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Title: Modelling industrial systems : sustainability, complexity and evolutionary processes
Author: Baldwin, James Scott
ISNI:       0000 0001 2388 7546
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2004
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New ideas, concepts and understanding that are currently emerging from the science of complex systems are beginning to challenge the way people think about and model industrial systems. In addition, sustainable development and industrial ecology are now two of the most popular concepts with which to understand and represent sustainable industrial systems. In bringing all three of these areas of research together and with a specific focus on the industrial region of Sheffield and South Yorkshire, two theoretical models of sustainable systems are developed with an underlying argument of homology rather than the typical analogy. The aim is to reconcile understanding, in physics, biology, ecology, and the industrial process. Hypotheses of homology are tested on the emergent patterns found in both natural and industrial systems - patterns in energy intensities, production and recycling, diversification, organisational life histories and selection pressures, and systemic stability. The model is then used to examine regional decline and sustainable industrial regeneration in the South Yorkshire region of the UK. Building on these models, the cladistic evolution of manufacturing technologies and practices is modelled through simulation. Manufacturing cladistics was first developed not only as a means of classifying manufacturing organisations but also, and perhaps more importantly, as a tool to both help deal with change, and use as a guide for organisational re-engineering. However, this approach has one major limitation - it is only a description of the past; the future is not represented. Uncertainty in decision-making and unknown barriers are thought to be major inhibitors behind the introduction of important innovations in technical, organisational and social domains. This thesis reports on the results of a study that interprets two complimentary, but currently unrelated, areas of research, manufacturing cladistics and evolutionary systems methodology. This new framework enables the exploration of evolutionary processes involved in the interactions of technologies and practices, facilitating decision-making as well as the exploration of new organisational structures.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available