統計性的庫存控制英文解釋翻譯、統計性的庫存控制的近義詞、反義詞、例句

英語翻譯：

【經】 statistical stock control

分詞翻譯：

統計的英語翻譯：

【醫】 statistics
【經】 numerical statement; statistics

庫存的英語翻譯：

repertory; reserve; stock; stockpile; storage
【化】 stock
【經】 inventories; on hand; stock; stocks; store; treasury

控制的英語翻譯：

control; dominate; desist; grasp; hold; manage; master; predominate; rein
rule
【計】 C; control; controls; dominance; gated; gating; governing
【醫】 control; dirigation; encraty
【經】 check; command; control; controlling; cost control; dominantion
monitoring; regulate; rig

專業解析

Statistical Inventory Control (SIC) refers to a systematic approach in supply chain management that utilizes statistical methods and historical data to determine optimal inventory levels, minimizing costs while ensuring adequate product availability to meet customer demand. It moves beyond simple rules-of-thumb by applying probability theory and forecasting techniques to account for demand variability and lead time uncertainty. The core objective is to balance the costs associated with holding inventory (carrying costs) against the costs of running out of stock (stockout costs) and the costs of placing orders (ordering costs).

The fundamental principle underpinning SIC is the recognition that both customer demand and supplier lead times are not constant but exhibit variability. Statistical models, often assuming demand follows patterns like a normal distribution, are employed to analyze historical sales data and forecast future demand. This analysis allows businesses to calculate key parameters:

Demand Forecast: The expected average demand over a specific period.
Demand Variability (Standard Deviation): A measure of how much actual demand tends to deviate from the forecasted average.
Lead Time: The time between placing an order and receiving the inventory.
Lead Time Variability: Uncertainty in the actual duration of the lead time.

Using these parameters, SIC systems calculate two critical control points:

Reorder Point (ROP): The inventory level at which a new order should be placed to replenish stock before it runs out. It's calculated to cover expected demand during the lead time plus a buffer (safety stock) to absorb unexpected demand surges or delivery delays. A common formula is: $$ROP = (Average Demand per Day times Lead Time in Days) + Safety Stock$$
Safety Stock: Extra inventory held specifically to buffer against uncertainties in demand and supply. The required safety stock level increases with higher demand variability, longer or more variable lead times, and the desired service level (probability of not stocking out). A basic formula considering demand variability during lead time is: $$Safety Stock = Z times sigma_{LT}$$ Where:
- $Z$ is the Z-score corresponding to the desired service level (e.g., Z=1.28 for 90% service level).
- $sigma_{LT}$ is the standard deviation of demand during the lead time.

Implementing SIC effectively requires accurate data collection, robust forecasting methods, and regular review of the statistical parameters and service level targets. Modern inventory management software often incorporates SIC principles, automating calculations and order generation based on real-time data. This approach is crucial for businesses aiming to optimize working capital tied up in inventory while maintaining high customer satisfaction through reliable product availability.

References:

APICS Dictionary (16th Edition), ASCM: Definition of Inventory Control & related principles.
Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd ed.). Wiley. (Covers statistical models for ROP and Safety Stock).
SAP Help Portal: Documentation on Inventory Management and MRP concepts within ERP systems.

網絡擴展解釋

統計性的庫存控制是指通過統計分析曆史數據、市場需求及供應鍊信息，動态調整庫存策略的管理方法。其核心是通過數學模型和統計工具優化庫存水平，平衡供需關系，降低成本和風險。以下是詳細解釋：

1.核心目标

需求匹配：基于曆史銷售數據或市場趨勢預測需求，确保庫存量既能滿足生産和銷售需求，又避免積壓。
成本控制：通過優化訂貨頻率和批量，減少倉儲費用、資金占用及過期損耗。

2.關鍵方法

需求預測：利用統計模型（如時間序列分析、回歸分析）預測未來需求，指導采購計劃。
安全庫存計算：根據需求波動性和供應周期，通過标準差等統計指标确定緩沖庫存量。
訂貨策略：采用定量訂貨（如經濟訂貨批量模型）或定期訂貨法，結合統計參數動态調整。

3.實施優勢

降低缺貨風險：通過數據分析識别銷售波動規律，提前備貨。
提高周轉率：減少冗餘庫存，加速資金流動。
支持決策科學化：用數據替代經驗判斷，提升庫存管理精準度。

4.典型應用場景

零售業：根據季節性銷售數據調整庫存。
制造業：基于生産周期和供應鍊穩定性設定安全庫存。

如需進一步了解具體模型（如EOQ公式），可參考來源、4、5、7、8中的詳細分析。