Lecture 14

Supply Chain Management

Lecture 14

Outline

• February 25 (Today)– Network design simulation description– Chapter 8– Homework 4 (short)

• March 2– Chapter 8, 9– Network design simulation due before 5:00pm

• March 4– Simulation results– Midterm overview– Homework 4 due

• March 9– Midterm

Measures of Forecast Error

Error measure Formula

Et Forecast Error Ft - Dt

Biast Bias ∑tn=1 Et

At Absolute Deviation |Et|

MADn Mean absolute deviation (1/n)*∑nt=1 At

TSt Tracking signal Biast / MADt

MAPEn Mean absolute percentage error

(1/n)*∑nt=1 (At / Dt)*100

MSEn Mean squared error (1/n)*∑nt=1 Et

2


Error measure Description

Et Forecast Error Forecast – Demand

Biast Bias Sum of errors

At Absolute Deviation Absolute error

MADt Mean absolute deviation Average of absolute error

TSt Tracking signal Biast / MADt


Average of absolute percentage error

MSEn Mean squared error Average of squared error


Error measure Desired outcome / Use

Et Forecast Error Close to zero

Biast Bias Close to zero

At Absolute Deviation Close to zero

MADt Mean absolute deviation STDEV(Et) 1.25 MADt

TSt Tracking signal Stay within (-6, +6)


Stay under 10% (30% not uncommon)

MSEn Mean squared error VAR(Et) MSEt

Simulation Assignment (25%)

• Design the supply chain network for Jacobs Industries on the fictional continent of Pangea– Jacobs only product is an industrial chemical that can be mixed

with air to form a foam (used in air conditioner retrofit kits)

Demand

• Demand for Jacob’s product in Pangea– Existing and new markets

Air conditioner retrofit kit

Hardwood floor laminates

Premium home appliancesPremium home

appliancesInsulation products

Demand

• Average demand for Jacob’s product in Pangea– Existing and new markets

0

20

40

60

80

100

120

1 145 289 433 577 721 865 1009 1153 1297 1441

0

20

40

60

80

100

120

140

1 145 289 433 577 721 865 1009 1153 1297 1441

0

2

4

6

8

10

12

14

16

18

1 142 283 424 565 706 847 988 1129 1270 1411

0

2

4

6

8

10

12

14

16

18

1 142 283 424 565 706 847 988 1129 1270 1411

0

2

4

6

8

10

12

14

16

18

1 142 283 424 565 706 847 988 1129 1270 1411

250

Assignment

• Jacobs management would like to design a supply chain network for Pangea. It’s current network consist of a factory in Calopeia with a capacity of 20. You have been hired to suggest a network design that will maximize profits for Jacobs Industry. Designing such a network is complex and includes the following decisions:– Should the factory in Calopeia be expanded? – Should factories in other regions be built? If so, what should their

capacity be?– What regions should each factory serve?

TotalFactory? Capacity? Calopeia Sorange Tyran Entworpe Fardo

Calopeia YES 40 YES YES YES YES YESSorange

TyranEntworpe YES 20 YES YES YES YES NO

Fardo

Serve region?

Production parameters

20


• A factory must serve the region in which it is located

300


20

20 20

20

20


• You have $20,000,000 to design your network• The cost of building a factory is $500,000

regardless of the factory capacity• The cost of capacity is $50,000

20

5500,000 + 5*50,000 =

$750,000


• You have $20,000,000 to design your network• The cost of building a factory is $500,000

regardless of the factory capacity• The cost of capacity is $50,000

40

5500,000 + 5*50,000 =

$750,000

20*50,000 = $1,000,000

Transportation parameters

• Finished drums are shipped from the factory warehouse by mail to the customers

• Factories may ship to all the regions in Pangea• Shipping time is 1 day independent of origin and

destination

To Calopeia To Sorange To Tyran To Entworpe To FardoFrom Calopeia 50 100 100 100 200From Sorange 100 50 100 100 200From Tyran 100 100 50 100 200From Entworpe 100 100 100 50 200From Fardo 200 200 200 200 50

Financial and Other Parameters

• All customers pay $1450 per drum and the production cost is $1200 per drum

• The drum must be shipped within 24 hours of receiving the order or the order is lost

• Orders may be partially filled and one order may be filled from multiple factories

• Each factory has warehouse space to hold up to 500 finished drums– If warehouse space is used completely, the factory will remain idle

until warehouse space becomes available

• Interest accrues on cash at 10% per year, compounded daily

The Goal

• Your network design will run from day 1 till day 1460

• Investment in capital (such as new factories and factory capacity) will become obsolete on day 1460

The winning team is the one with the highest cash position on day 1460

From Forecasting to Planning

0

500

1000

1500

2000

2500

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Month

Dem

and

Forecast

Capacity

How should a company best utilize the resources that it has?

