Automated system design optimisation

The focus of this thesis is to develop a generic approach for solving reliability design optimisation problems which could be applicable to a diverse range of real engineering systems. The basic problem in optimal reliability design of a system is to explore the means of improving the system reliability within the bounds of available resources. Improving the reliability reduces the likelihood of system failure. The consequences of system failure can vary from minor inconvenience and cost to significant economic loss and personal injury. However any improvements made to the system are subject to the availability of resources, which are very often limited. The objective of the design optimisation problem analysed in this thesis is to minimise system unavailability (or unreliability if an unrepairable system is analysed) through the manipulation and assessment of all possible design alterations available, which are subject to constraints on resources and/or system performance requirements. This thesis describes a genetic algorithm-based technique developed to solve the optimisation problem. Since an explicit mathematical form can not be formulated to evaluate the objective function, the system unavailability (unreliability) is assessed using the fault tree method. Central to the optimisation algorithm are newly developed fault tree modification patterns (FTMPs). They are employed here to construct one fault tree representing all possible designs investigated, from the initial system design specified along with the design choices. This is then altered to represent the individual designs in question during the optimisation process. Failure probabilities for specified design cases are quantified by employing Binary Decision Diagrams (BDDs). A computer programme has been developed to automate the application of the optimisation approach to standard engineering safety systems. Its practicality is demonstrated through the consideration of two systems of increasing complexity; first a High Integrity Protection System (HIPS) followed by a Fire Water Deluge System (FWDS). The technique is then further-developed and applied to solve problems of multi-phased mission systems. Two systems are considered; first an unmanned aerial vehicle (UAV) and secondly a military vessel. The final part of this thesis focuses on continuing the development process by adapting the method to solve design optimisation problems for multiple multi-phased mission systems. Its application is demonstrated by considering an advanced UAV system involving multiple multi-phased flight missions. The applications discussed prove that the technique progressively developed in this thesis enables design optimisation problems to be solved for systems with different levels of complexity. A key contribution of this thesis is the development of a novel generic optimisation technique, embedding newly developed FTMPs, which is capable of optimising the reliability design for potentially any engineering system. Another key and novel contribution of this work is the capability to analyse and provide optimal design solutions for multiple multi-phase mission systems. Keywords: optimisation, system design, multi-phased mission system, reliability, genetic algorithm, fault tree, binary decision diagra

System design optimisation involving phased missions

The performance of a phased mission is defined as a succession of non-overlapping phases that constitute towards a continuous mission. The focus of this paper is to develop a method to construct an optimal design structure for a phased mission system when available resources are restricted and to ensure a minimal system failure probability throughout the whole mission. The implemented optimisation method employs fault tree analysis to represent the causes of failure in the system for each phase. Binary decision diagrams are used to quantify the failure probability of each phase and the whole mission, and a single objective genetic algorithm is chosen to solve the optimisation problem. Analysis of the optimisation process of a military vessel design during a training mission is presented and the obtained results are discussed

System failure minimisation using automated design optimisation

Safety systems are designed to prevent the occurrence and future development of hazardous situations. Consequences of the failure of a safety system varies from minor inconvenience and cost to personal injury, significant economic loss and death. The operation of a safety system can be improved by either introducing better performing components or by increasing the number of redundant components. At the same time, such design alterations can influence how available resources are utilized. The focus of this paper is to introduce a generic optimisation method for constructing an optimal design case for any safety system, with the aim of maximising its likelihood of functioning on demand and at the same time ensuring optimal usage of available resources. The analysed optimisation problem is represented as the constrained single objective problem. The implemented optimisation method employs Fault Tree Analysis (FTA) to represent system failure causes and Binary Decision Diagrams (BDDs) to quantify its failure probability. A Single Objective Genetic Algorithm (SOGA) has been chosen as the optimisation technique. The methodology is illustrated with the optimisation of a High Integrity Protection System (HIPS) design. The constraints imposed are on system dormant failure probability, cost and maintenance down time. Results of the application, with the generic implications of the analysis, are discussed

Phased mission failure minimisation using optimal system design

A phased mission system represents a system whose performance is divided into consecutive non-overlapping phases. The operation of a phased mission system can be improved by either introducing better performing components or by increasing the number of redundant components. At the same time, such design alterations can influence how available resources are utilised. The focus of this paper is to develop an optimisation method to construct an optimal design case for a phased mission system, with the aim of maximising its availability and ensuring optimal usage of available resources throughout all phases. The developed method is based on an approach where an individual phase is treated as a standard single phase system. Thus, to solve the whole phased mission optimisation problem each phase design is analysed individually, whilst dependencies between different phases are also included in the analysis in order to find the failure probability value of each phase. The implemented optimisation method employs Fault Tree Analysis (FTA) to represent system performance and Binary Decision Diagrams (BDDs) to quantify each phase failure probability. A Single Objective Genetic Algorithm (SOGA) has been chosen as the optimisation technique. A simple Unmanned Aerial Vehicle (UAV) mission has been selected to demonstrate the methods application. Results of the analysis are discussed

System design optimisation involving phased missions

A phased mission system represents a system where performance can be divided into consecutive non-overlapping phases. The operation of a phased mission system can be improved by introducing better performance components or adding more redundant ones. At the same time, such design alterations can influ-ence how available resources are utilised. The focus of this paper is to develop an optimisation method to construct an optimal design case for a phased mission system to maximise its availability with optimal usage of available resources considering all phases. The developed method is based on the approach that an individual phase can be treated as a standard single phase system. Thus, to solve the whole phased mission optimisation problem each phase design is analysed individually whilst to find each phase availability value dependencies between different phases are also included in the analysis. The implemented optimisation method employs Fault Tree Analysis (FTA) to represent system performance and Binary Decision Diagrams (BDDs) are used to quantify each phase failure probability. A Single Objective Genetic Algorithm (SOGA) has been chosen as the optimisation technique. A simple military ship mission has been chosen to demonstrate the methods application. Results of the analysis are discussed

Phased mission system design optimisation using genetic algorithms

A phased mission system represents a system whose performance is divided into consecutive non-overlapping phases. It is important to ensure safety of a phased mission system since the failure of it can have both life threatening and financial consequences. The focus of this paper is to develop an optimisation method to construct an optimal design case for a phased mission system, with the aim of minimising its unreliability and at the same time ensuring optimal usage of available resources throughout all phases. The introduced phased mission optimisation is represented as the constrained single objective problem. Here failure of the overall mission is the objective function and the introduced constraints are employed to determine the optimal use of resources. The implemented optimisation method employs Fault Tree Analysis to represent system performance and Binary Decision Diagrams to quantify each phase failure probability. A single objective Genetic Algorithm has been chosen as the optimisation technique. An Unmanned Aerial Vehicle mission has been selected to demonstrate the methods application. The results and the influence of modifications to the optimisation algorithm are discussed