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LSM-306 Supply Chain Management

Master of Business Administration

(Logistics & Supply Chain Management)

Supply Chain Management

SCM - 306

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GITAM INSTITUTE OF INTERNATIONAL BUSINESS Professor P.R.S SARMA M.B.A & Ph.D.- IITD

UNIT - II

I

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Why Network Planning?

Find the right balance between inventory, transportation and

manufacturing costs,

Match supply and demand under uncertainty by positioning and managing

inventory effectively,

Utilize resources effectively by sourcing products from the most

appropriate manufacturing facility

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Three Hierarchical Steps

Network design Number, locations and size of manufacturing plants and warehouses

Assignment of retail outlets to warehouses

Major sourcing decisions

Typical planning horizon is a few years.

Inventory positioning: Identifying stocking points

Selecting facilities that will produce to stock and thus keep inventory

Facilities that will produce to order and hence keep no inventory

Related to the inventory management strategies

Resource allocation: Determine whether production and packaging of different products is done at the right facility

What should be the plants sourcing strategies?

How much capacity each plant should have to meet seasonal demand?

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Network Design

Physical configuration and infrastructure of the supply chain. A strategic decision with long-lasting effects on the firm.

Decisions relating to plant and warehouse location as well as distribution

and sourcing

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Reevaluation of Infrastructure

Changes in:

demand patterns product mix

production processes

sourcing strategies

cost of running facilities.

Mergers and acquisitions may mandate the integration of different logisticsnetworks

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Key Strategic Decisions

Determining the appropriate number of facilities such as plants and

warehouses. Determining the location of each facility.

Determining the size of each facility.

Allocating space for products in each facility.

Determining sourcing requirements.

Determining distribution strategies, i.e., the allocation of customers to

warehouse

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Objective and Trade-Offs

Objective: Design or reconfigure the logistics network in order to minimize annual system-wide cost subject to a variety ofservice level requirements

Increasing the number of warehouses typically yields: An improvement in service level due to the reduction in average travel time to the customers

An increase in inventory costs due to increased safety stocks required to protect each warehouseagainst uncertainties in customer demands.

An increase in overhead and setup costs

A reduction in outbound transportation costs: transportation costs from the warehouses to thecustomers

An increase in inbound transportation costs: transportation costs from the suppliers and/or

manufacturers to the warehouses.

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Data Collection

Locations of customers, retailers, existing warehouses and distribution centers,manufacturing facilities, and suppliers.

All products, including volumes, and special transport modes (e.g., refrigerated).

Annual demand for each product by customer location.

Transportation rates by mode.

Warehousing costs, including labor, inventory carrying charges, and fixed operating costs.

Shipment sizes and frequencies for customer delivery.

Order processing costs.

Customer service requirements and goals.

Production and sourcing costs and capacities

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Data Aggregation

Customer Zone Aggregate using a grid network or other clustering technique for those in close proximity.

Replace all customers within a single cluster by a single customer located at the center of the cluster

Five-digit or three-digit zip code based clustering.

Product Groups Distribution pattern

Products picked up at the same source and destined to the same customers

Logistics characteristics like weight and volume.

Product type product models or style differing only in the type of packaging.

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Replacing Original Detailed Data with Aggregated Data

Technology exists to solve the logistics network design problem with theoriginal data

Data aggregation still useful because forecast demand is significantly moreaccurate at the aggregated level

Aggregating customers into about 150-200 zones usually results in nomore than a 1 percent error in the estimation of total transportation costs

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General Rules for Aggregation

Aggregate demand points into at least 200 zones Holds for cases where customers are classified into classes according to their service

levels or frequency of delivery

Make sure each zone has approximately an equal amount of total demand

Zones may be of different geographic sizes.

Place aggregated points at the center of the zone

Aggregate products into 20 to 50 product groups

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Customer Aggregation

Based on 3-Digit Zip Codes

Total C ost:$5,796,000Total Customers: 18,000

Total C ost:$5,793,000Total Customers: 800

Cost Difference < 0.05%

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Product Aggregation

Total Cost:$104,564,000Total Products: 46

Total Cost:$104,599,000Total Products: 4

Cost Difference: 0.03%

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Transportation Rates

Rates are almost linear with distance but not with volume

Differences between internal rate and external rate

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Internal Transportation Rate

For company-owned trucks

Data Required:

Annual costs per truck

Annual mileage per truck

Annual amount delivered

Trucks effective capacity

Calculate cost per mile per SKU.

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External Transportation Rate

Two Modes of Transportation

Truckload, TL

Country sub-divided into zones. One zone/state except for: Big states, such as Florida or New York (two zones)

Zone-to-zone costs provides cost per mile per truckload between any two zones.

