Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Управляемое поставщиком пополнение запасов× | Канбан× | |
|---|---|---|
| Область | Операционный менеджмент | Операционный менеджмент |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 2006 | 1950 |
| Автор метода≠ | Disney, S. M., & Towill, D. R. | Taiichi Ohno |
| Тип≠ | Business and inventory model | Production control system |
| Основополагающий источник≠ | Disney, S. M., & Towill, D. R. (2006). Vendor-managed inventory: A taxonomy of approaches and implications. International Journal of Production Economics, 106(2), 440-456. link ↗ | Ohno, T. (1988). Toyota production system: Beyond large-scale production. Cambridge, MA: Productivity Press. link ↗ |
| Другие названия | VMI, supplier-managed inventory | visual management, pull system |
| Связанные | 5 | 5 |
| Сводка≠ | Vendor-Managed Inventory (VMI) is a supply chain arrangement in which the supplier (vendor) has visibility into the customer's inventory levels and assumes responsibility for replenishing inventory to pre-agreed levels. Rather than customers placing orders based on internal forecasts, the supplier monitors actual consumption and triggers replenishment shipments automatically. VMI reduces administrative burden, minimizes stock-outs, improves cash flow (by reducing inventory in the supply chain), and fosters collaboration between supplier and customer. | Kanban is a pull-based production control system developed by Taiichi Ohno at Toyota in the 1950s that uses visual signals (traditionally cards or bins) to trigger production and movement of materials based on actual demand rather than forecasts. The Japanese word 'kanban' means 'visual card' or 'sign,' and the system operates on the principle that work should flow in response to downstream requirements. Kanban is a foundational element of the Toyota Production System and lean manufacturing, enabling just-in-time production, reduced inventory, and improved flow efficiency. |
| ScholarGateНабор данных ↗ |
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