Proceedings of the 1998 Winter Simulation Conference

Monitoring and improving the performance of complex distributed simulations can be challenging. Without proper software tools, the process of performance tuning could be complicated and tedious. This paper presents a new approach for visualizing the performance of distributed simulations. In particular, a formal methodology for constructing a visualization is presented, which includes a formal model for visualization and a systematic approach for identifying performance issues. This paper also presents results of a controlled evaluation of a prototype visualization created using the new methodology

Proceedings of the 1998 Winter Simulation Conference

Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or the nature of the relationships between the factors and the outputs can not be easily identified

Proceedings of the 1998 Winter Simulation Conference

Simulation is used to verify the feasibility of the design of manufacturing cells. The cell design, which combines new and existing machines in a component manufacture, is presented, showing the difficulties that can result with such a system. Simply changing the layout (arranging machines into cells) could provide some benefits, but these benefits were offset by a high level of required investment. The reasons for the increased costs include poorly matched cycle times, machine downtimes, complex material handling and long changeovers. Improvements in machine and material handling designs were found to be necessary in order to increase cell performance and reduce investment to a feasible level

Proceedings of the 1998 Winter Simulation Conference

Many simulation models include elements of human decision making which present some difficulty to the simulation modeller. It is often difficult to determine how a human goes about making decisions, and even where this is possible, representing this within the constructs of a simulation package may be problematic. In this paper an expert systems approach to representing the human decision maker is proposed. An example of an expert system linked to a simulation model is given. Not only was it possible to train the expert system by programming a set of decision rules, but also by obtaining examples of decisions through running and interacting with the simulation model. The paper concludes by discussing the future directions of this research