Good Research Project Chitunha Shapaz

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Inventory Model Project Page 0

RESEARCH PROJECT:

INVENTORY MODEL FOR A FUEL

COMPANY

Done by

Xavier moyo

Applied Mathematics Department


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ABSTRACT

Fuel has and always will be a necessity for most if not all entities of this world.

The demand for fuel has always been high and it has maintained its status

regardless of the economic challenges that Zimbabwe has been facing. A state

owned petroleum company in Zimbabwe that supplies fuel to a number of

service stations and organisations around Zimbabwe. The company operates

under two Regional offices, that is Harare and Bulawayo, and has been

struggling to meet this demand thereby resulting in a lot of shortages.

The EOQ model was used in this project to help in the solution to these

shortages. It was discovered that the procurement officer was not keeping track

of the stationsinventory to make sure he orders in time before the fuel actuallyruns out. It was also discovered that the company was sometimes ordering more

than enough fuel in anticipation of a high demand, thereby losing a lot of moneyin storage fees and transportation charges. The procurement officer was

sometimes ordering too little fuel which was not sufficient to cater for the

demand of the product.

From calculations of the EOQ model, results were established to give the

procurement manager a guideline of how to manage the companys inventory.The results gave the amount of fuel that is supposed to be ordered each time and

the level of fuel that is supposed to trigger a new order (reorder point). A

conclusion was made that the model would work for this company and

recommendations were made on how to implement the results of the EOQ

model.


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ACKNOWLEDGEMENTS

Special thanks goes to the National Oil Company of Zimbabwe (NOCZIM)Southern Region Stock Control Manager, Mr. Musunda for allowing me to do a

research of the companys product.Special thanks also go to the NOCZIM staff in the Bulawayo office, for providing the information necessary for my project.

I would also like to thank my family members and fellow classmates, David

Zimmerman for his help and support during the research process and also for

giving me ideas on how to go about in doing my project. Thanks also goes to

my lecturer Mr.tino for his tireless efforts in teaching the concepts that were

required to be able to come up with my project, his efforts are greatly

appreciated.

A last but not least thanks goes to the Lord Almighty for his guidance and

protection throughout the course of my study of the project


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Contents

ABSTRACT ........................................................................................................................... 1

ACKNOWLEDGEMENTS ...................................................................................................... 2

1. INTRODUCTION ............................................................................................................ 4

2. LITERATURE REVIEW .................................................................................................. 5

3. METHODOLOGY ........................................................................................................... 5

4. DATA COLLECTION ...................................................................................................... 8

5. DATA ANALYSIS .......................................................................................................... 9

6. RESULTS ..................................................................................................................... 14

7. CONCLUSION .............................................................................................................. 16

8. RECOMMENDATIONS ................................................................................................. 17

APPENDICES...................................................................................................................... 18

REFERENCES ..................................................................................................................... 20


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1. INTRODUCTION

National Oil Company of Zimbabwe (NOCZIM) is a state enterprise

responsible for national procurement, storage and distribution of fuels and

lubricants.

NOCZIM procures Petrol and Diesel from IPMG in Kuwait, Middle East, and

supplies the whole of Zimbabwe. Supplies are divided into two groups:

i. Retail these are supplies to service stations like Elangeni Energy, BP,etc, for resale to other motorists.

ii. Commercial these are direct sales to organisations like Telone, NationalRailways of Zimbabwe, Kukura Kurerwa, etc

The NOCZIM Harare office is the companys central distribution centre. Allfuel procured from IPMG is stored in the companys depot and thendistributedto other depots as per their order. The other depots then supply customers with

fuel.

The NOCZIM Bulawayo office is responsible for supplying all customers in the

Southern Region. The Southern Region covers Bulawayo, Masvingo, and allcities and towns in Midlands, Matebeleland North and South Provinces.

However, NOCZIM does not have a depot of its own in Bulawayo. Therefore,

it makes use of BP depot and pays for all fuel stored there belonging to

NOCZIM.


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Since most large fuel supplying companies cannot import fuel in their own

capacities, they have had to rely on NOCZIMs fuel supply. This has increasedthe demand for fuel.

From analysis done by the Inventory Manager at the Bulawayo office, it seems

one of their major problems is that some of the customers cannot be predicted

their buying behaviour. This results in a difficulty to forecast the consumer

demand for fuel and hence difficulty in knowing how much and when to order

from the Harare office. This caused run-outs occurring time and again. Withsuch a trend, current customers and other prospective customers may be lost.

