Theory of constraints (TOC) uses a demand-pull replenishment strategy with buffer management (DPBM) to effectively manage inventory. This strategy has been demonstrated to perform better than traditional inventory strategies, such as (s, S), (s, Q), (R, S), (R, s, S) policies. However, the replenishment lead time is long, and demand changes rapidly in the semiconductor industry. These characteristics cause problems in managing semiconductor inventory and complicate the inventory replenishment strategy. In order to effectively solve the issue of inventory management, this paper proposes a novel approach to improve the classical DPBM by using market demand forecast information and demand-pull replenishment to effectively manage inventory in the semiconductor industry. In numerical verification, this paper used real data provided by a wafer foundry in Taiwan to demonstrate the feasibility and effectiveness of the proposed approach. Simulated scenarios that account for different patterns of demand and different degrees of accuracy of the demand forecasts were generated to test the performance of the proposed approach. After comparing the result that was obtained from the proposed approach with the one from the classical DPBM, it was found that the proposed approach can reduce the average inventory and does not adverse the level of service as long as the demand forecasts are not too far from the real demand.