Let’s augment the future together!:Augmented reality troubleshooting support for IT/OT rolling stock failures

The railway industry is moving to a socio-technological system that relies on computer-controlled and human-machine interfaces. Opportunities arise for creating new services and commercial business cases by using technological innovations and traffic management systems. The convergence of Information Technology (IT) with Operational Technology (OT) is critical for cost-effective and reliable railway operations. However, this convergence introduces complexities, leading to more intricate rolling stock system failures. Hence, operators necessitate assistance in their troubleshooting and maintenance strategy to simplify the decision-making and action-taking processes. Augmented Reality (AR) emerges as a pivotal tool for troubleshooting within this context. AR enhances the operator’s ability to visualize, contextualize, and understand complex data by overlaying real-time and virtual information onto physical objects. AR supports the identification of IT/OT rolling stock system failures, offers troubleshooting directions, and streamlines maintenance procedures, ultimately enhancing decision-making and action-taking processes. This thesis investigates how AR can support operators in navigating troubleshooting and maintenance challenges posed by IT/OT rolling stock system failures in the railway industry

Integrated application of compositional and behavioural safety analysis

To address challenges arising in the safety assessment of critical engineering systems, research has recently focused on automating the synthesis of predictive models of system failure from design representations. In one approach, known as compositional safety analysis, system failure models such as fault trees and Failure Modes and Effects Analyses (FMEAs) are constructed from component failure models using a process of composition. Another approach has looked into automating system safety analysis via application of formal verification techniques such as model checking on behavioural models of the system represented as state automata. So far, compositional safety analysis and formal verification have been developed separately and seen as two competing paradigms to the problem of model-based safety analysis. This thesis shows that it is possible to move forward the terms of this debate and use the two paradigms synergistically in the context of an advanced safety assessment process. The thesis develops a systematic approach in which compositional safety analysis provides the basis for the systematic construction and refinement of state-automata that record the transition of a system from normal to degraded and failed states. These state automata can be further enhanced and then be model-checked to verify the satisfaction of safety properties. Note that the development of such models in current practice is ad hoc and relies only on expert knowledge, but it being rationalised and systematised in the proposed approach – a key contribution of this thesis. Overall the approach combines the advantages of compositional safety analysis such as simplicity, efficiency and scalability, with the benefits of formal verification such as the ability for automated verification of safety requirements on dynamic models of the system, and leads to an improved model-based safety analysis process. In the context of this process, a novel generic mechanism is also proposed for modelling the detectability of errors which typically arise as a result of component faults and then propagate through the architecture. This mechanism is used to derive analyses that can aid decisions on appropriate detection and recovery mechanisms in the system model. The thesis starts with an investigation of the potential for useful integration of compositional and formal safety analysis techniques. The approach is then developed in detail and guidelines for analysis and refinement of system models are given. Finally, the process is evaluated in three cases studies that were iteratively performed on increasingly refined and improved models of aircraft and automotive braking and cruise control systems. In the light of the results of these studies, the thesis concludes that integration of compositional and formal safety analysis techniques is feasible and potentially useful in the design of safety critical systems

Operator interfaces for the lifecycle support of component based automation systems

Current manufacturing automation systems (specifically the powertrain sector) have been facing challenges with constant pressures of globalisation, environmental concerns and ICT (Information and Communication Technology) innovations. These challenges instigate new demands for shorter product lifecycles and require customised products to be manufactured as efficiently as possible. Manufacturing systems must therefore be agile to remain competitive by supporting frequent reconfigurations involving distributed engineering activities. [Continues.

Fabricate

Bringing together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation, Fabricate is a triennial international conference, now in its third year (ICD, University of Stuttgart, April 2017). Each year it produces a supporting publication, to date the only one of its kind specialising in Digital Fabrication. The 2017 edition features 32 illustrated articles on built projects and works in progress from academia and practice, including contributions from leading practices such as Foster + Partners, Zaha Hadid Architects, Arup, and Ron Arad, and from world-renowned institutions including ICD Stuttgart, Harvard, Yale, MIT, Princeton University, The Bartlett School of Architecture (UCL) and the Architectural Association

The application of modified adaptive landscapes to heuristic modelling of engine concept designs using sparse data

The automotive internal combustion engine industry operates in a sector that relies on high production volumes for economies of scale, and dedicated production equipment for efficiency of operations and control of quality, yet is subject to the vagaries of a dynamic marketplace, with the need for constant change. These circumstances place pressure on engine designs to be optimised at launch to be competitive and meet market needs, yet be adaptable to uncertain requirements for change over their production life. Engine designers therefore need concept configuration evaluation tools that can assess architectures for resilience to geometric change over the production life of the product. The problem of being resource efficient whilst having the capacity to adapt tochanging environments is one that has been addressed in nature. Natural systems have evolved strategies of satisficing conflicting requirements whilst being resource efficient. The theory of adaptive landscapes helps us to visualise the adaptive capacity of potential morphological forms. A concept attribute analysis methodology based on satisficing and adaptive landscapes has been developed and tested for application to engine concept design. The Plateau, Flooded Adaptive Landscape technique (PFAL),has been evaluated against exemplar engine life histories and shows merit in aiding the decision-making process for concept designers working with sparse data. The process lets the designer visualise the attribute map, enabling them to make better trade-off decisions and share these with non-expert stakeholders to gain their input in final concept choices

Multi-objective optimisation of safety-critical hierarchical systems

Achieving high reliability, particularly in safety critical systems, is an important and often mandatory requirement. At the same time costs should be kept as low as possible. Finding an optimum balance between maximising a system's reliability and minimising its cost is a hard combinatorial problem. As the size and complexity of a system increases, so does the scale of the problem faced by the designers. To address these difficulties, meta-heuristics such as Genetic Algorithms and Tabu Search algorithms have been applied in the past for automatically determining the optimal allocation of redundancies in a system as a mechanism for optimising the reliability and cost characteristics of that system. In all cases, simple reliability block diagrams with restrictive assumptions, such as failure independence and limited 2-state failure modes, were used for evaluating the reliability of the candidate designs produced by the various algorithms.This thesis argues that a departure from this restrictive evaluation model is possible by using a new model-based reliability evaluation technique called Hierachically Performed Hazard Origin and Propagation Studies (HiP-HOPS). HiP-HOPS can overcome the limitations imposed by reliability block diagrams by providing automatic analysis of complex engineering models with multiple failure modes. The thesis demonstrates that, used as the fitness evaluating component of a multi-objective Genetic Algorithm, HiP-HOPS can be used to solve the problem of redundancy allocation effectively and with relative efficiency. Furthermore, the ability of HiP-HOPS to model and automatically analyse complex engineering models, with multiple failure modes, allows the Genetic Algorithm to potentially optimise systems using more flexible strategies, not just series-parallel. The results of this thesis show the feasibility of the approach and point to a number of directions for future work to consider