Question

TourneSol Canada, Ltd. is a producer of high quality sunflower oil. The company buys raw sunflower seeds directly from large agricultural companies, and refines the seeds into sunflower oil that it sells in the wholesale market. As a by-product, the company also produces sunflower mash (a paste made from the remains of crushed sunflower seeds) that it sells into the market as base product for animal feed.

The company has a maximum input capacity of 150 short tons of raw sunflower seeds every day (or 54,750 short tons per year). Of course the company cannot run at full capacity every day as it is required to shut down or reduce capacity for maintenance periods every year, and it experiences the occasional mechanical problem. The facility is expected to run at 90% capacity over the year (or on average 150 x 90% = 135 short tons per day).

TourneSol is planning to purchase its supply of raw sunflower seeds from three primary growers, Supplier A, Supplier B, and Supplier C. Purchase prices will not set until the orders are actually placed so TourneSol will have to forecast purchase prices for the raw material and sales prices for the refined sunflower oil and mash. The contract is written such that TourneSol is only required to commit to 70% of total capacity up front. Any amounts over that can be purchased only as required for the same price. Historical prices for the last 15 years are in the table below (note that year 15 is the most current year).

Historical Price Data
Marketing Year	Seed Average Price Index $/short ton	Oil Average Price Index $/short ton	Mash Average Price Index $/short ton
1	127.7	317.8	63
2	192.4	465	87
3	242	662.2	105
4	242	668.2	111
5	274	791.3	124
6	242	732	108
7	290	951	134
8	347.2	1123	153
9	436	1297.3	193
10	422.8	1312	187
11	466	1416	193
12	582	1664	247
13	508	1317.4	242
14	428	1182.4	197
15	434	1334.4	210

Sunflower oil contains a number of fatty acids, some which are desirable in food products and others that are not. One desirable fatty acid is oleic acid. TourneSol produces high oleic oil for the wholesale market, and requires that the oleic acid content be a minimum of 77%. Sunflower oil also contains trace amounts of iodine. The market requires that that iodine content be a minimum of 0.78% and maximum of 0.88%

The oleic acid and iodine content for the sunflower seeds from the three suppliers is given in the table below.

Supplier	Oleic Acid	Iodine
A	72%	0.95%
B	82%	0.85%
C	65%	0.72%

For all three suppliers, it is expected that the average yield of oil from the seeds is 30%. There is no net loss of material, so the yield of mash from the same supply is expected to be 70%.

Because the oleic acid and iodine content varies across the three suppliers, so does the price. It is expected that the cost of supply from the suppliers will be a percentage of the market average price of seeds.

Supplier	Cost as % of Average Market Price of Seed
A	85%
B	100%
C	90%

The company faces an additional variable production cost of $10/short ton and an estimated fixed cost of $1,750,000 over the upcoming production period.

The company is asking you to provide a recommendation on the amount of raw material it should purchase from each supplier to minimize its cost of feedstock.

Management is also looking for an analysis on the profitability of the company in the next production cycle.

Formulate a linear program in Excel to minimize the cost of raw sunflower seeds. Use the average price of seeds forecasted from the previous step in order to determine supplier prices.

Perform a cost-volume-price analysis using the average cost per short ton average selling price per short ton.

Answer 1

ANS

One can see that three is a considerable increasing trend in the data. Hence, it would be easier to use the regression analysis. spreadsheet for regression analysis as shown below Now, create a A C D 2 Year Seed Oil Mash 317.8 63 3 1 127,7 465 87 4 2 192.4 662.2 242 5 3 105 668.2 6 4 242 111 791.3 274 7 5 124 732 951 242 8 6 108 290 9 7 134 347.2 153 10 8 1123 436 1297.3 1312 11 9 193 422.8 12 10 187 193 1416 13 11 466 582 1664 247 242 14 12 1317.4 1182.4 1334.4 15 13 508 197 16 14 428 210 17 15 434 18 16 -SLOPE(C3:C17,SA$3 : SAS17) 20 InterceptINTERCEPT( B3:B17,SAS3: SAS17)-INTERCEPT(C3:C17,SAS3:SAS17)- INTERCEPT(D3:D17,SAS3:SAS17) - SLOPE(D3:D17,SA$3: SAS17) 19 Slope =SLOPE(B3:B17,SA$3:SAS17)

