methods advantages.