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A proper simulation process, led well, can generate true organizational learning

By Timothy Stansfield, Ronda Massey and David Jamison

Simulation modeling provides an opportunity to assess complex and varied manufacturing systems with an objective, systematic and team-based approach. This mathematical and data-driven design tool requires all components and variables to be accounted for as the model is prepared. The model requires process definitions, transportation definitions, inspections, interferences, inventory allowances and all of the appropriate mathematical parameters. To ensure timely results, a systematic approach is required, including objective definitions, process mapping, data collection, model construction and simulation runs. Production simulations are intended to identify critical production constraints while balancing labor, asset utilization, inventory and lead-time. The end game for manufacturing simulation is to determine future production outputs.

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