z
UNIVERSITY OF TECHNOLOGY, JAMAICA
COLLEGE:
Business and Management
SCHOOL:
Business Administration
Assessment Examination, Semester 2, AY 2019/20
Module Name:
SUPPLY CHAIN MANAGEMENT
Module Code:
POM4010
Date:
May 11th, 2020
Theory/ Practical: Theory
Groups:
BBA4 POM & MKT
Duration:
72 hours
Instructions
This Assessment paper has 11 questions and looks at all sectors covered.
Do all questions and show all the necessary working.
You will have 72 hours after the paper is made available to Download,
Execute and Upload the Complete assessment. The Total Marks for
this Assessment is 100
Name : Tanecea Campbell
ID:
1702855
Group: Tuesday 1pm – 5pm
Question1.( 4 marks)
A prediction equation for starting salaries (in $1,000’s) and SAT scores was performed using
simple linear
regression. In the regression printout shown below, what can be said about the level of
significance for the overall model?
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.93501812
3
R Square
0.87425889
Adjusted R
0.86028765
Square
5
Standard Error
3.30729594
9
Observations
11
ANOVA
df
SS
MS
F
Significance
F
Regression
1
684.4652324 684.4652 62.5756
2.42144E-05
4
Residual
Total
9
10
98.44385847 10.93821
782.9090909
Coefficients Standard Error t Stat P-value Lower 95%
8.660080997 -3.36493 0.00832 -48.73108387
29.1406046
4
8
0.06544384
0.008273059 7.910476 2.42E- 0.046728866
1
05
Intercept
SAT
(a) SAT is not a good predictor for starting salary.
(b) Overall the model does not provide a good prediction equation.
(c) The significance level for SAT indicates the slope is not equal to zero.
(d) The significance level for SAT indicates the slope is equal to zero.
(a) The significance level for the intercept indicates the model is not valid.
Answer : C
Question2.( 3 marks)
.
Given that the MAD for the following forecast is 2.5, what is the actual
value in period 2?
Perio
Forecas
Actua
d
1
2
3
4
t
100
110
120
130
l
95
123
130
(a) 120
(b) 98
(c) 108
(d) 115
(e) none of the above
Answer : C
Question3( 2 marks)
.
. Enrollment in a particular class for the last four semesters has been 120, 126, 110, and
135.
The best
forecast of enrollment next semester, based on a three-semester moving average, would be
(a) 126.
(b) 135.
(c) 120.
(d) 123.
(e) 125.
Answer : D
Question4
Below is a table showing the demand (in ‘000 of boxes) for Red Stripe Beer.
a)
Calculate the 3, 4 and 5 Month Simple Moving Average forecasts( 4 marks)
Period
January
2011
February
March
April
May
June
July
August
September
October
November
December
Demand
‘000’s of
Cases of
Beers
3 Month
Simple
MA
4 Month Simple
MA
5 Month Simple MA
8
1
3
2
3
3
4
1
0
1
8
2
3
3
8
1
2
1
3
3
2
4
1
8+13+23= 14.7
3
13+23+34= 23.3
3
23+34+10=22.3
3
34+10+18=20.7
3
10+18+23= 17.0
3
18+23+38=26.3
3
23+38+12=24.3
3
38+12+13=21
3
12+13+32=19
3
8+13+23+34=19.5
4
13+23+34+10=20
4
23+34+10+18=21.3
4
34+10+18+23=21.3
4
10+18+23+38=22.3
4
18+23+38+12=22.8
4
23+38+12+13=21.5
4
38+12+13+32=23.8
4
8+13+23+34+10= 17.6
5
13+23+34+10+18= 19.6
5
23+34+10+18+23= 21.6
5
34+10+18+23+38= 24.6
5
10+18+23+38+12= 20.2
5
18+23+38+12+13= 20.5
5
23+38+12+13+32= 23.6
5
b)
Calculate the Exponential Smoothing Forecasts at Alpha = 0.3, 0.45 and
