Supply Chain Management Lecture 14. Outline February 25 (Today) –Network design simulation...
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Transcript of Supply Chain Management Lecture 14. Outline February 25 (Today) –Network design simulation...
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
Measures of Forecast Error
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
MAPEn Mean absolute percentage error
Average of absolute percentage error
MSEn Mean squared error Average of squared error
Measures of Forecast 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)
MAPEn Mean absolute percentage error
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
• 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
Production parameters
• 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