Transient state estimation for a discrete manufacturing system

Abstract To control a discrete manufacturing system (DMS), one must first estimate its current transient state. If control is to occur in a closed-loop mode, then a method is required to estimate the system state automatically. However, the state of a DMS changes rapidly, and the estimation of its transient state poses subtle challenges. This paper evaluates four methods for transient state estimation of a DMS, including a fuzzy algorithm that estimates the qualitative trajectory of system congestion. None of the methods require that any restrictive assumptions be made that could limit their applicability to practical systems. The effectiveness of the four methods for transient state estimation is demonstrated by their inclusion in an application to on-line, closed-loop control of order lead time for a job shop. Simulation experiments show that most of the methods for transient state estimation are fast and accurate enough to significantly improve the performance of the controller for order lead time. Following detailed analysis of the results, the paper concludes with a discussion of the intuitions gained from this research regarding the nature of transient states in a DMS.

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