0.65.( 4 marks)
Period
Demand
‘000’s
Cases
Beers
of
of
Ex
Smoothing
Forecast @ a =
0.3
Ex
Smoothing
Forecast
@a=
Ex
Smoothing
Forecast
@a=
0.45
0.65
January
2016
February
8
8
8
8
13
8+0.3(13-8)=8
8+0.45(8-8)= 8 8
March
23
8+0.3(5)=9.5
April
34
May
10
June
18
July
23
August
38
September
12
October
8+0.45(13-8)=
10.25
9.5+0.3(23-9.5)=
10.25
13.6
+0.45(23+10.25
)= 16
13.6+0.3(34-13.6)= 16.0+0.45(3419.72
16.0)=24.1
19.72+0.3(1017.8
19.72=16.8
16.8+0.3(18-16.8)= 17.9
17.2
11.3
21.1
13
17.2+0.3(23-17.2)= 20.2
18.9
18.9+0.3(3828.2
18.9)=24.6
20.8
20.9
November
32
18.5
17.3
15.1
December
41
22.6
23.9
26.1
18.9
28.7
16.5
17.5
32.1
19
c)
Period
Using the MAD error analysis method, which is the preferred Forecasting
method to forecast the demand for Red Stripe Beer – 3 Month Simple Moving
Average or Exponential Smoothing @ alpha = 0.4 ?( 4 marks)
Demand
‘000’s
Cases
Beers
of
of
3 Month Simple
Moving Average
Ex Smoothing
Forecast
@ a = 0.4
January
2011
February
13
8+0.4(8-8)= 8
March
23
8+0.4(13-8)= 10
April
34
May
10
June
18
July
23
August
38
September
12
October
13
November
32
December
2011
January
2012
41
d)
ERROR
ActualSMA
MSE
MAPE
Error/ actual
19.3
372.49
0.57
13.3
176.89
1.33
4.3
18.49
0.24
2.3
5.29
0.1
21
441
0.55
14.3
204.49
1.19
11.3
127.69
0.86
11
121
0.34
22
484
0.54
8
8+13+23= 14.7
3
13+23+34= 23.3
3
23+34+10=22.3
3
34+10+18=20.7
3
10+18+23= 17.0
3
18+23+38=26.3
3
23+38+12=24.3
3
38+12+13=21
3
12+13+32=19
3
13+32+41= 28.7
3
10+0.4(23-10)=
15.2
15.2+0.4(3415.2)=22.7
22.7+0.4(1022.7)=17.6
17.6+0.4(1817.6)=17.8
17.8+0.4(2317.8)= 19.9
19.9+0.4(3819.9)= 27.1
27.1+0.4(1227.1)=21.1
21.1+0.4(13=21.1)
=17.9
17.9+0.4(3217.9)= 23.5
23.5+0.4(4123.5)=30.5
Use the preferred method to forecast demand for January 2012( 6 marks).
e) Repeat Question c using the MSE ( 3 marks)
f) Repeat Question c using the MAPE( 3 marks)
g)
What are your observations?( 6 marks)
In conclusion, table one is showing the period of January 2011 to April, the total demand for cases of
beer is 14.7. After four months the demand for cases of beer increased to 19.5. Then in five months the
demand of Cases of beer declined to 17.6. In table two, the year 2016 January to April the demand of
cases of beer there was a drastic increase each month. As examined the first two months of the year 2016
the Ex smoothing forecast of each moth is a total of 8. In March there was an increasing in the Ex
smoothing forecast from 8 to 11.3 then from 11.3 to 18.9 in April. There was a declining at the starting of
June. The months of July to September there was growth in the Ex smoothing forecast. At the final
months of the year December the Ex Smoothing ended at 26.1. In table there, the demand of cases of beer
for the first three months is the same of year 2016 in the previous table. After the first three month the
total; moving average is 14.7 when compared to the first four months there was an increase to 23.3.
According to the table the total number of MSE for the first 3 months is 372.49 then there was a greater
decline in the 4th month to 176.89. The total amount of Error Actual- SMA in the 3rd month is 19.3unlike
to the 4th month the Error Actual – SMA declined to 13.3.
