The increasing demand for customization, reduced time to market and globalization are the real challenges for
today’s manufacturing enterprises (MEs). Therefore MEs can reduce these competitive pressures by becoming more
and more change-capable. The agile and lean manufacturing philosophies must complement the application of
reconfiguration techniques. However, choosing and applying the best philosophies and techniques are far from being
well understood and well structured processes because most MEs deploy complex and unique configurations of
processes and resource systems, and seek economies of scope and scale in respect of a number of distinctive product
flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component
based manufacturing systems are required to design, engineer and change next generation MEs. This paper discusses
research aimed at developing and prototyping a model-driven environment for the design, optimization and control of
enterprises with an embedded capability to handle various types of change in an example of a production planning
and control (PPC) scenario. The developed environment supports the engineering of common types of strategic,
tactical and operational process found in many MEs. Also reported are initial findings of manufacturing case study
work in which coherent multi-perspective models of a specific ME have facilitated process reengineering and
associated resource system configuration and interoperation. In order to understand the system prior to realisation of
any PPC strategy, multiple process segments of organisations need to be modelled. The paper considers key PPC
strategies and describes a novel systematic approach to create coherent sets of unified models that facilitate the
engineering of PPC strategies. Case study models are presented with capability to enable PPC decision making
processes in support of complex organisation design and change (OD&C). The paper outlines key areas for future
research including the need for research into unified modelling approaches and interoperation of partial models in
support of complex OD&C.
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