TL cost from Chicago to Boston =

Illinois-Massachusetts cost per mile X Chicago-Boston distance

TL cost structure is not symmetric

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Less-Than-Truckload, LTL

Class rates

standard rates for almost all products or commodities shipped.

Classification tariffsystem that gives each shipment a rating or a class. Factors involved in determining a products specific class include:

product density, ease or difficulty of handling and transporting, andliability for damage.

After establishing rating, identify rate basis number.

Approximate distance between the loads origin and destination.

With the two, determine the specific rate per hundred pounds (hundred weight,or cwt) from a carrier tariff table (i.e., a freight rate table).

Exception rates provides less expensive rates

Commodity rates are specialized commodity-specific rates

External Transportation Rate

Two Modes of Transportation

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SMC3s CzarLite

Engine to find rates in fragmented LTL industry

Nationwide LTL zip code-based rate system.

Offers a market-based price list derived from studies of LTL pricing on a regional,interregional, and national basis.

A fair pricing system

Often used as a base for negotiating LTL contracts between shippers, carriers, and

third-party logistics providers

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Transportation Rate for Shipping 4,000 lbs.

Transportation rates for shipping 4,000 lb

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Mileage Estimation

Estimate lona and lata, the longitude and latitude of point a (and similarly

for point b)

Distance between a and b

For short distances

For large distances

2 2)6 9 ( ( )a b a b a bl o nD l o n l a t l a t

1 2 2) ))) ))2(69) sin (sin( cos( cos( (sin(

2 2

a b a b

ab a X b X

lat lat lon lonD lat lat

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Circuity Factor,

Equations underestimate the actual road distance.

MultiplyDab by .

Typical values:

= 1.3 in metropolitan areas

= 1.14 for the continental United States

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Chicago-Boston Distance

lonChicago = -87.65

latChicago = 41.85

lonBoston = -71.06

lonBoston = 42.36

DChicago, Boston = 855 miles Multiply by circuity factor = 1.14

Estimated road distance = 974 miles

Actual road distance = 965 miles

GIS systems provide more accuracy

Slows down systems

Above approximation good enough!

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Warehouse Costs

Handling costs

Labor and utility costs

Proportional to annual flow through the warehouse.

Fixed costs

All cost components not proportional to the amount of flow

Typically proportional to warehouse size (capacity) but in a nonlinear way.

Storage costs

Inventory holding costs

Proportional to average positive inventory levels.

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Determining Fixed Costs

Warehouse fixed costs as a function of the warehouse capacity

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Determining Storage Costs

Multiply inventory turnover by holding cost

Inventory Turnover =

Annual Sales / Average Inventory Level

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Warehouse Capacity

Estimation of actual space required

Average inventory level =

Annual flow through warehouse/Inventory turnover ratio

Space requirement for item = 2*Average Inventory Level Multiply by factor to account for

access and handling

aisles,

picking, sorting and processing facilities

AGVs

Typical factor value = 3

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Warehouse Capacity Example

Annual flow = 1,000 units

Inventory turnover ratio = 10.0

Average inventory level = 100 units

Assume each unit takes 10 sqft. of space

Required space for products = 2,000 sqft.

Total space required for the warehouse is about 6,000 square feet

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Potential Locations

Geographical and infrastructure conditions.

Natural resources and labor availability.

Local industry and tax regulations.

Public interest.

Not many will qualify based on all the above conditions

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Service Level Requirements

Specify a maximum distance between each customer and the warehouse

serving it

Proportion of customers whose distance to their assigned warehouse is no

more than a given distance

95% of customers be situated within 200 miles of the warehouses serving them

Appropriate for rural or isolated areas

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Future Demand

Strategic decisions have to be valid for 3-5 years

Consider scenario approach and net present values to factor in expected

future demand over planning horizon

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$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

0 2 4 6 8 10

Number of Warehouses

Cost(millions$)

Total Cost

Transportation Cost

Fixed Cost

Inventory Cost

Number of Warehouses

OptimalNumber

of Warehouses

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Industry Benchmarks:

Number of Distribution Centers

Avg.

# of

WH 3 14 25

Pharmaceuticals Food Companies Chemicals

- High margin product- Service not important (or

easy to ship express)

- Inventory expensive

relative to transportation

- Low margin product- Service very important

- Outbound transportation

expensive relative to inbound

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Model Validation

Reconstruct the existing network configuration using the model and collected data

Compare the output of the model to existing data

Compare to the companys accounting information

Often the best way to identify errors in the data, problematic assumptions,modeling flaws.

Make local or small changes in the network configuration to see how the systemestimates impact on costs and service levels.

Positing a variety of what-if questions.

Answer the following questions:

Does the model make sense? Are the data consistent?

