Estimating simulation metamodel parameters for unexpected shop floor real time events

In order to better understand assembly line system dynamic behavior and provide a basis for developing effective production controls, three unexpected real time events are studied, including sudden machine breakdown at a work station, parts supply shortage and high priority job order processing. Short term system performance is evaluated by dynamic response variables associated with assembly time and work in process (WIP) inventory. Simulation is used as the modeling tool, and the results are further described by mathematical metamodels for overall system behavior. The system transients can be adequately represented by first order exponential functions, and satisfactory results are also obtained for expressing simultaneous occurrence of dynamic events by combined metamodels using linear additivity. A procedure is proposed for the development of dynamic metamodels. For a given system, only a limited number of simulation runs should be made in advance to estimate the metamodel parameters. Using the resultant application program that only contains the metamodels, whenever an event occurs, without running simulation a user can instantaneously predict the consequence in a specified time period by an estimation to the number of assembly products to be finished late.