Question ( 9 marks)
Based on the data collected from 30 shops island-wide by the producers of a new brand of
vegetable loaf as at December 2010, the regression analysis was run which produced the
summary output below:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.952413257
R Square
0.907091012
Adjusted
0.675425058
R Square
Standard Error
1.767131177
Observations
30
ANOVA
Significanc
Df
Regression
SS
4
Residual
25
Total
29
MS
F
135.9587 33.9896
5.78000
8
46.84129 3.12275
3
182.8
0
e
F
0.000241546
Standar
Coefficients
Intercept
X Variable 1
-4,650.0001
-20.0005248
d
Error
2.002465
19.50003
X Variable 2
30.0001546
1.400000
X Variable 3
6.95000038
0.080001
X Variable 4
0.3000075
0.220010
t Stat
P-value
Lower 95%
1.07E-07 20.4256009
0.00219
-0.1340466
2
0.67158
-0.2092916
2
0.00975 -0.12816526
2
0.23738 -0.02444292
1
Given:
Q = Quantity sold per month
P(in cents) = Price of the product = 700
shops are located = 13,500.
Monthly advertising expenditure = 8,000
Using the information above,
a)
b)
Develop the linear regression model for the Quantity of Vegetable Loaves demand
per month.
Y= - 4650.0001- 20.0005248x1 + 30.0001546x2 + 6.95000038x3 +
0.3000075x4
Ydemand – 4650 -20 (price) + 30 ( cp)+ 6.959 (PCI)+ 0.30 (MAE)
What is the quality of the model (estimator) developed?
R= 0.90 very good model
c) What is the relationship and the strength of the relationship
between Demand for the Vegetable Loaves and the Independent Variables as a
group?
r = 0.95 very strong positive relationship
d)
Compute the t-statistics for each variable and state whether it is
statistically significant at the 5% level.
-
e)
Forecast the Demand for Vegetable Loaves using the model developed
in part a), based on the given information.
Demand = - 4650 – 20 ( 700 ) + 30 ( 750)+ 6.95 (13500) + 0.3(8000)
-4650 – 14000+ 22500+93825+ 2400
= 100075
Question 6 ( 9 marks)
a)
Using the data below, develop a multi-regression model for the demand
for soft drink using excel.
b)
What is the quality of the estimator?
Answer: A good estimator is the one which provides an estimate with the following
qualities: unbiasedness, Consistency and efficiency
c)
What is the relationship and the strength of the relationship between
the dependent and independent variables?
Answer: The independent variable is the one that experimenter controls. The
dependent variable is the variable that changes in response to the independent
variable. The two variable maybe related by cause and effect. If the
independent variable changes, then the dependent variable is affected.
Correlation Coefficient ( r ) indicates both the strength and direction of the
linear relationship between the independent and dependent variable.
d)
Use the model to forecast the demand for soft drinks based on the values given.
Given the data below, gathered from 20 outlets in Kingston by the producers of a new Soft
drink as at December 2015.
Q
10
12
13
14
9
8
4
3
15
12
13
14
12
10
10
12
11
12
10
8
Given:
P
100
100
90
95
110
125
125
150
80
80
90
100
100
110
125
110
150
100
150
150
I
14
16
8
7
11
5
12
10
18
12
6
5
12
10
14
15
16
12
12
10
E
100
95
110
90
100
100
125
150
100
90
80
75
100
125
130
80
90
95
100
90
B
4
3
2
8
7
9
12
15
8
7
13
10
9
25
39
44
61
63
30
40
Q = Quantity (‘000) sold per month
P(in cents) = Price of the product = 70
I (in dollars) = per capita income of the persons in the area in which
the outlets are located = 6,500.
E (in dollars) = Monthly advertising expenditure = 1,000
B = Number of pizzas sold (per month in the area in which
the outlets are located.= 8,000.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.862413257
0.743756625
0.675425058
1.767131177
20
ANOVA
df
Regression
Residual
Total
Intercept
X1
X2
X3
X4
4
15
19
Coefficients
26.38826301
-0.08495248
0.051155946
-0.074501538
0.033945775
SS
MS
F
135.9587 33.98968 10.88452
46.84129 3.122753
182.8
Significance
F
0.000242
Standard
Error
t Stat
P-value Lower 95%
2.797465 9.43292 1.07E-07
20.42561
0.023034 -3.68811 0.002192
-0.13405
0.118299 0.432428 0.671582
-0.20099
0.025177 -2.95908 0.009752
-0.12817
0.027582 1.230713 0.237381
-0.02484
Upper
95%
32.35092
-0.03586
0.303305
-0.02084
0.092736
Lowe
95.0%
20.425
-0.134
-0.200
-0.128
-0.024
Question7( 9 marks)
Acne Electrical Company purchases a component used in the manufacture of automobile
generators directly from the supplier. Acne’s generator production operation requires 4,500
components per month.
