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An approximate model for performance measurement in base-stock controlled assembly systems

2004
Rodoplu, Umut
The aim of this thesis is to develop a tractable method for approximating the steady-state behavior of continuous-review base-stock controlled assembly systems with Poisson demand arrivals and manufacturing and assembly facilities modeled as Jackson networks. One class of systems studied is to produce a single type of finished product assembling a number of components and another class is to produce two types of finished products allowing component commonality. The performance measures evaluated are the expected backorders, fill rate and the stockout probability for finished product(s). A partially aggregated but exact model is approximated assuming that the state-dependent transition rates arising as a result of the partial aggregation are constant. This approximation leads to the derivation of a closed-form steady-state probability distribution, which is of product-form. Adequacy of the proposed model in approximating the steady-state performance measures is tested against simulation experiments over a large range of parameters and the approximation turns out to be quite accurate with absolute errors of 10% at most for fill rate and stockout probability, and of less than 1.37 (82) requests for expected backorders. A greedy heuristic which is proposed to be employed using approximate steady-state probabilities is devised to optimize base-stock levels while aiming at an overall service level for finished product(s).