Can the model results be fully explained?

Did you perform sensitivity analysis?

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Solution Techniques

Mathematical optimization techniques:

1. Exact algorithms: find optimal solutions

2. Heuristics: findgood

solutions, not necessarily optimal

Simulation models: provide a mechanism to evaluate specified design alternativescreated by the designer.

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Example

Single product

Two plants p1 and p2

Plant p2 has an annual capacity of 60,000 units.

The two plants have the same production costs.

There are two warehouses w1 and w2 with identical warehouse handling costs.

There are three markets areas c1,c2 and c3 with demands of 50,000, 100,000 and50,000, respectively.

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Unit Distribution Costs

21225w2

54340w1

c3c2c1p2p1Facility warehouse

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Heuristic #1:Choose the Cheapest Warehouse to Source Demand

D = 50,000

D = 100,000

D = 50,000

Cap = 60,000

$5 x 140,000

$2 x 60,000

$2 x 50,000

$1 x 100,000

$2 x 50,000

Total Costs = $1,120,000

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Heuristic #2:Choose the warehouse where the total delivery costs to and from the warehouse are the

lowest[Consider inbound and outbound distribution costs]

D = 50,000

D = 100,000

D = 50,000

Cap = 60,000

$4

$5

$2

$3

$4$5

$2

$1

$2

$0

P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4



Market #1 is served by WH1, Markets 2 and 3are served by WH2

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D = 50,000

D = 100,000

D = 50,000

Cap = 60,000

Cap = 200,000

$5 x 90,000

$2 x 60,000

$3 x 50,000

$1 x 100,000

$2 x 50,000

$0 x 50,000




Total Cost = $920,000

Heuristic #2:Choose the warehouse where the total delivery costs to and from the warehouse are the

lowest[Consider inbound and outbound distribution costs]

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The Optimization Model

The problem described earlier can be framed as the following linear programming

problem.

Let

x(p1,w1), x(p1,w2), x(p2,w1) and x(p2,w2) be the flows from the plants to thewarehouses.

x(w1,c1), x(w1,c2), x(w1,c3) be the flows from the warehouse w1 to customer

zones c1, c2 and c3.

x(w2,c1), x(w2,c2), x(w2,c3) be the flows from warehouse w2 to customer zones

c1, c2 and c3

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The problem we want to solve is:

min 0x(p1,w1) + 5x(p1,w2) + 4x(p2,w1)

+ 2x(p2,w2) + 3x(w1,c1) + 4x(w1,c2)

+ 5x(w1,c3) + 2x(w2,c1) + 2x(w2,c3)

subject to the following constraints:

x(p2,w1) + x(p2,w2) 60000

x(p1,w1) + x(p2,w1) = x(w1,c1) + x(w1,c2) + x(w1,c3)

x(p1,w2) + x(p2,w2) = x(w2,c1) + x(w2,c2) + x(w2,c3)

x(w1,c1) + x(w2,c1) = 50000x(w1,c2) + x(w2,c2) = 100000

x(w1,c3) + x(w2,c3) = 50000

all flows greater than or equal to zero.

The Optimization Model

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Optimal Solution

060,000060,0000w2

50,00040,00050,0000140,000w1

c3c2c1p2p1Facilitywarehouse

Total cost for the optimal strategy is $740,000

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Simulation Models

Useful for a given design and a micro-level analysis. Examine:

Individual ordering pattern.

Specific inventory policies. Inventory movements inside the warehouse.

Not an optimization model

Can only consider very few alternate models

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Which One to Use?

Use mathematical optimization for static analysis

Use a 2-step approach when dynamics in system has to be analyzed: Use an optimization model to generate a number of least-cost solutions at the

macro level, taking into account the most important cost components.

Use a simulation model to evaluate the solutions generated in the first phase.

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DSS for Network Design

Flexibility to incorporate a large set of preexisting network characteristics

Other Factors:

Customer-specific service level requirements.

Existing warehouses kept open Expansion of existing warehouses.

Specific flow patterns maintained

Warehouse-to-warehouse flow possible

Production and Bill of materials details may be important

Robustness

Relative quality of the solution independent of specific environment, datavariability or specific settings

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Inventory Positioning and Logistics Coordination

Multi-facility supply chain that belongs to a single firm

Manage inventory so as to reduce system wide cost

Consider the interaction of the various facilities and the impact of this interactionon the inventory policy of each facility

Ways to manage:

Wait for specific orders to arrive before starting to manufacture them [make-to-order facility]

Otherwise, decide on where to keep safety stock?

Which facilities should produce to stock and which should produce to order?

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Single Product, Single Facility Periodic Review Inventory

Model

Assume -

SI: amount of time between when an order is placed until the facility receives a

shipment (Incoming Service Time)

S: Committed Service Time made by the facility to its own customers.