2. LITERATURE REVIEW

3. METHODOLOGY

Many companies in the world have experienced shortages in the products they

supply due to poor management of inventories. Other companies have sufferedlosses due to large unnecessary inventories which are also due to poor

management of inventories. The application of operations research techniques

in the area of inventory management has helped the business world to gain a

competitive edge in the market.

Inventory management involves:


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1. Formulating a mathematical model describing behaviour of the inventory

system

2. Seeking an optimal inventory policy with respect to the model.

3. Use a computerised information processing system to maintain a record

of the current inventory levels

4. Using this record of current inventory levels, apply the optimal inventory

policy to signal when and how much to replenish inventory.

Economic order quantity (EOQ) Model is the level of inventory that

minimizes the total inventory holding costs and ordering costs. EOQ

determines the point at which the combination of order costs and inventory

carrying costs are the least. The result is the most cost effective quantity to

order. In purchasing this is known as the order quantity, in manufacturing it is

known as the production lot size.The EOQ model is applicable where you haverepetitive purchasing or planning of an item, demand for a product is constant

over the year and each new order is delivered in full at one time when the

inventory reaches zero.

The model to be used in this particular project is called The Economic Order

Quantity Model (EOQ). The objectives of this model are to determine:

a) How much to order when the level of inventory drops

b) When to order to avoid shortages

The EOQ involves a continuous review of the following attributes:


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1. Demand- This is described as the number of units that will need to be

withdrawn from inventory for some use ( e.g. Sales) during a specific

period

2. Cost of Ordering- this is the cost of ordering a given product, the cost

comprises of transportation costs incurred per order. This cost is regarded

constant regardless of the order quantity.

3. Holding Cost- this figure represents all the costs associated with the

storage of the inventory until it is sold. By virtue that NOCZIM does not

own its own depot in Bulawayo it stores its products in BPs depot.Therefore the holding cost is charged by BP.

This project will be dwelling on all the attributes of the EOQ model to help the

NOCZIM (Bulawayo office) determine how much to order to minimise its

inventory costs and to determine the reorder points to avoid shortages. For

convenience sake, this project is only going to focus at the NOCZIM

Matshobana service station in Bulawayo.

1. Formulas

i. Determining how much to order when inventory level drops at the

same time minimising the total inventory costs

I =annual holding cost rate

C = unit cost of inventory item

Ch= annual cost of holding one unit in inventory

Ch= I C

Q= order quantity

D= Demand (constant)


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Co= cost of placing one order (constant)

Annual Holding Cost= QC h

Annual Ordering Cost= (D/Q) Co

Total cost= QC h + (D/Q) Co

Q*= Amount to order to minimize costs

Q*= 2DC o /C h

ii. Determining reorder points to avoid shortages

r = reorder point

d= daily demand

m= lead time (Time between inception of order and delivery)

r=dm

4. DATA COLLECTION

1. Choice of data to be collected

The main problem here is to determine the demand for fuel and the

amount of inventory required at the depots tanks in order to meet theestablished demand. Therefore the following data is to be collected:

a) Daily fuel redemption at the station for the month of December and

January


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2. How to collect data

a) Fuel reconciliation is done each day to show the amount of litresavailable, sold and lost. Then a monthly report is done (see Appendix

1 and 2)

b) A fuel requisition form is filled by customer when ordering

c) A loading instruction form is filled by NOCZIM Bulawayo office

going to depot to instruct supply of fuel.

5. DATA ANALYSIS

PETROL DIESEL

US$ US$

Cost 1.18 Cost 1.05

Transport Cost 0.03

Transport

Cost 0.03

Total 1.21 Total 1.08

Ordering Cost 1.21

Ordering

Cost 1.08

Fig1.1


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259209

192423

0

50000

100000

150000

200000

250000

300000

Petrol

Monthly demand of Petrol

December

January


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358146

308383

280000

290000

300000

310000

320000

330000

340000

350000

360000

370000

Diesel

Monthly Demand of Diesel

December

January

451632

666529

0

100000

200000

300000

400000

500000

600000

700000

December & January

Total demand for fuel in the two months

Petrol

Diesel


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The total demand in the two months is 451632 litres of petrol and 666529 litres

of diesel.

Calculations

Average Daily Demand:

Petrol: Diesel:

451632 62 = 7284.387 666529 62 = 10750.47

To the nearest litre this gives us an average daily demand of 7284 litres for

petrol and 10750 litres of diesel.

