Novel functional availability analysis technique using system algebra for safety critical systems

Abstract

,Systems around us are often complex in design and functionality, and futuristic systems are going to be even more complex. There is a need to incorporate more formal method (FM)-based tools and techniques to fundamentally raise the bar with systems engineering processes, for lowering cost and time while increasing the safety assurance of complex systems. Such tools and techniques address problem spaces like generation of an integrated formal framework, a tool-based formal workbench, synthesis of critical functionalities, and real-life challenges. There already exist various FM-based tools and techniques being incorporated into various phases of the systems engineering process in order to address real-life system challenges. The research reported in this thesis adds a novel technique to the existing repertoire of systems engineering, to help increase the safety assurance level during the design of safety-critical systems. Modern systems in critical applications, such as net-centric warfare and aerospace cyber-physical systems, are multi-functional. The availability requirements of these complex systems are very high. An ability to predict the future functional availability of a system given its design, and to achieve an assurance of a desired level of functional ability during design, are thus of much importance for safety-critical systems. The functional availability of a system, if known early on, can be used to better understand the pros and cons of the design and to detect design anomalies, which in turn leads to improvements in the design and life-cycle processes. There is a need for such a technique to detect design anomalies early on in the engineering process, to improve the design phase. This thesis proposes a novel FM-based technique for analyzing functional availability of a system. The functional availability is determined using theSystem Algebra (SA) FM. The SA technique uses the concept of a System State Machine (SSM) to compute system states and transitions between them over the life of a system. In the SA technique, a mathematical model is generated to represent the system under analysis. The relationships between different sub-systems of a system are modeled using this mathematical model by generating an SA expression. Applying operations on the SA expressions enables understanding of the system. As per SA, a system exists in one of the three states: the safe state, the hazardous state, and the unsafe state. The related SSM concept determines and analyzes the system state and its transition from one state to another over time, influenced by the failure of various sub-systems and components. The system state at any instant is determined by the health of its components and the states of its sub-systems. The health of a component is determined by its failure rate. Over time, as components start failing, the sub-systems degrade, thus degrading the overall system due to unavailable functionality. With SSM analysis, the design can be improved for better functional availability. This technique can help designers better understand system behavior and detect design anomalies. The system state and its transition determine the control flow between system states, and related changes in system functionality. The proposed integrated design framework based on the SA technique has been automated to make the systems engineering process faster, more effective, and easier to implement. A design tool is being developed for easy plugin into any engineering framework. The design framework has been validated by applying the technique for analyzing the design of existing safety-critical systems in different domains. In addition, the efficacy of the modified design framework has been validated by implementing it on completely new safetycritical aerospace systems. The SA technique introduced in the design phase of the integrated formal framework is seen to improve the performance of the process as compared to the conventional and model-based systems engineering framework.