1. MID-TERM EXAM/REVISION
Business Department
SPRING
MID-TERM EXAM/REVISION

2. Section A/Multiple Choice-Example-30%
1) Production/Operations Management is
A) responsible for producing goods
B) responsible for providing services
C) system that create goods or services
D) often referred to as the core of scientific management
2) Operations Management does not affect
A) The collective success or failure of companies’ POM
B) Companies’ financial resources
C) Companies’ system
D) Companies’ ability to compete

3. Section A/Multiple Choice-Example
3) Which of the following part indicates the three Basic Functions?
A) Finance, marketing and management
B) Finance, human resources and management
C) Marketing, operations and finance
D) Operations, finance and scientific management
4) The steps of the conversion of inputs into outputs are:
A) Input, process, transformation
B) Labor, control, goods
C) capital, land, service
D) Input, conversion process, output
5) The operations function involves __________
A) The transformation process of inputs into outputs
B) Feedback control
C) Value added process
Only goods process

4. Section A/Multiple Choice-Example
6) Which of the following is not one of the input concepts?
A) Labor
B) Information
C) Data
D) Legal constraints
7) In profit organization, value-added of output __________
A) is measured by prices that customers are willing to pay for only those goods
B) is measured by prices that customers are willing to pay for those goods and services.
C) is their value to society.
D) is difference between cost of inputs and price of output
8) The steam engine and advanced the use of mechanical power to increase productivity indicate__________
A)The concepts of standardised parts and interchangeable parts.
B) The handicraft era
C) The Industrial revolution era
D) The advantages of the division of labor

5. Section A/Multiple Choice-Example
9) Which of the following indicates the aim of forecasting?
A) Short term plan
B) Long term operational decision
C) Reduce risk and uncertainty
D) Predicting past
10) Time series forecast analysis depends on __________
A) Explanatory variables
B) Consumer surveys
C) methodologies
D) The past values
11) Which of the following is not one of example of strategies__________
A) Low cost
B) High quality
C) Flexible operation
D) Technology

6. Section A/Multiple Choice-Example
12) Which of the following is not one of the important concepts for Lean and JIT system?
A) Quality
B) Price
C) Skilled labour
D) time
13) Hungarian method is associated with__________
A) Matching process
B) Colomun reduction
C) One to one basis process
D) Penalty cost
14) Competitiveness is not based on__________
A) Pricing
B) Promotion
C) Customers’ needs
D) Time
15) Equality and the role of government is the difference between __________
A) Mass production and JIT
B) Opportunism and realism
C) Production and operations
D) capitalism and socialism

7. Section B/type 1-Example- Productivity-35%
Assume 40 hour weeks and an hourly wage of $12. Overhead is 1.5 times weekly labor cost. Material cost is $ 6 per pound.
Compute the average multi-factor productivity measure for each of the weeks shown.
Calculate the productivity growth rates throughout the weeks.
What do the productivity figures suggest? Draw the productivity figures and briefly explain.
Week
Output (units)
Workers
Materials (lbs) 1
30,000 6
450 2
33,600 7
470 3
32,200
460 4
35,400 8
480

8. Section B/type 1-Example- Productivity-35%
Week
Output (units)
Worker cost
12*40
Overhead cost
Materials cost
Total cost
MFP 1
30,000
2880
4320
2700
9900
3.03 2
33,600
3360
5040
2820
11220
2.99 3
32,200
2760
11160
2.89 4
35,400
3840
5740
12480
2.84

9. Section B/type 1-Example- Productivity-35%
Week 1- 12*40*6 =2880= worker cost
Week 1- 12*40*6 =2880* 1.5=4320= overhead cost
Week *6 = 2700=material cost
Week =9900 total cost
Week 1-MFP=output (units)/(labor+materials+overhead) =30000/9900= unit per dollar input

10. Section B/type 1-Example- Productivity-35%

11. Section B/type 2-Example-Productivity-35%
A firm has the following information for the last two years and if the capital cost and the inflation rate are 25% and 15% respectively.
Factor
Year 1
Year 2
Revenue
220
240
Labor 55 60
Materials 30 35
Overhead costs 20 25
Other costs 15
Stocks 95 85
Buildings 80 90
(a) Calculate TFP for year 1 and 2. Briefly explain
(b) Compute total labor productivity (TLP). Briefly explain

12. Section B/type 2-Example-Productivity-35%
(a) TFP for the two year...
Year 1
220/ (0.25)(95+80)=220/163.75=1,34
Year 2
240/1,15*(( (0,25)(85+90))=240/205.56= 1,16
TFP= (1,16-1,34)/1,34= - 13,4%