Annual Demand:

Petrol: Diesel:

7284 365 = 2658801 10750 365 = 3923921

(NB: 365 days is used for the service station because it is open every day of

the year including holidays.)

Weekly Demand:

Petrol: Diesel:

7284 7 = 50988 10750 7 = 75250

Amount of fuel to order:

The objective of this section is to obtain the amount of litres that need to be

ordered when the level of fuel drops, at the same time minimizing the total

annual costs incurred by the company. The following equation is to be used:

Q*= 2DC o /C h


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From Fig 1.1 the ordering costs are calculated as:

LC o = 0.03

Since BP Depot charges NOCZIM for storage cost, the holding cost iscalculated as:

Ch = 0.02

Petrol:

Q* = (2DC o)/C h

= (226588011.21)/0.02

= 321714921

= 17936.41327021654

17936 litres

Diesel:

Q* = (239239211.08)/0.02

=423783468

= 20586.00174876122

20586 litres

Re-order point:


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The lead time to order from NOCZIM Harare office is 3 days i.e. 1 day to sort

out order papers and 2 day for the truck to travel from Msasa (Harare) to

Bulawayo:

Petrol:

r = dm

= 2658801 3

= 7976403 litres

Diesel:

r = dm

= 3923921 3

= 11771763 litres

6. RESULTS

From the calculations done above, the results can be shown in the following

table:

Service Station

Entity Petrol Diesel

Q* 17936 litres 20586 litres

R 7976403 litres 11771763 litres


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Q.*- This is the minimum order quantity, meaning that this is the amount of

fuel in litres that the procurement officer needs to order each time an order for

more fuel is made in order to minimize costs incurred by the company.

r - This is the reorder point, meaning that each time the level of fuel gets to this

point in the tanks, the station manager is supposed to inform the procurement

officer to start ordering more fuel.

With the results obtained we can see that NOCZIM had a problem of sometimes

ordering too much fuel and sometimes ordering too little fuel. The procurement

officer was not also taking note of when to order fuel thus resulting in ordering

fuel before it is needed.

Sometimes fuel was ordered late and thus resulting in fuel shortages as one

customer could come and purchase all fuel that was left. Thus the company will

end up having a shortage.


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7. CONCLUSION

The conclusion thereby stands to say that National Oil Company of Zimbabwe

was using a poor inventory management system resulting in large financial

losses. The procurement manager should therefore use the results in the

previous chapter to make decisions on how much to order and when to order

more fuel.

This model will ensure that the stations never get dry, meaning there will

always be fuel at all times for clients who want to purchase fuel. This will

increase the companys efficiency resulting in increased customer faith and agreater competitive edge.

Ordering fuel before it is needed may result in failure to access storage thusresulting in an added cost of demurrage due to not offloading the product. Thus

this model will also reduce the companys incurred costs and thus increasing thecompanys profit which is one of the ma jor aims of any company.


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8. RECOMMENDATIONS

The procurement officer needs to continuously monitor the demand for fuel

because although this model is for a constant demand, it is recommended that

any changes in the demand be catered for in order to avoid further losses. The

demand is likely to increase because of the increased customer faith resulting

from better efficiency of the company, so the model will have to be recalculated

using the new figures.

The station managers will need to be vigilant in keeping up to date with their

balances of fuel to make sure they do not order before fuel is needed as it may

resulting in demurrage costs. Keeping up to date with their balances of fuel will

also ensure that they do not order after there is no more fuel. They should The

procurement officer will also need to be ready at all times to order more fuel so

as to minimise any delays in delivery which may cause run outs at the stations

because the lead time will have been tempered with.

National Oil Company of Zimbabwe can also invest in a fuel management

system that will manage the inventory of all the service stations in the Southern

Region. The system will use swipe cards and will automatically tell the stationattendant how much fuel is left in the tanks after each redemption. This will

help the station managers to keep track of how much fuel is left and be able to

keep track of the reorder point.

A manual with the results of this project must then be drafted and released in

the procurement department and the stations so that even when new employees


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are contracted by the company, they will know how to manage the inventory to

avoid losses.