Assume that the ordering costs are $50 per order, the unit cost is $85.50 per
component, and the annual holding costs are 10% of the value of the inventory. Acne
Electrical Company has 240 working days per year and a lead time of 5 days. Devise
an inventory policy for Acne Electrical Company to include:
  Economic Order Quantity
 
 
Q*= √2DS = √2*4500*12*50 = √5400000 = √6352941.18 = 2520.50
8.50*0.1
0.85
Ch
Annual Holding Costs

= Q* ch = 2520.50*0.85 = 1071.21
2
2
Annual Ordering Costs

= D * S = 5400 * 50 = 1071.22
  Total Annual Costs
= holding cost+ ordering cost
1071.21 + 1071.22 = 2142.43
  Maximum Inventory Level = EOQ


Average Inventory Level = EOQ 2
2520.50 = 1260.25
2
  Reorder Point
= daily demand * lead time
= 54000 * 5
= 270000

Number of Orders per year
=D
= 54000= 21.42
2520.50
Q*

  Cycle Time (Days)
= Q* = 2520.50 = 1260.25
22
Question8.( 9 marks)
a)
Harley Davidson has its engine assembly plant in Milwaukee and its motorcycle assembly plant
in Pennsylvania. Engines are transported between the two plants usingtrucks. Each truck trip
costs $1,000. The motorcycle plant assembles and sells 300 motorcycles each day. Each engine
costs $500 and Harley incurs a holding cost of 20 percent per year. How many engines should
Harley load onto each truck? What is the cycle inventory of engines at Harley?( 3 marks)
EOQ= √2DS
Ch
= √2 * 300*365*1000
0.2 * 500
=√219000000
100
= √2190000
Q*= 1479.86
Cycle Inventory = Q*/2
= 1479.86/2
=739.93
# of orders =D/Q*
= 109500/1479.86
= 73.99 ( 74 ) engines Harley should load 0
b)
Harley purchases components from three suppliers. Components purchased from Supplier A at price
$5 each, and used at the rate of 20000 units per month. Components purchased from supplier
B are priced at $4 each and used at the rate of 2,500 units per month. Components purchased
from Supplier C are priced at $5 each and used at the rate of 900 units per
month. Currently, Harley purchases a separate truck load from each supplier. As part of its JIT
drive, Harley has decided to aggregate purchase from the three suppliers. The trucking company
charges a fixed cost of $400 for the truck with an additional charge of $100 for each stop. Thus,
if Harley asked for a pick up from one supplier, charges $500; from two suppliers $600; and
from three suppliers it charges $700. Suggest a replenishment strategy for Harley that minimizes
annual cost. Harley incurs a holding cost of 20 percent per year. Compare the cost of your
strategy with Harley’s current strategy of ordering separately from each supplier. What is the
cycle inventory of each component at Harley?( 6 marks)
EOQA = √ 2*20000*12*500
0.2*5
= √240000000
1
=√240000000
Q*A= 15491.93
Cycle Inventory = Q*
2
= 15491.93
2
= 7745.97
EOQB = √2*2500*12*500
0.2*4
=√30000000
0.8
= √37500000
Q8B= 6123.72
Cycle Inventory = Q*
2
= 6123.72
2
= 3061.86
EOQc = √2*900*12*500
:
0.2*5
=√10800000
0.1
=√10800000
Q*c = 3286.34
Cycle Inventory= Q*
2
= 3286.34
2
= 1643.17
Question 9( 9 marks)
Georgia Products offer the following discount schedule for its 4- by 8-foot sheets of good
quality plyboard.
Home Sweet Home Company orders plyboard from Georgia Products. Home Sweet
Home has an ordering cost of $300. The carrying cost is 10%. And the annual demand is
6,000 sheets. What do you recommend?