T: Processing Time at the facility.

Net Lead Time = SI + T - S

Safety stock at the facility:

STSI

STSIzh

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2-Stage System

Reducing committed service time from facility 2 to facility 1 impacts required

inventory at both facilities

Inventory at facility 1 is reduced

Inventory at facility 2 is increased

Overall objective is to choose:

the committed service time at each facility the location and amount of inventory

minimize total or system wide safety stock cost.

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ElecComp Case

Large contract manufacturer of circuit boards and other high tech parts.

About 27,000 high value products with short life cycles

Fierce competition => Low customer promise times < Manufacturing Lead Times

High inventory of SKUs based on long-term forecasts => Classic PUSH STRATEGY

High shortages Huge risk

PULL STRATEGY not feasible because of long lead times

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New Supply Chain Strategy

OBJECTIVES:

Reduce inventory and financial risks

Provide customers with competitive response times.

ACHIEVE THE FOLLOWING:

Determining the optimal location of inventory across the various stages Calculating the optimal quantity of safety stock for each component at each

stage

Hybrid strategy of Push and Pull

Push Stages produce to stock where the company keeps safety stock

Pull stages keep no stock at all.

Challenge:

Identify the location where the strategy switched from Push-based to Pull-based

Identify the Push-Pull boundary

Benefits:

For same lead times, safety stock reduced by 40 to 60%

Company could cut lead times to customers by 50% and still reduce safetystocks by 30%

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Notations Used

How to read the diagrams

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Current Safety Stock Location

Current safety stock location

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Optimized Safety Stock Location

Optimized safety stock

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Current Safety Stock with Lesser Lead Time

Optimized safety stock with reduced lead time

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Supply Chain withMore Complex Product Structure

Current supply chain

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Optimized Supply Chain withMore Complex Product Structure

Optimized supply chain

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Key Points

Identifying the Push-Pull boundary

Taking advantage of the risk pooling concept

Demand for components used by a number of finished products has smaller variability

and uncertainty than that of the finished goods.

Replacing traditional supply chain strategies that are typically referred to as

sequential, or local, optimization by a globally optimized supply chain strategy.

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Local vs. Global Optimization

Trade-off between quoted lead time and safety stock

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Global Optimization

For the same lead time, cost is reduced significantly

For the same cost, lead time is reduced significantly

Trade-off curve has jumps in various places

Represents situations in which the location of the Push-Pull boundarychanges

Significant cost savings are achieved.

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Problems with Local Optimization

Prevalent strategy for many companies:

try to keep as much inventory close to the customers

hold some inventory at every location

hold as much raw material as possible.

This typically yields leads to:

Low inventory turns

Inconsistent service levels across locations and products, and

The need to expedite shipments, with resulting increased transportation costs

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Consider a two-tier supply chain

Items shipped from manufacturing facilities to primary warehouses

From there, they are shipped to secondary warehouses and finally to retail outlets

How to optimally position inventory in the supply chain?

Should every SKU be positioned both at the primary and secondary warehouses?, OR

Some SKU be positioned only at the primary while others only at the secondary?

Integrating Inventory Positioning and Network Design

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Integrating Inventory Positioning and Network Design

Sample plot of each SKU by volume and demand

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Three Different Product Categories

High variability - low volume products

Low variability - high volume products, and

Low variability - low volume products.

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Supply Chain Strategy Different for the Different Categories

High variability low volume products Inventory risk the main challenge for

Position them mainly at the primary warehouses

demand from many retail outlets can be aggregated reducing inventory costs. Low variability high volume products

Position close to the retail outlets at the secondary warehouses

Ship fully loaded tracks as close as possible to the customers reducing transportationcosts.

Low variability low volume products Require more analysis since other characteristics are important, such as profit margins,

etc.

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Resource Allocation

Supply chain master planning

The process of coordinating and allocating production, and distribution strategiesand resources to maximize profit or minimize system-wide cost

Process takes into account: interaction between the various levels of the supply chain

identifies a strategy that maximizes supply chain performance

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Global Optimization and DSSFACTORS TO CONSIDER

Facility locations: plants, distribution centers and demand points

Transportation resources including internal fleet and common carriers

Products and product information

Production line information such as min lot size, capacity, costs, etc.

Warehouse capacities and other information such as certain technology (refrigerators) that aspecific warehouse has and hence can store certain products

Demand forecast by location, product and time.

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Focus of the Output

Sourcing Strategies:

where should each product be produced during the planning horizon, OR

Supply Chain Master Plan: production quantities, shipment size and storage requirements by product,

location and time period.