Aggregate Planning Strategies

• Basic strategies– Level strategy (using inventory as lever)

• Synchronize production rate with long term average demand• Swim wear

– Chase (the demand) strategy (using capacity as lever)• Synchronize production rate with demand• Fast food restaurants

– Time flexibility strategy (using utilization as lever)• High levels excess (machine and/or workforce) capacity• Machine shops, army

– Tailored strategy• Combination of the chase, level, and time flexibility

strategies

Aggregate Planning

• Aggregate planning involves aggregate decisions rather than stock-keeping unit (SKU)-level decisions for a medium term planning horizon (2-18 months)

All-Terrain Vehicle (ATV)

EngineAssembly

Transmission

Model A Model B Model C Automatic Manual

Case Study Results

• In general, the chase strategy is used when– Products are valuable– Products are bulky or hard to store– Products are perishable or carry an appreciable risk of

obsolescence– High variety

• Accurate sales predictions are hard to obtain making stockpiling hazardous

• Fashion items

• In general, the level strategy is used when– Operators take a long time to become proficient at critical tasks– Products with negligible probability of obsolescence– Low variety

• Forecasts are quite good

Importance of Aggregate Planning

Without a sufficiently long-term view one may make short-term decisions that hurt

the organization in the long-term

Importance of Aggregate Planning• Aggregate planning at Henry Ford Hospital

involves matching available capacity, workers, and supplies to a highly variable customer demand pattern

Importance of Aggregate Planning• Aggregate planning at Henry Ford Hospital

involves matching available capacity, workers, and supplies to a highly variable customer demand pattern– 903 beds arranged into 30 nursing units– Cost $5,000 of turning away a patient (simple cases) – Cost of one idle 8-bed module is $35,000/month or

$420,000/year– High degree of demand variability

• Demand for beds could change by as many as 16% in less than two weeks

Importance of Aggregate Planning

• Shortly after Henry Ford Hospital reduced staff, it determined the staff was needed– New staff was recruited– Both staff reduction and recruiting costs were incurred

Without a sufficiently long-term view one may make short-term decisions that hurt

the organization in the long-term

Aggregate Planning

• Aggregate planning– A general plan that determines ideal levels of capacity,

production, subcontracting, inventory, stockouts, and even pricing over a specified time horizon (i.e. planning horizon)

• Production rate (number of units to produce)• Workforce (number of workers needed)• Overtime (number of overtime hours)• Machine capacity level (machine capacity needed)• Subcontracting (subcontracted capacity)• Backlog (total demand carried over to future periods)• Inventory on hand (total inventory carried over to future

periods)

Generic tool, call it Shovel

Example: Aggregate planning at RedTomatoTools

• RedTomatoTools– A small manufacturer of gardening equipment

Shovels

Spades

Forks

Demand forecast

0

1,000

2,000

3,000

4,000

1 2 3 4 5 6

Inputs of an Aggregate Plan

• Demand forecast in each period• Production costs

– labor costs, regular time ($/hr) and overtime ($/hr)– subcontracting costs ($/hr or $/unit)– cost of changing capacity: hiring or layoff ($/worker) and cost of

adding or reducing machine capacity ($/machine)

• Other costs– Labor/machine hours required per unit– Inventory holding cost ($/unit/period)– Stockout or backlog cost ($/unit/period)

• Constraints– Limits on overtime, layoffs, capital available, stockouts and

backlogs

Example: Red Tomato Tools

• Constraints– Workforce, hiring, and layoff constraints– Capacity constraints– Inventory balance constraints– Overtime limit constraints– Inventory at end of Period 6 is at least 500– Stockout at end of Period 6 equals 0

Example: Red Tomato Tools

Aggregate plan decision variablest Ht Lt Wt Ot It St Ct Pt

Month Period Hired Laid off WorkforceOvertime Inventory Stockout SubcontractProductionDecember 0 0 0 80 0 1000 0 0January 1 0 0 0 0 0 0 0 0February 2 0 0 0 0 0 0 0 0March 3 0 0 0 0 0 0 0 0April 4 0 0 0 0 0 0 0 0May 5 0 0 0 0 0 0 0 0June 6 0 0 0 0 0 0 0 0

Table 8-1Month Period Demand PriceJanuary 1 1,600 40February 2 3,000 40March 3 3,200 40April 4 3,800 40May 5 2,200 40June 6 2,200 40

Average Flow Time

• Average flow time– Average time one unit spends in inventory

Average inventoryThroughput

Average flow time =

9921775125847558

308

Average Inventory

Average Inventory = (0.5(I0 + I1) + 0.5(I1 + I2) +

0.5(I2 + I3) + 0.5(I3 + I4) + 0.5(I4 + I5) +

0.5(I5 + I6))/6

t ItMonth Period InventoryDecemb 0 0January 1 1983February 2 1567March 3 950April 4 0May 5 117June 6 500

Average Inventory

Average Inventory = (0.5I0 + 0.5I1 + 0.5I1 + 0.5I2 +

0.5I2 + 0.5I3 + 0.5I3 + 0.5I4 + 0.5I4 + 0.5I5 +

0.5I5 + 0.5I6)/6

t ItMonth Period InventoryDecemb 0 0January 1 1983February 2 1567March 3 950April 4 0May 5 117June 6 500

019831567950

0117250

Average Inventory

Average Inventory = (0.5I0 + 0.5I6 + I1 + I2 + I3 + I4 + I5)/6

= (0.5(I0 + I6) + I1 + I2 + I3 + I4 + I5)/6t It

Month Period InventoryDecemb 0 0January 1 1983February 2 1567March 3 950April 4 0May 5 117June 6 500

Average Flow Time

• Little’s Law

1

10

11 )(

2

11)(

2

11Inventory Average

T

ttT

T

ttt III

TII

T

T

ttD

T 1

1Throughput Average

Average inventoryThroughput

Average flow time =

Documents

Lecture 14