Discount
Number
ORDE Unit
Price
R
(C)
1
0-100
$1,500
2
101 400
401 800
801
and
over
$1,450
3
4
$1,425
$1,400
Order Quantity
(Q)
Annual
Annual Ordering
Material Cost Cost
(D/Q * S)
(DC)
Annual
Carrying Cost
Total
(Q/2*Ch)
Cost
√2*6000*300/0.1*1 6000*1500=90 6000/
100/2*150*0.1 9009300
500= 154.92 (100) 00000
100*300=18000 =7500
√2*6000*300/0.1*1 6000*1450=87 6000/157.6*300= 157.6/2*1450* 8722847.32
450=157.6
00000
11421.32
0.1=11426
√2*6000*300/0.1*1 6000 *1425= 6000/401* 300= 401/2*142.5*0. 8583060.03
425=158.9 (401)
8550000
4488.78
1= 28571.25
√2*6000*300/0.1*1 6000*1400= 6000/801*300=22 801/2*140*0.1 8458317.19
400=160.35 (801) 8400000
47.19
= 5607
Question 10( 10 marks)
Michael’s limited, a manufacturer of Sliding Door Panels, is in need of an aggregate plan for 5
months of its operations. Its production manager was instructed to use the chase and level
strategy methods. Data of forecasted demand and operational parameters for the 5 months are as
shown below.
Data
1
2
3
4
5
6
7
8
no overtime allowed
no subcontracting allowed
regular cost of production
backorder cost of production
hiring cost
production/employee
firing costs
workforce
9
10
overtime cost of production
inventory carrying/holding
cost
hiring and firing is allowed
11
=
=
=
=
=
=
=
=
$60/unit
$9/unit
$90/unit
300 units per month
$300/unit
30 workers prior to start of production
cycle
$75/unit
$3/unit/month
Level Production Strategy
start with 30
Quarter Demand Reg
Inventory
Back
# of
Produc
orders
workers
tion
1
10500 14800 1480049
10500=4300
2
11500 14800 1480011500=
3300+ 4300=
7600
3
25000 14800
7600+14800=22
400-25000=2600
4
12000 14800 1480012000=2800=
2600=200
5
15000 14800
14800-12000=
2800 – 2600=
200-200= 0
74000
12100
2600
total
cost
total
7400/5= 14800
# Of workers = Production regular
Production/employee
Production Cost = 74000 x 60= 444000
Hiring Cost =
19 x 90 = 1710
Inventory cost = 12100 x 3 = 36300
Backorders= 2600x 9= 23400
505410
= 14800/ 300 = 49
# hired
19
# fired
Chase Production Strategy
Quarter Demand Regular # of
prdn.
worker
s
require
d
1
10500 10500 49
2
11500 11500
3
25000 2500
4
12000 12000
5
15000 15000
total
cost
total
74000
10500/300= 35
11500/ 300= 38
2500/300= 8
12000/30= 40
15000/300= 50
start with 30
# of
# hired # fired
workers
availabl
e
30
35
8
40
50
19
35-30=5
35-8= 27
40-8=32
5040=10
47
46
74000
Production Cost = 74000 x 60 = 4440000
Firing Cost = 46 x 300 = 13800
Hiring Cost = 47 x 90 = 4230
4458030
Develop aggregate production plans using the tabular format shown above,
and complete the table.( 8 marks)
i
ii
Which plan should the manufacturer choose and why?
(2 marks)
Answer: Chase production strategy would be a better fit than level production strategy because it is
cheaper.
Question 11( 6 marks)
Explain the six distinct distribution network designs that may be used to move products from
factory to customer. ( 9 marks)
Answer: In manufacture storage with direct shipping, product is shipped directly from the
manufacture to the end customer, bypassing the retailer. This option is also referred to as drop
shipping with product delivered directly from the manufacture to the customer location.
Manufacture storage with direct shipping and in- transfer merge is similar to pure drop shipping,
except that pieces of the order coming from different locations are combined so that the
customer gets single delivery.
Distributor Storage with package carrier delivery is being used when inventory is not held by
manufactures at the factories, but is held by distributors/retailers in intermediate warehouses, and
package carries are used to transport products from the intermediate location to final customer.
Distributor storage with last mile delivery is being used when the distributor/retailer delivers
the product to the customer’s home instead of using a package carrier.
Manufacture/distributor storage with customer pickups is being used when inventory is stored at
the manufacture or distribution warehouse but customer place their orders online or on the
phone and then come to designed pickup point to collect their orders
Retail storage with customer pickup is being used when inventory is stored locally at retail
stores and customers walk into the retail store or place an order online or on the phone and pick
it up at retail store.
END OF EXAMINATION