13. Section B/type 2-Example-Productivity-35%
(b) TLP for the two year...
TLP=
Revenue
labor+Overhead
TLP
Year 1: 220/(55+20)=2.93
Year 2: 240/1,15*(60+25)=2.45
( )/2.93= %
Decrease in labor productivity may stem from different economic reasons.
This answer should be improved…

14. Section C/type 1-Example-Trend Analysis-35%
Use the information in the following table and construct the forecast equation.
Use time series regression to forecast the petrol consumption (mn gallons) for the next four year.
Compute the correlation coefficient, determination of coefficient and standard deviation. Briefly explain
Draw the pattern for data as well as forecasting periods. Briefly explain.

15. Section C/type 1-Example-Trend Analysis-35%
YEAR
2004
2005
2006
2007
2008
2009
2010
2011
PETROLSALE(Y) 1 3 4 2 5

16. Section C/type 1-Example-Trend Analysis-35%
Year
Trend (t)
PETROLSALES (Y)
(t) SQ
Y*t
(y) SQ
(Σt) SQ
(ΣY) SQ
2004 1
2005 2 3 4 6 9
2006 12 16
2007 8
2008 5 25
2009 36 18
2010 7 49 35
2011 64 24
(sum) Σ 22
204
109 74
1296
484 a
1.678 b
0.238

17. Section C/type 1-Example-Trend Analysis-35%
Y9= (9) = 3.83 in 2012
Y10= (10) = 4.06 in 2013
Y11= (11) = 4.30 in 2014
Y12= (12) = 4.53 in 2015
Note: Petrol sales are expected to increase by mn gallons per year.
This answer should be improved.

18. Section C/type 1-Example-Trend Analysis-35%
Sxy = 1.36
Sxy is a measure of how historical data points have been dispersed about the trend line. If it is large (reference point in mean of the data) , the historical data points have been spread widely about the trend line and if otherway around, the data points have been grouped tightly about the trend.

19. Section C/type 1-Example-Trend Analysis-35%
r lies between -1 and 1, -1 is strong negative whereas 1 is strong positive. 0 means that there is no relationship between the two variables (x and y). In this case, there is a strong positive relationship between the two variables and if an increase in independent variable, it will be a rise in dependent variable.
R2=0.18. It varies between 0 and 1.0 means that there is no relationship between the two variables whereas 1 indicates that there is a perfect relationship. 18.0% variation in dependent variable can be explained by the variation happened in the independent variable. It is worth to emphasize that 82% shows unexplained part of the relationship.

20. Section C/Type2-Example-Forecast-35%
A company records indicate that monthly sales for a seven-month period are as follows:.

21. Section C/Type2-Example-Forecast-35%
a) Use a simple two-month moving average and single exponential smoothing technique to find the next period employing smoothing constant and 7. period forecast value are 21.3 and 0.4 respectively.
Use a simple two-month moving average and single exponential smoothing technique to find all periods. First month forecast value is 15.
c) Use RMSE error model and decide which technique is better explain the data (MA and ES).
d) Plot the monthly data, two-month moving average estimates as well as exponential smoothing estimates. Briefly explain the patterns.

22. Section C/Type2-Example-Forecast-35%

23. Section C/Type2-Example-Forecast-35%
MA02:
F3= 15+23/2=19
F8=21+24/2=22.5
***ES(α=0.4)
Ft = F (t-1)+α (A(t-1)-F(t-1))
F1= 15 (it is the average of series if it is not given)
F2= (15-15)=15
F8= ( )=21.2

24. Section C/Type2-Example-Forecast-35%

25. Section C/Type2-Example-Forecast-35%
(A - F )2
RMSE n = Σ
RMSE(MA02) = 3,11
RMSE(ES04) = 2,37
ES 04 is better explain the pattern of the data than MA 02 because ES 04 gives less error compared to MA 02.
This answer should be improved.

26. Section C/Type2-Example-Forecast-35%

27. Section D/Bonus 1-Example-VOGEL/NCW
NWC
To (Cost)
From supply
A $
B $
C $
Demand
Use Vogel method and calculate the optimal solution.
Use NCW method and calculate the optimal solution.
Discuss the answers calculated in section a and b.

28. Section D/Bonus 1-Example-NCW
NWC
To (Cost)
From supply
A $ 6* *
B $ *
C $ * *
Demand
A → 1 =90*6 =540
B → 1 =7*10 =70
B → 2 =3*175 =525
C → 2=5*10 =50
C → 3 =7*190=1330
NWC Total= 2,515
VOGEL total cost is 2465

29. Thanks