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The Extended Supply Chain: From Manufacturing toOrder Fulfillment

The extended supply chain: from manufacturing to order fulfillment

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Questions to Ask During the Planning Process

Will leased warehouse space alleviate capacity problems?

When and where should the inventory for seasonal or promotional demand be built and stored?

Can capacity problems be alleviated by re-arranging warehouse territories? What impact do changes in the forecast have on the supply chain?

What will be the impact of running overtime at the plants or out-sourcing production?

What plant should replenish each warehouse?

Should the firm ship by sea or by air. Shipping by sea implies long lead times and therefore requireshigh inventory levels. On the other hand, using air carriers reduces lead times and hence inventorylevels but significantly increases transportation cost.

Should we rebalance inventory between warehouses or replenish from the plants to meet unexpectedregional changes in demand?

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SUMMARYNetwork Planning Characteristics

FewFewVery FewUsers

ShortShortVery ShortImplementation

MediumMediumHighROI

Monthly/WeeklyMonthly/WeeklyYearlyFrequency

ClassesItemFamilyAggregation Level

MonthsMonthsYearsPlanning Horizon

Production DistributionSafety stockInfrastructureDecision focus

Resource AllocationInventory Positioning and

Management

Network Design

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SUMMARY

Optimizing supply chain performance is difficult

conflicting objectives

demand and supply uncertainties

supply chain dynamics.

Through network planning, firms can globally optimize supply chain performance

Combines network design, inventory positioning and resource allocation

Consider the entire network account production

Warehousing

transportation inventory costs

service level requirements.

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SUMMARY

Demonstrate applicability of risk pooling and postponement, EOQ

modeling, and inventory sizing to improve customer service in make-to-

order job shop setting

Demonstrates value from getting and looking at data

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Case: H. C. Starck, Inc.

Background and context

Why are lead times long?

How might they be reduced?

What are the costs? benefits?

Stephen C. Graves Copyright 2003

All Rights Reserved

GITAM INSTITUTE OF INTERNATIONAL BUSINESS P f P R S SARMA

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Metallurgical Products

Make-to-order job shop operation

600 SKUs made from 4 sheet bar (4 alloys)

Goal to reduce 7-week customer lead times

Expediting is ad hoc scheduling rule

Six months of inventory

Manufacturing cycle time is 2 3 weeks

Limited data


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ProductionOrder#1

4Bar 1/4Plate 1/8Plate 0.015Sheet Tubing

ProductionOrder#2 ProductionOrder#3

CleanRoll AnnealSheet Bar(forgedingot)

Repeat0n3

Finish(cut, weld, etc.)

Production Orders


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Why Is Customer Lead Time 7 Weeks?

From sales order to process order takes 2 weeks

Typical order requires multiple process orders, each 2 3 weeks

Expediting as scheduling rule

Self fulfilling prophecy?


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What Are Benefits From Reducing Lead Time?

New accounts and new business

Protect current business from switching to substitutes or Chinese

competitor

Possibly less inventory Better planning and better customer service

Savings captured by customers?


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How Might Starck Reduce Customer LeadTimes?

Hold intermediate inventory

How would this help?

How much? Where?

Eliminate paper-work delays Reduce cycle time for each process order

How? What cost?


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Two-Product Optimal Cycle Time

*

*

2 2

2

2 400 4000.02 years

.06 100 526000 .06 125 183000

B F B B F F

B F

B B F F

K K h D h DCost T T

T

K KT

h D h D

T


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Intermediate Inventory

Characterize demand by possible intermediate for each of two alloys

Pick stocking points based on risk pooling benefits, lead time reduction,

volume

Determine inventory requirements based on inventory model, e. g. basestock


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83


PopularityMaterialGauge-Description Jan Feb Mar Apr May Jun Jul Aug Sep Total Cum%

1 1011 0.002 Foil 618 1,079 1,215 1,188 1,020 290 1,590 849 1,017 8,866 22%

2 1004 0.015 Sheet 68 611 1,263 167 1,917 803 321 377 404 5,931 37%

3 1003 0.005 Sheet 263 576 584 812 617 969 572 359 909 5,661 50%

4 1029 0.500 Disk- 10" dia 275 0 353 0 581 0 530 414 1,017 3,170 58%

5 1009 0.030 Sheet 0 122 614 275 422 360 686 246 177 2,902 65%

6 1008 0.040 Sheet 321 101 191 486 8 98 263 176 690 2,334 71%

7 1002 0.010 Sheet 20 56 287 179 41 204 560 143 276 1,766 76%

8 1014 0.250 Plate 6 12 0 770 0 752 0 0 174 1,714 80%

9 1007 0.060 Plate 0 146 32 117 129 414 581 26 191 1,636 84%

10 1012 0.125 Plate 228 8 32 90 432 17 8 0 450 1,265 87%

11 1013 0.150 Plate 1,100 0 0 0 0 35 0 0 0 1,135 90%12 1028 0.500 Ring- 10" ODx8.5" ID 0 189 0 48 293 93 0 0 174 797 92%

