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)

Abstract

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
• Status: Published
• Refereed: Yes
• 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
• Publisher: Springer-Verlag
• ISSN: 0268-3768
• ISSN (Online): 1433-3015