l11inventory Drp

Inventory Management Distribution Requirements Planning Lecture 11 ESD.260 Fall2003 Caplice

Assumptions: Basic MRP ModelDemand Constant vs Variable Known vs Random Continuous vs DiscreteLead time Instantaneous Constantc or Variable (deterministic/stochastic)Dependence of items Independent Correlated Indentured Review Time Continuous vs PeriodicNumber of Echelons One vs ManyCapacity/Resources UnlimitedvsLimited

Discounts None All Units OrIncrementalExcess Demand None All orders are backordered Lost orders SubstitutionPerishability None Uniform with timePlanning Horizon Single Period Finite Period InfiniteNumber of Items One Many

MIT Center for Transportation & Logistics - ESD.260 2 Chris Caplice, MIT

A Multi-Echelon Inventory System MIT Center for Transportation & Logistics - ESD.260 3 Chris Caplice, MIT

What if I Use Traditional Techniques? In multi-echelon inventory systems with decentralized control, lot size / reorder point logic will: Create and amplify "lumpy" demand Lead to the mal-distribution of available stock, hoarding of stock, and unnecessary stock outs Force reliance on large safety stocks, expediting, and re-distribution.MIT Center for Transportation & Logistics - ESD.260 4 Chris Caplice, MIT

Impact of Multi-Echelons CDC Demand Pattern RDC OrderingPatterns RDC InventoryCycles Layers of Inventory Create Lumpy Demand MIT Center for Transportation & Logistics - ESD.260 5 Chris Caplice, MIT

What does a DRP do? Premises Inventory control in a distribution environment Many products, many stockage locations Multi-echelon distribution network Layers of inventory create "lumpy" demand Concepts Dependent demand versus independent demand Requirements calculation versus demand forecasting Schedule flow versus stockpile assets Information replaces inventory

DRP is simply the application of the MRP principles and techniques to distribution inventories Andre Martin MIT Center for Transportation & Logistics - ESD.260 6 Chris Caplice, MIT

DRP Requirements

Information Requirements: Base Level Usage Forecasts Distribution Network Design Inventory Status Ordering Data DRP Process: Requirements Implosion Net from Gross Requirements Requirements Time Phasing Planned Order Release MIT Center for Transportation & Logistics - ESD.260 7 Chris Caplice, MIT

A Distribution Network ExamplePlant Centra Warehouse Regional Warehouse 2 Regional Warehouse 1 Regional Warehouse 3 Retailer A

Retailer BRetailer C Retailer D Retailer E Retailer ERetailer G Retailer HRetailer IMIT Center for Transportation & Logistics - ESD.260 8 Chris Caplice, MIT

Example: The DRP Plan Regional Warehouse One Q=50 , SS=15 , LT=1 Period UsageGross RqmtBegin InvSched RcptNet Rqmt Plan RcptEnd InvPORtMIT Center for Transportation & Logistics - ESD.260 9 Chris Caplice, MIT

The DRP Plan MIT Center for Transportation & Logistics - ESD.260 10 Chris Caplice, MITCentral Warehouse Facility Period Usage Gross RqmtBegin Inv Sched Recpt Net Rqmt Planned Recpt End Inv Planned OrderPeriod Usage Gross RqmtBegin Inv Sched Recpt Net Rqmt Planned Recpt End Inv Period Usage Gross RqmtBegin Inv Sched Recpt Net Rqmt Planned Recpt End Inv Planned OrderPeriod Usage Gross RqmtBegin Inv Sched Recpt Net Rqmt Planned Recpt End Inv Planned Order

Example: The DRP Plan Regional Warehouse Two Q=30 , SS=10 , LT=1 Period UsageGross RqmtBegin InvSched RcptNet RpmtPlan RcptEnd InvPORNOWMIT Center for Transportation & Logistics - ESD.260 11 Chris Caplice, MIT

Example: The DRP Plan Regional Warehouse Three Q=20 , SS=10 , LT=1 Period UsageGross RqmtBegin InvSched RcptNet RpmtPlan RcptEnd InvPORNOWMIT Center for Transportation & Logistics - ESD.260 12 Chris Caplice, MIT

The DRP Plan for All Locations Rolling Up Orders


NOW12345678CENTRALPeriod Usage10020503010001000POR200

200200

REGION ONEPeriod Usage2525252525252525

POR50505050

REGION TWOPeriod Usage1010101010101010POR30303030

REGION THREEPeriod Usage5151010015015POR20202020

Example: The DRP Plan MIT Center for Transportation & Logistics - ESD.260 14 Chris Caplice, MITCentral Warehouse Q=200 , SS=0 , LT=2 Period UsageGross RqmtBegin InvSched RcptNet RpmtPlan RcptEnd InvPOR

Results and Insights DRP is a scheduling and stockage algorithm -- it replaces the forecasting mechanism above the base inventory level DRP does not determine lot size or safety stock -- but these decisions must be made as inputs to the process DRP does not explicitly consider any costs -- but these costs are still relevant the user must evaluate trade-offs DRP systems can deal with uncertainty -- using "safety time" and "safety stock" MIT Center for Transportation & Logistics - ESD.260 15 Chris Caplice, MIT

MRP / DRP Integration Purchase OrdersMRPMPSDRPProductCDCRDCRetailRetailRetailRetailSales/Marketing PlanMIT Center for Transportation & Logistics - ESD.260 16 Chris Caplice, MIT

Evolution of Inventory Management Traditional Replenishment Inventory: Lot Size/ Order Point Logic Single item focus Emphasis on cost optimization Long run, steady state approach The MRP / DRP Approach: Scheduling emphasis Focus on quantities and times, not cost Multiple, inter-related items and locations Simple heuristic rules


Evolution of Inventory Management MRP / DRP have limited ability to deal with: Capacity restrictions in production and distribution set-up costs fixed and variable shipping costs alternative sources of supply network transshipment alternatives expediting opportunities Next Steps in MRP/DRP Establish a time-phased MRP/MPS/DRP network Apply optimization tools to the network Consider cost trade-offs across items, locations, and time periods Deal with shortcomings listed aboveMIT Center for Transportation & Logistics - ESD.260 18 Chris Caplice, MIT

A DRP Network Plan What happens when actual demand in the short term doesnt follow the forecast exactly.. How should I re-deploy my inventory to take the maximum advantage of what I do have? PlantLDC2LDC1R7R6R5R4R3R2R1RDC2RDC1LDC4LDC3R8MIT Center for Transportation & Logistics - ESD.260 19 Chris Caplice, MIT

A DRP Network Reality PlantRDC1RDC2LDC1LDC2LDC3LDC4R1R2R3R4R5R6R7R8SHORTAGESEXCESSHigher than expected demand Lower than expected demand MIT Center for Transportation & Logistics - ESD.260 20 Chris Caplice, MIT

Optimal Network Utilization PlantLDC2LDC1R7R6R5R4R3R2R1RDC2RDC1LDC3LDC4R8SHORTAGESEXCESSMIT Center for Transportation & Logistics - ESD.260 21 Chris Caplice, MIT

Information and Control Impacts MIT Center for Transportation & Logistics - ESD.260 22 Chris Caplice, MIT

CenrtalizedControlDecentralized Control Global Information Vendor Managed Inventory (VMI) DRP (some cases) ExtendedBaseStock ControlSystems DRP (most cases) Base Stock Control Local Information N/A Standard Inventory Policies: (R,Q), (s,S) etc.

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