13 1010 0.020 Sheet 0 54 102 183 45 54 126 92 119 775 94%

14 1017 0.750 Tube- 3/4" 0 0 0 8 12 558 0 0 12 590 95%

15 1015 0.375 Plate 0 0 0 0 0 0 375 0 0 375 96%

16 1018 0.015 Tube- 1.0" OD 8 0 0 0 0 230 0 41 0 279 97%

17 1001 0.005 Sheet - 1.0" x23.75" 171 0 0 20 0 0 0 17 0 208 97%

18 1016 0.500 Tube- 0.50" OD 3 0 0 51 6 54 33 27 33 207 98%

19 1023 0.010 Sheet - 1.0" x23.75" 0 99 14 18 0 0 0 0 0 131 98%

20 1027 0.015 Sputter Target - 2.0" x5.0" 0 105 0 0 0 0 0 0 0 105 98%

Other - - 17Other Items 217 36 57 86 100 40 52 43 35 666 100%

40,513

1999InvoicedSales- Poundsper month

Alloy 1Stephen C. Graves Copyright 2003

All Rights Reserved

GITAM INSTITUTE OF INTERNATIONAL BUSINESS Professor P.R.S SARMA M B A & Ph D IITD

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Sales

Rank Material Gauge- Description Jan Feb Mar Apr May Jun Jul Aug Sep Total Cum%

1 2040 0.015 WeldedTube.75" OD 296 9362,9891,3662,468 989 657 5281,392 11,623 27

2 2031 0.020 Sheet Annealed 761 521 826 671 8891,0043,975 27 7 8,681 48

3 2035 0.030 Sheet Annealed 1,638 1161,138 634 524 5791,672 703 517 7,520 65

4 2041 0.020 WeldedTube.75" OD 0 50 316 3 379 02,856 0 0 3,604 74

5 2043 0.015 WeldedTube1.0" OD 0 0 480 444 0 77 118 343 0 1,462 77

6 2027 0.060 PlateAnnealed 0 0 277 323 60 0 504 12 205 1,382 80

7 2050 0.015 WeldedTube1" ODWithCap 0 0 01,003 0 0 176 0 0 1,179 83

8 2029 0.045 Sheet Annealed 137 122 430 18 37 16 0 368 5 1,133 86

9 2026 0.010 Sheet Annealed 0 0 435 0 251 412 0 0 0 1,098 88

10 2051 0.022 WeldedTube1.25" OD 0 0 01,014 0 0 0 0 0 1,014 91

11 2025 0.002 Foil Annealed 551 0 0 0 0 0 0 0 0 551 92

12 2034 0.125 PlateAnnealed 0 35 78 63 34 0 0 208 0 418 9313 2045 0.030 WeldedTube1.0" OD 0 0 370 0 0 1 0 0 41 412 94

14 2044 0.020 WeldedTube1.0" OD 0 0 0 32 241 108 4 0 0 386 95

15 2047 0.030 WeldedTube1.5O" OD 0 255 100 0 0 0 0 0 0 355 96

16 2039 0.020 WeldedTube.50" OD 0 0 181 142 0 0 0 0 0 323 96

17 2052 0.035 Tube1.25" OD 0 0 302 0 0 0 0 0 0 302 97

18 2036 0.015 Sheet Annealed 108 0 13 56 0 27 0 0 1 205 98

19 2046 0.015 WeldedTube1.5" OD 0 0 0 0 40 0 133 0 0 173 98

20 2012 0.045 4" Repair Disk 0 8 6 15 0 84 7 9 8 137 98

Other - - 35Other Items 77 118 64 67 113 133 44 24 112 753 100

42,709

1999InvoicedSales- Poundsper Month

Alloy 2


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A l l o y # 1 P r o d u c t H e i r a r c h y

( T o p 2 0 I t e m s - 9 8 % o f S a l e s )

4

8

1 2

1 5

1 01 1

2

5

6

9

1 31 4

1 6

1 8

2 0

1

3

7

1 7

1 9

0 . 0 3 0 " S h e e t

2 , 0 5 3 l b s / m o

2 8 % R S D

1 / 8 " P l a t e

4 , 1 0 4 l b s / m o

3 0 % R S D

1 / 4 " P l a t e

5 , 4 6 3 l b s / m o

2 3 % R S D

4 " B a r

6 , 8 1 7 l b s / m o2 5 % R S D


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GITAM INSTITUTE OF INTERNATIONAL BUSINESS S S M.B.A & Ph.D.- IITDA l l o y # 2 P r o d u c t H e i r a r c h y

