Modelling industrial systems : sustainability, complexity and evolutionary processes.

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.