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Abstract
The landscape of production has evolved drastically from its nascency. The emergence of diversedemand, globalization, environmental and alternative aspects of the global economy, constitutes greater
complexity in manufacturing. The need for companies to stay competitive warrant robust business models
and systems capable of accommodating uncertainty in markets. Increased attention to sustainability
in manufacturing is promoting remanufacturing directives poised to extend product service life which
could present uncertainty in supply. This paper proposes a framework/modeling approach to equip manufacturing
systems to respond to uncertainty in market demand and supply, with motivation nested in
remanufacturing techniques that mitigate compromise in stakeholder requirements whilst accommodating
more sustainable practice. The proposed production model implements Bayesian inferential methods
to enable data driven capability in the model accounting for uncertainty, heuristics methods in the form
of genetic algorithms for adaptability to system deliverables, and discrete modeling approaches to simulate
shop floor behaviour through the generation of sample paths. This report provides an extensive
overview of contemporary manufacturing phenomena in industry and research pertinent to sustainability,
intended to present a clearer view of the landscape and where the research lays.