( T o p 2 0 I t e m s - 9 8 % o f S a l e s )

6

1 2

2

3

4

8

1 0

1 3

1 4

1 5

1 6

1 7

2 0

1

5

7

1 8

1 9

0 . 0 1 5 " S h e e t

1 , 8 0 8 l b s / m o

6 5 % R S D

1 1

9

0 . 0 3 0 " S h e e t

2 0 4 l b s / m o

1 2 6 % R S D

1 / 8 " P l a t e

5 , 1 8 1 l b s / m o

5 9 % R S D

1 / 4 " P l a t e

6 , 7 2 6 l b s / m o

5 9 % R S D

4 " B a r

7 , 4 7 4 l b s / m o

5 9 % R S D


All Rights Reserved

GITAM INSTITUTE OF INTERNATIONAL BUSINESS Professor P.R.S SARMA M B A & Ph D - IITD

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Sales

Rank Material Gauge - Description Jan Feb Mar Apr May Jun Jul Aug Sep

Total

(Pounds)

Monthly

Average

Standard

Deviation % RSD

From 0.030" Sheet

1 1011 0.002 Foil 618 1,079 1,215 1,188 1,020 290 1,590 849 1,017 8,866 985 372 38%

3 1003 0.005 Sheet 263 576 584 812 617 969 572 359 909 5,661 629 235 37%

7 1002 0.010 Sheet 20 56 287 179 41 204 560 143 276 1,766 196 168 85%

19 1023 0.010 Sheet - 1.0" x 23.75" 0 99 14 18 0 0 0 0 0 131 15 32 223%

17 1001 0.005 Sheet - 1.0" x 23.75" 171 0 0 20 0 0 0 17 0 208 23 56 242%

Monthly Subtotal 1,072 1,810 2,100 2,217 1,678 1,463 2,722 1,368 2,202

90% Input required at yield 1,191 2,011 2,333 2,463 1,864 1,626 3,024 1,520 2,447 18,480 2,053 569 28%

From 0.125" Plate

0.030" Sheet to Supply Above 1,191 2,011 2,333 2,463 1,864 1,626 3,024 1,520 2,447 18,480 2,053 569 28%

2 1004 0.015 Sheet 68 611 1,263 167 1,917 803 321 377 404 5,931 659 594 90%

16 1018 0.015 Tube - 1.0" OD 8 0 0 0 0 230 0 41 0 279 31 76 245%

20 1027 0.015 Sputter Target - 2.0" x 5.0" 0 105 0 0 0 0 0 0 0 105 12 35 300%

18 1016 0.015 Tube - 0.50" OD 3 0 0 51 6 54 33 27 33 207 23 22 94%

14 1017 0.015 Tube - 3/4" 0 0 0 8 12 558 0 0 12 590 66 185 282%

13 1010 0.020 Sheet 0 54 102 183 45 54 126 92 119 775 86 54 63%

5 1009 0.030 Sheet 0 122 614 275 422 360 686 246 177 2,902 322 224 70%

6 1008 0.040 Sheet 321 101 191 486 8 98 263 176 690 2,334 259 214 83%

9 1007 0.060 Plate 0 146 32 117 129 414 581 26 191 1,636 182 194 107%


90% Input Required at Yield 1,768 3,500 5,039 4,167 4,893 4,663 5,594 2,783 4,525 36,932 4,104 1213 30%

From 0.250" Plate

0.125" Plate to Supply Above 1,768 3,500 5,039 4,167 4,893 4,663 5,594 2,783 4,525 36,932 4,104 1213 30%

10 1012 0.125 Plate 228 8 32 90 432 17 8 0 450 1,265 141 185 131%

11 1013 0.150 Plate 1,100 0 0 0 0 35 0 0 0 1,135 126 365 290%



From 4.0" Sheet Bar

0.250" Plate to Supply Above 3,870 4,385 6,339 5,321 6,656 5,894 7,002 3,479 6,219 49,165 5,463 1273 23%

8 1014 0.250 Plate 6 12 0 770 0 752 0 0 174 1,714 190 328 172%

15 1015 0.375 Plate 0 0 0 0 0 0 375 0 0 375 42 125 300%

4 1029 0.500 Disk - 10" dia 275 0 353 0 581 0 530 414 1,017 3,170 352 337 96%

12 1028 0.500 Ring - 10" OD x 8.5" ID 0 189 0 48 293 93 0 0 174 797 89 107 121%



Alloy 1Stephen C. Graves Copyright 2003All Rights Reserved

GITAM INSTITUTE OF INTERNATIONAL BUSINESS Professor P.R.S SARMA M B A & Ph D - IITD

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G NS U O N N ON US N SS M.B.A & Ph.D.- IITDSales

