Engineering failure analysis and design optimisation with HiP-HOPS

Abstract

The scale and complexity of computer-based safety critical systems, like those used in the transport and manufacturing industries, pose significant challenges for failure analysis. Over the last decade, research has focused on automating this task. In one approach, predictive models of system failure are constructed from the topology of the system and local component failure models using a process of composition. An alternative approach employs model-checking of state automata to study the effects of failure and verify system safety properties.In this paper, we discuss these two approaches to failure analysis. We then focus on Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) -one of the more advanced compositional approaches -and discuss its capabilities for automatic synthesis of fault trees, combinatorial Failure Modes and Effects Analyses, and reliability versus cost optimisation of systems via application of automatic model transformations.We summarise these contributions and demonstrate the application of HiP-HOPS on a simplified fuel oil system for a ship engine. In light of this example, we discuss strengths and limitations of the method in relation to other state-of-the-art techniques. In particular, because HiP-HOPS is deductive in nature, relating system failures back to their causes, it is less prone to combinatorial explosion and can more readily be iterated. For this reason, it enables exhaustive assessment of combinations of failures and design optimisation using computationally greedy meta-heuristics.

Variability Management in Safety-Critical Software Product Line Engineering

“…Such variation may be further propagated throughout the decomposition of SILs allocated to hazards throughout contributing failures modes and components. Variation in SIL decomposition, which can be performed with automated tool support [30], is outside the scope of this paper. It is important to highlight that when developing reusable components, all variability aspects of a component should be considered from the initial stages of the SPL lifecycle, and the most stringent SIL assigned to that component in different contexts should be assigned to that component to ensure its safety usage across the SPL.…”

“…The adoption of an SPLE approach for developing safety-critical systems demands the integration of safety engineering into SPLE processes [14,28]. Compositional dependability analysis techniques [6,27,30] provide the automated support for safety engineering, and seamless integration between system design and dependability analysis. Thus, system design and dependability analysis can be performed in a single model, contributing to reduce the complexity of the product line dependability analysis.…”

“…Existing variability management techniques [1,15,17,32,33,34] provide support for managing variation at requirements, architecture, components, source code, and test cases. However, these techniques were not originally designed/or used to support variability management in dependability models developed with the support of compositional analysis techniques, e.g., OSATE AADL [6], HiP-HOPS [30], and CHESS [27].…”

Automatic optimisation of system architectures using EAST-ADL

“…HiP-HOPS has contributed to this area by enabling the optimisation of systems that have a networked architecture (i.e. they are not necessarily in parallel/series configurations as in RBDs) and by overcoming the traditional assumption made in RBDs that a component or system either works or fails in a single failure mode [PW1,AP1].…”

A Safety Analysis Approach to Clinical Workflows: Application and Evaluation

“…The model optimisation capability of HiP-HOPS [17] can also produce different alternative models to help to achieve safety requirements, and in doing so it can assist in selecting component and subsystems among different alternatives as well as helping to decide the level and location of replicated components.…”