Mechanisms to adjust planned lead times based on current work loads are desirable for time‐phased planning systems. This paper investigates the use of exponentially smoothed order flow time feedback in setting planned lead times dynamically. The system studied is a supply chain with capacity‐constrained processing stations and transit times between stations. Lot sizes are based on the minimization of flow times using queuing approximations. Both seasonal and level demand patterns with uncertainty are considered. Since both dependent and independent demands are assumed at each station, customer delivery performance depends on the distribution of inventory along the supply chain. Results show that dynamic planned lead time setting can be used effectively to control delivery performance along the supply chain. Performance is also influenced significantly by appropriate lot size selection.

This research considers inventory replenishment in a stochastic, multi-echelon supply chain involving both production and distribution functions. Simulation is used to compare distribution/material requirements planning (DRP/MRP), re-order point (ROP) and Kanban (KBN) replenishment strategies. Additional experimental factors include the demand pattern and the existence of manufacturing capacity constraints. Trade-off curves between inventory and delivery performance are generated. Statistical techniques, including analysis of variance (ANOVA), are then used to compare the areas under the trade-off curves and determine the relative dominance among the replenishment strategies. The methodology is used to identify both main and interaction effects. With seasonal demand, DRP/MRP performance is found to be best, followed by ROP and KBN, respectively. Without seasonal demand, the relative performance ranking depends on the presence of capacity constraints. Without capacity constraints, ROP performs best, followed by DRP/MRP and KBN. With capacity constraints, the ranking is reversed. This difference in behaviour can be explained using queuing analysis.

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