APPENDICES

Appendix 1: Daily fuel Reconciliation for the month of December

DatePETROL DIESEL PETROL DIESEL PETROL DIESEL PETROL DIESEL

1/1/2010 1743 36175 28608 0 7995 3865 21890 323101/2/2010 21890 32310 29077 0 17259 9066 33700 232441/3/2010 33700 23244 14950 29434 7290 3103 40991 498001/4/2010 40991 49800 14420 0 13549 5567 42224 442001/5/2010 42224 44200 0 0 10962 4804 31458 344001/6/2010 31458 34400 28742 0 11378 17066 49066 202871/7/2010 49066 20287 0 0 6810 9785 42266 127241/8/2010 42266 12724 0 59241 6161 26527 36325 477251/9/2010 36325 47725 0 0 7059 5274 29276 39590

1/10/2010 29276 39590 0 0 3533 8272 25943 314561/11/2010 25943 31456 0 0 6737 11767 19276 196151/12/2010 19276 19615 0 0 8146 4216 11343 15395

1/13/2010 11343 15395 0 29525 4809 27066 6593 178751/14/2010 6593 17875 29027 29491 4815 10078 30683 374601/15/2010 30683 37460 0 0 5073 11669 25295 256761/16/2010 25295 25676 0 0 4900 6106 20261 196101/17/2010 20261 19610 0 29900 3139 3640 16743 449121/18/2010 16743 44912 28601 0 3612 8577 42460 365751/19/2010 42460 36575 0 0 3407 20418 39325 159911/20/2010 39325 15991 0 29775 4279 14658 34968 311251/21/2010 34968 31125 0 0 3266 10415 31785 209251/22/2010 31785 20925 0 29975 4577 8486 27793 41466

1/23/2010 27793 41466 0 0 4667 4290 23293 373161/24/2010 23293 37316 0 0 3195 4348 20226 329661/25/2010 20226 32966 0 0 5833 6905 14393 255001/26/2010 14393 25500 0 0 13770 4146 943 201501/27/2010 943 20150 28950 0 2700 5705 24287 154501/28/2010 24287 15450 0 35688 2733 20231 24287 285261/29/2010 24287 28526 0 29754 3664 17735 20653 404731/30/2010 20653 40473 0 0 3948 7412 16774 330231/31/2010 16774 33023 0 0 3157 7186 13737 25965

TOTAL 202375 302783 192423 308383

Opening Stock Received Redeemed Balance


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Appendix 2: Daily fuel Reconciliation for the month of January


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REFERENCES

Date Opening Stock Received Redeemed Balance

PETROL DIESEL PETROL DIESEL PETROL DIESEL PETROL DIESEL

1/1/2010 1743 36175 28608 0 7995 3865 21890 32310

1/2/2010 21890 32310 29077 0 17259 9066 33700 23244

1/3/2010 33700 23244 14950 29434 7290 3103 40991 49800

1/4/2010 40991 49800 14420 0 13549 5567 42224 44200

1/5/2010 42224 44200 0 0 10962 4804 31458 34400

1/6/2010 31458 34400 28742 0 11378 17066 49066 20287

1/7/2010 49066 20287 0 0 6810 9785 42266 12724

1/8/2010 42266 12724 0 59241 6161 26527 36325 47725

1/9/2010 36325 47725 0 0 7059 5274 29276 39590

1/10/2010 29276 39590 0 0 3533 8272 25943 31456

1/11/2010 25943 31456 0 0 6737 11767 19276 19615

1/12/2010 19276 19615 0 0 8146 4216 11343 15395

1/13/2010 11343 15395 0 29525 4809 27066 6593 17875

1/14/2010 6593 17875 29027 29491 4815 10078 30683 37460

1/15/2010 30683 37460 0 0 5073 11669 25295 25676

1/16/2010 25295 25676 0 0 4900 6106 20261 19610

1/17/2010 20261 19610 0 29900 3139 3640 16743 44912

1/18/2010 16743 44912 28601 0 3612 8577 42460 36575

1/19/2010 42460 36575 0 0 3407 20418 39325 15991

1/20/2010 39325 15991 0 29775 4279 14658 34968 31125

1/21/2010 34968 31125 0 0 3266 10415 31785 20925

1/22/2010 31785 20925 0 29975 4577 8486 27793 414661/23/2010 27793 41466 0 0 4667 4290 23293 37316

1/24/2010 23293 37316 0 0 3195 4348 20226 32966

1/25/2010 20226 32966 0 0 5833 6905 14393 25500

1/26/2010 14393 25500 0 0 13770 4146 943 20150

1/27/2010 943 20150 28950 0 2700 5705 24287 15450

1/28/2010 24287 15450 0 35688 2733 20231 24287 28526

1/29/2010 24287 28526 0 29754 3664 17735 20653 40473

1/30/2010 20653 40473 0 0 3948 7412 16774 330231/31/2010 16774 33023 0 0 3157 7186 13737 25965

TOTAL 202375 302783 192423 308383


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