Rank Material Gauge - Description Jan Feb Mar Apr May Jun Jul Aug Sep

Total

(Pounds)

Monthly

Average

Standard

Deviation % RSD

From 0.030" Sheet

11 2025 0.002 Foil Annealed 551 0 0 0 0 0 0 0 0 551 61 184 300%

9 2026 0.010 Sheet Annealed 0 0 435 0 251 412 0 0 0 1,098 122 190 156%

Monthly Subtotal 551 0 435 0 251 412 0 0 0

90% Input required at yield 612 0 484 0 279 458 0 0 0 1,833 204 256 126%

From 0.015" Sheet

1 2040 0.015 Welded Tube .75" OD 296 936 2,989 1,366 2,468 989 657 528 1,392 11,623 1291 900 70%

5 2043 0.015 Welded Tube 1" OD 0 0 480 444 0 77 118 343 0 1,462 162 202 125%

7 2050 0.015 Welded Tube 1" OD With Cap 0 0 0 1,003 0 0 176 0 0 1,179 131 332 254%

18 2036 0.015 Sheet Annealed 108 0 13 56 0 27 0 0 1 205 23 37 163%

19 2046 0.015 Welded Tube 1.5" OD 0 0 0 0 40 0 133 0 0 173 19 45 232%

Monthly Subtotal 404 936 3,483 2,869 2,508 1,093 1,084 871 1,393

90% Input required at yield 449 1,040 3,870 3,188 2,787 1,215 1,205 967 1,548 16,269 1,808 1175 65%

From 0.125" Sheet

0.030" Sheet to Supply Above 612 0 484 0 279 458 0 0 0 1,833 204 256 126%

0.015" Sheet to Supply Above 449 1,040 3,870 3,188 2,787 1,215 1,205 967 1,548 16,269 1808 1175 65%

2 2031 0.020 Sheet Annealed 761 521 826 671 889 1,004 3,975 27 7 8,681 965 1184 123%

4 2041 0.020 Welded Tube .75" OD 0 50 316 3 379 0 2,856 0 0 3,604 400 933 233%

14 2044 0.020 Welded Tube 1.0" OD 0 0 0 32 241 108 4 0 0 386 43 83 193%

16 2039 0.020 Welded Tube .50" OD 0 0 181 142 0 0 0 0 0 323 36 72 200%

10 2051 0.022 Welded Tube 1.25" OD 0 0 0 1,014 0 0 0 0 0 1,014 113 338 300%

3 2035 0.030 Sheet Annealed 1,638 116 1,138 634 524 579 1,672 703 517 7,520 836 533 64%

13 2045 0.030 Welded Tube 1.0" OD 0 0 370 0 0 1 0 0 41 412 46 122 268%

15 2047 0.030 WELDED TUBE 1.5O" OD 0 255 100 0 0 0 0 0 0 355 39 87 221%

17 2052 0.035 Tube 1.25" OD 0 0 302 0 0 0 0 0 0 302 34 101 300%

8 2029 0.045 Sheet Annealed 137 122 430 18 37 16 0 368 5 1,133 126 163 130%

20 2012 0.045 4" Repair Disk 0 8 6 15 0 84 7 9 8 137 15 26 171%



From 0.250" Plate

0.125" Sheet to Supply Above 3,997 2,347 8,913 6,352 5,706 3,849 10,798 2,305 2,363 46,630 5181 3053 59%

6 2027 0.060 Plate Annealed 0 0 277 323 60 0 504 12 205 1,382 154 183 119%

12 2034 0.125 Plate Annealed 0 35 78 63 34 0 0 208 0 418 46 67 145%



From 4.0" Sheet Bar

0.250" Plate to Supply Above 4,996 2,978 11,585 8,423 7,251 4,811 14,128 3,156 3,210


Alloy 2Stephen C. Graves Copyright 2003All Rights Reserved


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M.B.A & Ph.D. IITD

Material

Monthly

Demand

Monthly

Sigma

Period

(Weeks)

Average

(Pipeline)

Period

Sigma

Service

Level

Reliability

Factor Buffer Safety Total

Alloy#1

0.125" Plate 4,104 1,213 1 947 583 95% 90% 958 191 2,10

0.030" Sheet , 474 273 % % 450 92 ,

oy

0.125" Plate , , 1,196 1,467 % % 2,412 361 ,

0.015" Sheet 1,808 1,175 1 417 564 95% 90% 928 135 1,48

Estimated Inventory Requirements


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LSM-306SupplyChainM

anagement

Documents

306 Scm Unit III