A knowledge-based system for operations management in a small to medium sized enterprise

Chatwin, C. R., Abdullah, H. A. and Watson, I. A. (1996) A knowledge-based system for operations management in a small to medium sized enterprise. International Journal of Advanced Manufacturing Technology, 11(5), pp. 381-386. (doi:10.1007/BF01845697)

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Publisher's URL: http://dx.doi.org/10.1007/BF01845697


In recent years, there has been an increasing interest in the mechanisms and structure of scheduling in a computer-integrated manufacturing (CIM) environment. This has led to the development of new scheduling models, such as Petri nets, time-augmented Petri nets, fuzzy scheduling models and neural net scheduling models. A fundamental objective of any scheduling system is event synchronisation and optimisation of command, communication and control C3 between each active node of the overall CIM structure. CIM scheduling can be regarded as a nonlinear dynamic control process, whereby, the feed forward or feedback elements are the scheduling priorities that enable the manufacturing organisation to remain within a “steady-state” profit margin. However, in each different hierarchy level of the organisation, randomness phenomena in the C3 environment can be observed, i.e. events in a particular department or organisational level cause a perturbation elsewhere in the manufacturing organisation. Furthermore, these changes are constrained by the framework of rules pre-set by the organisational structure and business corporate strategy. To a first approximation, these cause-and-effect phenomena can be viewed as deterministic changes which may result in “deterministic chaos”. In this paper, a self-organising compensating information system (SOCIS) is presented. This system is designed utilising knowledge control modelling (KCM) topology with its architecture based on the principles of client-server and a second-order proportional-integral-differential knowledge-based management system (PID-KBMS).

Item Type:Articles
Glasgow Author(s) Enlighten ID:Watson, Dr Ian and Chatwin, Prof Christopher
Authors: Chatwin, C. R., Abdullah, H. A., and Watson, I. A.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:International Journal of Advanced Manufacturing Technology
ISSN (Online):1433-3015

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