Assad, Fadi (2021) A component-based design approach for energy flexibility management in cyber-physical systems. PhD thesis, University of Warwick.

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Abstract

Traditional production and manufacturing systems are aimed at agility and responsiveness to customer demands. However, sustainability has become a new target that now accompanies the high productivity and quality goals required by manufacturing companies. To this end, energy flexibility emerges as a viable solution that attempts to satisfy all these requirements by the best management of the available energy resources including renewable energies in the context of manufacturing needs.

Following Industry 4.0 revolution, manufacturing processes and systems are being reshaped taking advantage of the advancements in information and communication technologies. Therefore, reaching the manufacturing system’s targets of sustainability and productivity takes new means of implementation. As smart manufacturing environments produce remarkable amounts of data, harnessing the resultant data has a significant impact on these targets.
A vital goal of this work is to contribute a new method of managing energy flexibility in digital manufacturing. Unlike the research reported in recent literature, low-level component control is the point of focus. This stems from manufacturing systems’ design vision by embedding energy flexibility in the component design. On the way to accomplish this, the theoretical foundation of energy flexibility, manufacturing flexibility and reconfigurability are explained.

Using virtual engineering as a viable system design tool, a research methodology that guarantees the realisation of energy-flexible components of cyber-physical systems is constructed. A digital twin of the energy-flexible component is developed to proactively embed energy flexibility, and interactively exchange data with the physical counterpart. In addition, external services in terms of using Deep Learning and Particle Swarm Optimisation were connected to the digital twin, and could contribute to real-time decision-making.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering
Library of Congress Subject Headings (LCSH):	Energy consumption, Industry 4.0, Cooperating objects (Computer systems), Digital twins (Computer simulation), Cybernetics
Official Date:	October 2021
Dates:	Date Event October 2021 UNSPECIFIED
Institution:	University of Warwick
Theses Department:	Warwick Manufacturing Group
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Harrison, Robert (Professor) ; Rushforth, Emma
Sponsors:	University of Warwick
Format of File:	pdf
Extent:	xxiv, 188 leaves : illustrations, charts
Language:	eng

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