7 research outputs found
Automated evolutionary design of self-assembly and self-organising systems
Self-assembly and self-organisation are natural construction processes where the spontaneous formation of aggregates emerges throughout the progressive interplay of local interactions among its constituents. Made upon cooperative self-reliant components, self-assembly and self-organising systems are seen as distributed, not necessarily synchronous, autopoietic mechanisms for the bottom-up fabrication of supra-structures. The systematic understanding of how nature endows these autonomous components with sufficient ''intelligence'' to combine themselves to form useful aggregates brings challenging questions to science, answers to which have many potential applications in matters of life and technological advances. It is for this reason that the investigation to be presented along this thesis focuses on the automated design of self-assembly and self-organising systems by means of artificial evolution. Towards this goal, this dissertation embodies research on evolutionary algorithms applied to the parameters design of a computational model of self-organisation and the components design of a computational model of self-assembly. In addition, an analytical assessment combining correlation metrics and clustering, as well as the exploration of emergent patterns of cooperativity and the measurement of activity across evolution, is made. The results support the research hypothesis that an adaptive process such as artificial evolution is indeed a suitable strategy for the automated design of self-assembly and self-organising systems where local interactions, homogeneity and both stochastic and discrete models of execution play a crucial role in emergent complex structures
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A Cloud-based Framework for Shop Floor Big Data Management and Elastic Computing Analytics
Advanced digitalization together with the rise of disruptive Internet technologies are key enablers of a fundamental paradigm shift observed in industrial production. This is known as the fourth industrial revolution (Industry 4.0) which proposes the integration of the new generation of ICT solutions for the monitoring, adaptation, simulation, and optimisation of factories. With the democratization of sensors and actuators, factories and machine tools can now be sensorized and the data generated by these devices can be exploited, for instance, to optimise the utilization of the machines as well as their operation and maintenance. However, analyzing the vast amount of generated data is resource demanding both in terms of computing power and network bandwidth, thus requiring highly scalable solutions. This paper presents a novel big data approach and analytics framework for the management and analysis of machine generated data in the cloud. It brings together standard open source technologies and the exploitation of elastic computing, which, as a whole, can be adapted to and deployed on different cloud computing platforms. This enables reducing infrastructure costs, minimizing deployment difficulty and providing on-demand access to a virtually infinite set of computing power, storage and network resources.H202
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Digital Manufacturing on a Shoestring - Low cost digital solutions for SMEs
This paper introduces the Digital Manufacturing on a Shoestring programme as a whole and demonstrates the way in which it addresses the need for low cost digital solutions for SME Manufacturers. It discusses challenges associated with integrating low cost technologies into industrial solutions and the style of IT architectures best suited for integrating these solutions into industrial environments.Engineering and Physical Sciences Research Council [grant number EPSRC: EP/R032777/1
Automated evolutionary design of self-assembly and self-organising systems
Self-assembly and self-organisation are natural construction processes where the spontaneous formation of aggregates emerges throughout the progressive interplay of local interactions among its constituents. Made upon cooperative self-reliant components, self-assembly and self-organising systems are seen as distributed, not necessarily synchronous, autopoietic mechanisms for the bottom-up fabrication of supra-structures. The systematic understanding of how nature endows these autonomous components with sufficient ''intelligence'' to combine themselves to form useful aggregates brings challenging questions to science, answers to which have many potential applications in matters of life and technological advances. It is for this reason that the investigation to be presented along this thesis focuses on the automated design of self-assembly and self-organising systems by means of artificial evolution. Towards this goal, this dissertation embodies research on evolutionary algorithms applied to the parameters design of a computational model of self-organisation and the components design of a computational model of self-assembly. In addition, an analytical assessment combining correlation metrics and clustering, as well as the exploration of emergent patterns of cooperativity and the measurement of activity across evolution, is made. The results support the research hypothesis that an adaptive process such as artificial evolution is indeed a suitable strategy for the automated design of self-assembly and self-organising systems where local interactions, homogeneity and both stochastic and discrete models of execution play a crucial role in emergent complex structures.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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Towards a Comparison of Low-Cost Technologies for Monitoring the Consumption of Power
The cost of energy has skyrocketed worldwide and monitoring the consumption of electricity could help save money that, in turn, could be invested somewhere else. From individual devices like CNC machines to sets of equipment such as packaging rooms, manufacturing companies are now keen to explore if there are reasonable efficiency processes in place. However, there are many ways to do this. On the one hand, manufacturing companies could look at the half an hour metered electricity records coming from their energy suppliers. However, this might be a coarse grain picture of consumption that discloses very little about individual devices. One of the many alternative options would be retrofitting a digital infrastructure to support power monitoring solutions across the shopfloor. However, this could, arguably, represent a significant financial investment to small and medium enterprises (SMEs). Low-cost technologies like sensors, microcomputers and microcontrollers have been available for many years giving birth to so many familiar devices like mobile phones, voice controlled speakers, smart tv sets, etc. Yet most manufacturing SMEs are still non-digital because of barriers such as the lack of digital skills in the workforce or unforeseen economic costs. Thus, this paper proposes to explore and compare a set of solutions built to monitor electrical power consumption using off-the-shelf low-cost technologies, and with the aim to shed light on technological features as well as market availability and accuracy
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Student Hackathons for Low Cost Digital Solutions
Academic research projects often face challenges when trying to deliver innovation in a fast and creative way. In particular, projects of multidisciplinary nature that look at cross domain aspects applied in industry may take longer to expect. This paper addresses such an issue in the area of low cost digital solution development and proposes an approach using student hackathons as a mean to enable rapid prototypes of low cost digital solutions for manufacturing SMEs. It highlights how these fast-paced activities could be seen as additional options to help students foster technical and soft skills ahead of working in industrial environments.Research England’s Connecting Capability Fund award CCF18-7157 - Promoting the Internet of Things via Collaboration between HEIs and Industry (Pitch-In
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Designing Shoestring Solutions: An Approach for Designing Low-Cost Digital Solutions for Manufacturing
This paper examines the design of low-cost digital solutions for manufactur-ing. A set of criteria are established that take into account the limited design-er experience and limited time budget that accompany a low-cost project. Al-ternatives are assessed and a design approach is proposed that addresses these criteria using a set of identified features. Development of the proposed approach is not yet complete, however it already provides a simple, accessi-ble, and streamlined method for implementing low-cost digital solutions