A manufacturing control system configuration is defined by the number of parallel assembly cells slaved to a specific superior microprocessor, their superior microprocessor, and the associated microprocessors performance capacities. The above-mentioned items of configuration were explored in this research to derive their effects on the efficiencies of manufacturing celIs. The manufacturing cells are represented in this research by pneumatic motors assembly cells. A knowledge base and inference algorithms were developed and programmed to explore the effects of a large variety of architecture configurations on cells efficiencies. The achieved numerical results lead to the conclusion that exponential correlations characterize the interrelationships between assembly cell unutilization and architecture configurations parameters. Since exponential correlations characterize the interrelationships between assembly cells unutilization and architecture configurations parameters, an optimal architecture configuration is defined by three conditions, which match the beginning of the flattened parts of the exponential curves: (1) If the number of slaved assembly cells is considered, the optimal configuration is achieved when an additional slaved assembly cell results in a most significant reduction in assembly cells efficiency. (2) If the number of superior microprocessors is considered, the optimal configuration is achieved when an additional superior microprocessor does not result in a significant reduction in assembly cells unutilization. (3) If microprocessors capacity performance (bits/sec) is considered, the optimal configuration is achieved when additional capacity performance cannot reduce the assembly cells unutilization. Computer runs were performed to evaluate the optimal configurations. The developed knowledge base and inference algorithms were defined and programmed in generic terms and can be implemented in a large variety of systems.