1. © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision MGMT 405, Production Man. REVISION Business Department FALL 2013-14

2. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 2 Section B/type 1-Example- Section B/type 1-Example- Productivity  Assume 40 hour weeks and an hourly wage of $12. Overhead is 1.5 times weekly labor cost. Material cost is $ 6 per pound. (a)Compute the average multi-factor productivity measure for each of the weeks shown. (b)Calculate the productivity growth rates throughout the weeks. (c) What do the productivity figures suggest? Draw the productivity figures and briefly explain. WeekOutput (units)Workers Materials (lbs) 130,0006 450 233,6007 470 332,2007 460 435,4008 480

3. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 3 Example- Example- Productivity Week Output (units) Worker cost 12*40 Overhead cost Material s cost Total cost MFP 130,0002880 4320270099003.03 233,6003360 50402820112202.99 332,2003360 50402760111602.89 435,4003840 57402880124802.84

4. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 4 Example- Example- Productivity Week 1- 12*40*6 =2880= worker cost Week 1- 12*40*6 =2880* 1.5=4320= overhead cost Week 1- 450*6 = 2700=material cost Week 1- 2880+4320+2700=9900 total cost Week 1-MFP=output (units)/(labor+materials+overhead)=30000/9900= 3.03 unit per dollar input

5. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 5 Section B/Type2-Example-Forecast A company records indicates that monthly sales for a twelve-month period are as follows:. PeriodSales 186 293 388 489 592 694 791 893 996 1097 1193 1295

6. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 6 Example-Forecast a) Use a simple three-month moving average and single exponential smoothing technique to find the next period employing smoothing constant and 12. period forecast value are 0.5 and 94.28 respectively. b) Use a simple three-month moving average and single exponential smoothing technique to find all periods. c) Use RMSE error model and decide which technique is better explain the data (MA and ES). d) Plot the monthly data, three-month moving average estimates as well as exponential smoothing estimates. Briefly explain the patterns.

7. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 7 Example-Forecast Period Sales MA03ES(α=0.5) 1 86 2 93 86 3 88 89.5 4 89 88.75 5 92 9088.875 6 94 89.6666790.4375 7 91 91.6666792.21875 8 93 92.3333391.60938 9 96 92.6666792.30469 10 97 93.3333394.15234 11 93 95.3333395.57617 12 95 95.3333394.28809 Next period 9594.64404 MA03: TT4= 88+93+86/3=89 TT13=95+93+97/3=95

8. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 8 Example-Forecast MA03: TT4= 88+93+86/3=89 TT13=95+93+97/3=95 ***ES(α=0.5) TTt = TT (t-1)+α (GT(t-1)-TT(t-1)) TT1= 86 (it is the average of series if it is not given) TT2= 86+0.5(86-86)=86 TT3=86+0.5(93-86)=89.5 TT4=89.5+0.5(88-89.5)=88.75 TT13=94.29+0.5(95-94.29)=94.64

9. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 9 Example-Forecast period Sales MA03ES05EMA03SQEMA03EES05SQEES05 1 86 00 2 93 86 749 3 88 89.5 -1.52.25 4 89 89.0088.75000.250.0625 5 92 90.0088.875243.1259.765625 6 94 89.6790.43754.3318.777783.562512.69141 7 91 91.6792.21875-0.670.444444-1.218751.485352 8 93 92.3391.609380.670.4444441.3906251.933838 9 96 92.6792.304693.3311.111113.695312513.65533 10 97 93.3394.152343.6713.444442.847656258.109146 11 93 95.3395.57617-2.335.444444-2.5761718756.636662 12 95 95.3394.28809-0.330.1111110.7119140630.506822 139594.6440410.67Σ=53.7777817.28808594Σ=106.0967

10. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 10 Example-Forecast (A - F ) 2 RMSE n = RMSE(MA03) = 2.44 RMSE(ES05) = 2.97 MA is better explain the pattern of the data than ES05 cause MA gives less error compared to ES.

11. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 11 Example-Forecast

12. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 12 Section C/type 1-Example-Trend Analysis 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.

13. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 13 Example-Trend Analysis YEAR 20042005200620072008200920102011 PETROLSALE(Y) 13421353

14. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 14 Example-Trend Analysis Year Trend (t) PETROLSALES (Y)(t) SQY*t(y) SQ(Σt) SQ(ΣY) SQ 200411111 200523469 20063491216 2007421684 2008512551 20096336189 201075493525 20118364249 (sum) Σ3622204109741296484 a1.678 b0.238

15. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 15 Example-Trend Analysis Y 9 =1.678+0.238(9) = 3.83 in 2012 Y 10 =1.678+0.238(10) = 4.06 in 2013 Y 11 =1.678+0.238(11) = 4.30 in 2014 Y 12 =1.678+0.238(12) = 4.53 in 2015 Note: Petrol sales are expected to increase by 0.238 mn gallons per year.Note: Petrol sales are expected to increase by 0.238 mn gallons per year.

16. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 16 Example-Trend Analysis 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.

17. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 17 Example-Trend Analysis r=0.42 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.

18. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 18 Section C/type 2-Vogel and NWC Use the relevant information in the following Table: Determine the dispatch program between the factories and stores. Calculate individual cost Calculate total minimum cost

19. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 19 Given a transportation problem wıth the following costs, supply, and demand, find the optimal solution: Section C/type 2-Vogel and NWC To (Cost) From 1 2 3 supply A $ 6 7 4 100 B $ 5 3 6 180 C $ 8 5 7 200 Demand 135 175 170

20. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 20 Section C/type 2-Vogel and NWC To (Cost) From 1 2 3 supply A $ 6 7 4 100 (2) B $ 5 3/175 6 180 (2) C $ 8 5 7 200 (2) Demand 135 175 170 480\480 (1) (2) (2) B → 2 =175*3 =525 To (Cost) From 1 3 supply A $ 6 4/100 100 (2) B $ 5 6 5 (1) C $ 8 7 200 (1) Demand 135 170 (1) (2) A → 3 =100*4 =400

21. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 21 Section C/type 2-Vogel and NWC To (Cost) From 1 3 supply B 5/5 6 5 (1) C 130/ 8 7/70 200 (1) Demand 130 70 (3) (1) B → 1 =5*5 =25 C → 1 =130*8 =1040 C → 3 =70*7 =490 Total= 2,480

22. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 22 Section C/type 2-Vogel and NWC To (Cost) From 1 2 3 supply A $ 6*100 7 4 100 B $ 5 *35 3*145 6 180 C $ 8 5 *30 7*170 200 Demand 135 175 170 A → 1 =6*100=600 B → 1 =5*35 =175 B → 2 =3*145 =435 C → 2 =5*30 =150 C → 3 =7*170 =1190 Total= 2,550

23. MGMT 405, Production Man., 2012/13 © 2012-13- Assoc Prof. Sami Fethi, EMU, Revision Revision 23 Thanks