E H J 1 Forecast Squared Error for (MSE) 2 Seed Oil Mash Seed Oil Mash ( E3 - B3 )2 -(E4-B4) 2 - ( E5 - B5 ) 2 -F3-С3у2 F4-C4) 2 - ( F5- C5 ) 2 - ( G3 - D3 ) 2 - (G4- D4 ) 2 - ( G5 - DS ) 2 3 BS20+BS19 SA3 -C$20+C$ 19 *SA3 -DS20+ DS 19* SA3 -BS20+BS 19 SA4 5BS20+B$19 SAS -CS20+C$ 19* SA4 -DS20+ DS 19 * SA4 -CS20+C$19 SAS -CS20+CS19 SA6 -CS20+C$19*SA7 =D$20+ D$ 19*SAS -(F6-C6)2 - ( F 7 - C7 ) -2 6 B$20+BS19 SA6 -DS20+ DS 19 * SA6 (E6-B6) 2 -(G6-D6) 2 7BS20+BS19 SA7 8BS20+BS19 SA8 -BS20+ BS 19 * SA9 - ( G7 - D7 ) 2 -(G8 - D8 ) 2 - ( G9 - D9 ) 2 - ( G10 - D10) 2 - ( Gl1-DI1) 2 -(G12 - D12 ) 2 - ( G13- D13 ) 2 -(G14-D14)2 -( G15- D15 ) 2 -(G16-D16 )2 - (G17 - D17 ) 2 BS20+BS19 SA18-CS20+CS19*SA18 DS20+DS19*SA18-AVERAGE(H3:H11-AVERAGE(13:117)-AVERAGE(J3:J17) - ( E7 - B7 ) 2 -DS20+ D$ 19* SA7 -(F8-C8)2 -( F9- C9 ) - 2 CS20+C$19*SA8 -DS20+ DS 19 * SA8 (E8-B8) 2 - 10 BS20+BS19 SA10 11B$20+ BS19 SA11 12 B$20+BS19 SA12 -DS20 + DS 19 * SA9 -D$20+D$19 *SA10 - (E9 - B9 ) 2 (E10-B102 -(El1 - B11 ) 2 (E12-B12) 2 CS20+ CS 19* SA9 -C$20+C$19*SA10 -(F10-C10) 2 - ( F11 - C11 ) 2 (F12-C12) 2 - ( F13- C13 ) 2 F14-C14) 2 -( F15-C15)2 (F16-C16) 2 - ( F17 - C17 ) - 2 -DS20+ DS 19 *SA1 CS20+C$19*SA11 -CS20+CS19* SA12 -CS20+C$ 19 *SA13 CS20+C$19* SA14 - CS20+C$ 19* SA15 -DS20+DS19* SA12 13 BS20+BS19*SA13 -DS20+ DS 19* SA13 -(E13-B13)2 DS20+DS19 SA14 DS20+ DS19 SA15 (E14-B14) 2 (E15-B15 ) 2 14 BS20+BS19 SA14 15 B$20+B$19 $A15 16 BS20+BS19 SA16 CS20+CS19 $A16 -DS20+DS 19 * SA16 (E16-B16) 2 - CS20+ C$ 19*SA17 -DS 20+ DS 19 *SA17 - ( E17 - B17 ) 2 17 BS20+BS19 SA17 18 19 MSE MSE MSE The result of this spreadsheet is shown below:

Forecast Squared Error for (MSE) Year Seed Oil Mash Seed Oil Mash Seed Oil Mash 127.70 317.80 63.00 192.40 465.00 87.00 242.00 662.20 105.00 218.02 242.00 668.20 111.00 244.21 274.00 791.30 124.00 270.39 242.00 732.00 108.00 296.57 290.00 951.00 134.00 322.76 347.20 1123.00 153.00 348.94 436.00 1297.30 193.00 375.12 422.80 1312.00 187.00 401.31 466.00 1416.00 193.00 427.49 582.00 1664.00 247.00 453.67 508.00 1317.40 242.00 479.86 428.00 1182.40 197.00 506.04 434.00 1334.40 210.00 532.22 21402 165.66 464.10 73.38 1441 108 2 191.84 542.88 85.32 0 6066 3 575 3 621.67 97.25 1643 60 4 700.45 109.19 5 1040 3 779.24 5 121.13 13 145 8 6 858.03 133.06 2978 15883 628 936.81 7 145.00 1073 201 121 1015.60 156.93 3 11535 15 1094.39 3706 9 168.87 41174 582 180.80 462 10 1173.17 19273 38 11 1251.96 192.74 1483 26909 12 1330.75 204.68 16468 111058 1791 216.61 645 13 1409.53 792 8488 93586 14. 1488.32 228.55 6090 995 9648 15 1567.11 240.48 54152 929 S558.41 S1,645.89 S252.42 2982.5 16 27503.7 395.2 26.18 78.79 Slope Intercept 139.47 385.31 11.94 MSE MSE MSE 61.45 follows The requirement forecast for the three is as Seed Oil Mash S558.41 S1,645.89 $252.42

I HOPE THIS ANSWER IS HELPFUL......................................

...........................THANK YOU...........................................