Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566500
Title: A SoA-based monitoring approach : towards energy efficient automation
Author: Cachapa Vieira, Daniel
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2012
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Abstract:
The field of industrial automation is ripe for modernization. With the advent of mass customization and increasingly shorter product lifecycles, production lines have to be more agile than ever. At the same time, the entire fabric of the Enterprise is changing from a strong hierarchical framework towards flatter structures in order to facilitate closer interactions between business strategy and operations. Moreover, energy costs are rising at an unprecedented rate while environmental concerns cause emissions regulations to be ever stricter. This dissertation describes a body of research which has been done on applying the concept of Service-oriented Architecture to industrial automation. In this work, a great deal of concern is given to production simulation systems and how innovations using SoA-based components can turn these tools from an aid during the production line design phase, to an indispensible part of the complete production lifecycle. This document explores how to build such innovations directly on top of existing tools, and how the new interaction paradigms can be explored for the benefit of the production engineer, by simulating production with multiple SoA-based devices, and then exporting that same control logic to the real world, even connecting virtual devices to real ones seamlessly. Those same principles are then exploited to tackle the issue of energy efficiency in the production line, using production simulation as a framework where different production scenarios and energy-saving strategies can be tested out. These experiments benefit greatly from the modular, SoA-based simulation environment, which is flexible enough to quickly adapt to any number of scenario variables, and extract relevant data. Using the tool, a number of strategies are developed and tested with encouraging results. Those findings serve as a testament to the value of applying modern state of the art research and technologies to the very competitive field of production automation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.566500  DOI: Not available
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