Customer oriented production planning at an integrated steel works
Date
2016-07-20
Authors
Besteiro, L M L
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Abstract
Developers of decision support systems for production planning domains often encounter
ill-structured problems that arc characterised by uncertairrty. This report describes a
knowledge-based decision modelling approach which successfully addressed these issues at
a steelmaking plant. All planning knowledge was reduced to a set of hard and soft
constraints explicitly derived from the relevant domain experts. A prototype system was
designc.l which allowed the operators to vary the relative priorities of the soft construints
according to the often unstable requirements of the various stukeltolders in the planning
decision process,
Soft constraint inferencing was modelled in two ways - a binary heuristic approach and a
fuzzy constraint analysis. The tWI) approaches arc evaluated and compared. The binary
heuristic approach enforced a rigid semantic partitioning of the constraint spaces. The
cOllsequelll/}.I!{IIIl'lltatioll of the problem resulted in a prohibitively complex system, which
provided neither consistent nor reliable decision support.
The fuzzy constraint analysis provided significantly improved results. It allowed an
intuitive representation of soft constraint semantics. Uncertainty was represented as all
intrinsic part of the decision model. The rule base was significantly reduced and the
inference rules were closet' to the manner in which the domain experts reason about the
problem. The operators were able to effectivel» impose their variable decision criteria on
the model.
Description
A dissertation submitted to the faculty of Engineering, University of the
Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of
l\:aster o'' Science in Englneerlng
Johannesburg, 1997