The thesis introduces a new quantitative safety modelling approach for large scale socio-technical systems that exhibit Low Probability High Consequence (LPHC) accidents. This approach uses Bayesian Belief Networks (BBN) and overcomes inherent difficulties of current methods, difficulties that make these methods incapable of coping with complexities of socio-technical systems.

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Highly mobile people (HMPs) require flexible, reactive service delivery due to their regularly changing location and activities and the lack of a wired network connection. A mobile service delivery system should be able to detect relevant events that occur such as change of location, availability of new last-minute specials, sales opportunities and safety issues and then reactively take action in response to these events. This work describes a situation management ontology based framework for delivering such a system. Issues addressed include HMP and service states and events, context, situations and situation-action rules, and syntactically and semantically compatible XML ontologies for their specification. A generic situation management ontology is developed in OWL using the ontology development tool, Protégé. This ontology is combined with domain specific classes in the travel domain to create a travel situation management ontology that can be used as the basis for a ubiquitous mobile travel service application. Using a typical independent traveller scenario, the travel situation management ontology is instantiated to demonstrate its effectiveness. The flexibility of the generic situation management ontology is demonstrated by creating an academic situation management ontology by simply replacing a small number of domain specific classes. A framework is also proposed that is based on the situation management ontology, distributed, co-operating software agents, and context based filtering, and is suitable for mobile service delivery. The example framework uses the situation management ontologies developed in this work and action rules to link situation specification to situation detection and action. The ontologies and action rules are semantically consistent and are specified in the XML based, industry standard language, OWL, thus drawing together previous independent work in a number of diverse disciplines.

Highly mobile people (HMPs) require flexible, reactive service delivery due to their regularly changing location and activities and the lack of a wired network connection. A mobile service delivery system should be able to detect relevant events that occur such as change of location, availability of new last-minute specials, sales opportunities and safety issues and then reactively take action in response to these events. This work describes a situation management ontology based framework for delivering such a system. Issues addressed include HMP and service states and events, context, situations and situation-action rules, and syntactically and semantically compatible XML ontologies for their specification. A generic situation management ontology is developed in OWL using the ontology development tool, Protégé. This ontology is combined with domain specific classes in the travel domain to create a travel situation management ontology that can be used as the basis for a ubiquitous mobile travel service application. Using a typical independent traveller scenario, the travel situation management ontology is instantiated to demonstrate its effectiveness. The flexibility of the generic situation management ontology is demonstrated by creating an academic situation management ontology by simply replacing a small number of domain specific classes. A framework is also proposed that is based on the situation management ontology, distributed, co-operating software agents, and context based filtering, and is suitable for mobile service delivery. The example framework uses the situation management ontologies developed in this work and action rules to link situation specification to situation detection and action. The ontologies and action rules are semantically consistent and are specified in the XML based, industry standard language, OWL, thus drawing together previous independent work in a number of diverse disciplines.

Safety of the airborne platforms rests heavily on the way they are maintained. This maintenance includes repairs and testing, to reduce platform down time. Maintenance is performed using generic and specific test equipment within the existing maintenance management system (MMS). This thesis reports the work undertaken to improve maintainability and availability of avionics systems using an intelligent decision support system (IDSS). In order to understand the shortcomings of the existing system, the prevalent practices and methodologies are researched. This research thesis reports the development and implementation of an IDSS and the significant improvements made by this IDSS by integrating autonomous and independent information sources by employing a multi-agent system (MAS). Data mining techniques and intelligence agents (IA) are employed to create an expert system. The developed IDSS successfully demonstrates its ability to integrate and collate the available information and convert into valuable knowledge. Using this knowledge, the IDSS is able to generate interpreted alerts, warnings and recommendations thereby reasonably improving platform maintainability and availability. All facets of integrated logistics support (ILS) are considered to create a holistic picture. As the system ages, the IDSS also matures to assist managers and maintainers in making informed decisions about the platform, the unit under test (UUT) and even the environment that supports the platform.