steven owen nicole robinson nina trujillo. background/problem coca-cola bottling company of north...

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Steven Owen Nicole Robinson Nina Trujillo

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Page 1: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Steven OwenNicole Robinson

Nina Trujillo

Page 2: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Background/Problem

Coca-Cola Bottling Company of North Texas

Inefficient Forecasting Model Simple linear regression Distributor guesswork

Relatively High Refill Rate on Machines Ave. of 55.13% Capacity refill ( 37 machines)

On average Machines are over ½ full upon refill

Page 3: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Background/Problem

Central Insurance 486 0.4279 21 9.902828571Ceramic Tile International 624 0.3461 10.5 20.56822857ColorWeb 440 0.3818 12.6 13.33269841Dallas Tile Corporation 376 0.4468 31.5 5.333231746Dallas Tile Corporation 336 0.6428 63 3.428266667DNS Electronics 486 0.5432 63 4.1904Dominos 1 196 0.5306 21 4.952266667Dominos 2 196 0.5306 21 4.952266667Dynamex Incorporated 368 0.1304 63 0.761701587

Page 4: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Objective

Estimate cost saving effectiveness of implementing real time inventory technologyDevelop a Linear Program to minimize costs in regard to stocking soft drink vending machinesUse simulation models to demonstrate effectiveness of new methods

Page 5: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology

Pick location of numerous vending machinesGather Data Machine capacity Distance between machines Actual days between service Average cans per day Costs

Fuel Labor

Page 6: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology

Simulations Over a period of 90 days Five Simulations

Constant Demand/Daily Refill/Previous Refill Rate Constant Demand/Daily Refill/New Refill Rate Constant Demand/Weekly Refill/New Refill Rate Variable Demand/Daily Refill/Previous Refill Rate Variable Demand/Daily Refill/New Refill Rate

Staggered Starting Inventory Uniform Distribution between .15 and 1

Page 7: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology-Simulation

Constant Demand Average Cans/Day = (Machine Capacity*Actual% Capacity

Fill)Actual Days Between

Service

Variable Demand Normal Distribution

μ = Average Cans/Day σ = 20% of Average Cans/Day

Page 8: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology – Refill Period

Refill Rate The percentage of inventory remaining that

determines the need for refilling on a specific machine. (Previous 55.13%, New 10%)

Daily Refill Machine would be refilled the day that it was

estimated to drop below the respective refill rate.

Weekly Refill Machine would be refilled at the beginning of the

week in which it was estimated to drop below the estimated refill rate.

Page 9: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology

Linear Programming Models Developed to optimize route distances on specific

days with more than two service locations

Page 10: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology -Linear Programming Model

Objective function:Minimize X01 + X02 +…+Xij ij = traveling from i ending at j.

(Respective distances as coefficients).

Subject to: X01 + X02 +…+X0j = 2 only two segments connecting to distributor.

X10 + X12 +…+X1j = 2 only two segments connecting to location #1. X20 + X21 +…+X2j = 2 only two segments connecting to location #2

. . = 2 . .

. . = 2 . .X60 + X61+…+X6j = 2 only two segments connecting to location #6

 

Page 11: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

#Central Insurance, Color Web, Dallas Tile, Dominos 2, Dynamex#dist_ccddd.lp minimize 17.9x01 + 17.9X10 + 9.0x02 + 9.0x20 + 20.7x03 + 20.7x30 +21.1x04 +21.1x40 + 18.9x05 + 18.9x50 + 6.0x21 + 6.0x12 + 19.8x31+ 19.8x13 + 6.5x41 + 6.5x14 + 13.2x51 + 13.2x15 + 25.5x32 + 25.5x23 + 12.1x42 + 12.1x24 +10.9x52 +10.9x25 +13.7x43 + 13.7x34 + 21.9x53 + 21.9x35 + 13.9x54 +13.9x45 subject tox01 + x02 + x03 + x04 + x05 = 2x01 + x12 + x13 + x14 + x15 = 2x02 + x12 + x23 + x24 + x25 = 2x03 + x13 + x23 + x34 + x35 = 2x04 + x14 + x24 + x34 + x45 = 2x05 + x15 + x25 + x35 + x45 = 2x01 + x13 + x35 + x05 <= 3 binary x01 x02 x03 x04 x05x12 x13 x14 x15x23 x24 x25x34 x35x45end

Linear Programming Example

Page 12: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Methodology - Calculations

Travel Cost = Distance of Route * $0.15 10 mpg * 1.50/gallon of fuel = $0.15/mileTravel Time = Distance of Route / 30mph Refill Time = .333 hours to refill each machine * number of machines on routeLabor Cost = $10/hour for labor * (Travel Time + Refill Time)

Page 13: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Analysis-ComparisonConstant Demand

ConstantPrevious-Daily New-Daily New-Weekly

Distance 2240.1 1424.6 662.5# of Machines 270 130 130

Travel Time 74.67 47.49 22.08Loading Time 89.91 43.29 43.29

Total Time 164.58 90.78 65.37

Travel Cost 336.015 213.69 99.375Labor Cost 1645.8 907.77 653.73Total Cost $1,981.82 $1,121.46 $753.11% Savings ---------------- 43.40% 61.99%

Page 14: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

$336.02

$213.69

$99.38

$1645.80

$907.77

$653.73

0

200

400

600

800

1000

1200

1400

1600

1800

Travel Cost Labor Cost

Constant Demand Travel/Loading

Previous-DailyNew-DailyNew-Weekly

Page 15: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Constant Demand Cost/Savings

$753.11

$1121.46

$1981.82

0

43.40%

61.99%

0

500

1000

1500

2000

2500

Previous-Daily

New-Daily New-Weekly

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Total Cost% Savings

Page 16: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Analysis-Comparison

Variable Demand Variation

Previous-Daily New-DailyDistance 3404.2 2576.8

# of Machines 483 267Travel Time 113.47 85.89

Loading Time 160.84 88.91Total Time 274.31 174.8

Travel Cost 503.63 386.52Labor Cost 2743.12 1748.04

Total Cost $3,253.75 $2,134.56

% Savings ---------------- 34.40%

Page 17: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

$503.63$386.52

$2743.12

$1748.04

0

500

1000

1500

2000

2500

3000

Travel Cost Labor Cost

Demand Variation Travel/Labor

Previous-Daily

New-Daily

Page 18: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Demand Variation Costs/Savings

$2134.56

$3253.75

0

34.40%

0

500

1000

1500

2000

2500

3000

3500

Previous-Daily New-Daily

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Total Cost

% Savings

Demand Variation Costs/Savings

$2134.56

$3253.75

0

34.40%

0

500

1000

1500

2000

2500

3000

3500

Previous-Daily New-Daily

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Total Cost

% Savings

Page 19: Steven Owen Nicole Robinson Nina Trujillo. Background/Problem Coca-Cola Bottling Company of North Texas Inefficient Forecasting Model  Simple linear

Conclusion/Recommendation

As our preliminary hypothesis suggested, there is considerable room for improvement in the efficiency in soft drink distribution.We recommend implementing a real time inventory system to capitalize on this cost saving opportunity.