This paper presents a novel architecture for offering a proactive decision support in the increasingly dynamic and flexible manufacturing environments. The managers need tools that may offer them intelligent support in the complex systems that ask for an effective and responsive managemmt. We have developed SAMIN architecture and a supporting tool set (Simulation Asisted _Models for proactive support in _Intelligent _Manufacturing Systems) to meet these needs. This arhitecture supports the concepts of phased developmeots in flexibility, integration and automation required by industry to develop towards CIM systems. The role of IT in this architecture is seen as an opportunity to improve the decision system and decision information synchronisation so that the inherent flexibility in the evolving CIM environments can be intelligently exploited. We believe such efforts will contribute towards IT supported intelligent Manufacturing Systems. The development of the toolset is focused on an industrial case study of a telephone manufacturing company, using real life data to build and evaluate various models. The results of the study indicate that, while a simulation based toolset provides a proactive knowledge generation environment for more effective decision making, it is important to minimize the decision delays involved in finding the desired solution. Towards this, the application of Artificial Neural Networks (lo replace the simulator), Simulated Annealing (for optimization of desired parameters using simulator as well as ANN as a test bed) and Taguchi Methods (to optimize the simulation experimentation and to ensure focus on important factors), have been found to be very useful in enhancing the decision responsiveness.
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