$$\text{TLC} = P_{\text{EXW}} + C_{\text{inland}} + C_{\text{export}} + C_{\text{freight}} + C_{\text{ins}} + \text{Customs BCD} + \text{SWS} + \text{IGST} + C_{\text{port}} + C_{\text{dest\_inland}}$$
P_EXWEx Works purchase price paid to overseas supplier at their factory gate.
C_freight & C_insInternational ocean or air freight charges + marine cargo insurance premium.
BCD + SWS + IGSTBasic Customs Duty + Social Welfare Surcharge (10% of BCD) + Integrated GST assessed at port of entry.
C_port & C_destPort terminal handling charges (THC), container demurrage, customs clearance broker fees, and destination inland delivery.
Strategic Sourcing Lesson:
Low nominal factory purchase prices in overseas origins frequently mask severe landed cost inflation (freight, duties, financing pipeline inventory, container detention). Overseas sourcing is often 25–40% more expensive than the purchase order price!
$$\text{Cube Space Utilization} = \left(\frac{\text{Total Cargo Stored Volume (CBM)}}{\text{Total Usable Internal Building Volume (CBM)}}\right) \times 100\%$$
$$\text{Honeycomb Loss Factor} = 1 - \left(\frac{\text{Occupied Pallet Positions}}{\text{Total Storage Locations Available}}\right)$$
Cube UtilizationMeasures 3D space efficiency. Typical conventional flat warehouses achieve only 20–30% cube utilization; automated high-bay ASRS achieve 60–75%.
Honeycomb LossLost storage capacity caused by inability to utilize empty rack spaces because stored SKUs cannot be co-mingled or blocked.
Engineering Principle:
Storing cargo in standard ISO pallets ($1000\text{mm} \times 1200\text{mm}$) on 12-meter high vertical selective racking doubles effective storage capacity without expanding building ground footprint.
💼 Warehouse Space Planning Numerical
A DC has 10,000 pallet rack locations. Due to SKU segregation and lot-number integrity rules, 1,800 pallet slots remain unusable across partial aisles.
• Honeycomb Loss: \text{Loss} = \frac{1,800}{10,000} = 18.0\%
• Corrective Action: Implementing dynamic WMS slotting algorithms reduces honeycomb loss to <6%, freeing up 1,200 pallet positions without expanding warehouse square footage.
$$\text{Pick Lines Per Labor Hour (LPH)} = \frac{\text{Total Order Lines Picked}}{\text{Direct Picker Labor Hours}}$$
$$\text{Total Fulfillment Lead Time} = T_{\text{Release}} + T_{\text{Travel}} + T_{\text{Pick}} + T_{\text{Sort/Pack}} + T_{\text{Dispatch}}$$
Lines Per Hour (LPH)Industry standard measure of picking labor throughput. Travel time consumes up to 55% of manual picker hours.
Fulfillment Lead TimeElapsed time from ERP order induction to carrier departure dock loading.
💼 Order Picking Optimization Numerical
A fulfillment center processes 12,000 daily order lines using 30 warehouse operators working 8-hour shifts.
• Current Throughput: \text{LPH} = \frac{12,000}{30 \times 8} = \frac{12,000}{240} = 50\text{ lines/hour}
• Automation Impact: Migrating from single-order paper picking to Batch Picking with Zone Sorting and Pick-to-Light accelerates throughput to 125 LPH, cutting required direct labor from 30 operators to 12 operators!