TOBB ETÜ 2015-2016 Spring
END 307- Production Systems Planning
Assignment 2
Assignment Date: 26.01.2016, Due Date: 02.02.2016 (1st class hour)
Q1. Demands for a model of a dishwasher are given below;
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Demand
(units)
26
38
42
44
47
49
50
49
52
48
52
55
64
56
57
a. Assume that you are at the end of day 6 , use Double exponential smoothing with
alpha = 0.2 and trend parameter beta = 0.1 and compute the forecasts for Day 7
through Day 13, day by day. (Every day you update the intercept and slope
considering the new data, and forecast for the next day only)
b. Compute the tracking signal values for the forecast errors you found in item a
above and comment about the tracking signal.
c. Assume that you are at the end of day 5, fit a linear regression line and find
forecasts for Day 7 through Day 13 using the linear regression line.
d. Find the correlation and coefficient of determination between time and data, using
the entire data set and comment on accuracy of the linear relation.
Q2. Following table shows the number of ski jackets demanded in a store;
Month
Jan
Year 1
1847
Feb
Mar
Apr
May
Jun
July
Aug
Sep
Oct
Nov
Dec
Jan
Feb
Mar
2669
2467
2432
2464
2378
2217
2445
1894
1922
2431
2274
Year 2
2045
2321
2419
a. Assume that you were at the end of September in the first year. Forecast for the
rest of the months (one month ahead forecasts), month by month, using both simple
exponential smoothing method (alpha=0,15) and moving average with window
length 5. Compare the performance of the two methods based on MAPE (You will
produce 6 forecasts and errors).
b. Plot the errors produced by the simple exponential method and comment about
the errors and the bias issue.
Q3. American Bottle, Inc. specializes in the manufacture of plastic containers. The
data on monthly sales of 10-ounce shampoo bottles for the last four years are
contained in the spreadsheet forecasting-hw-data.xls from the web site. Assume that
you are at the end of August in year 3 and answer the following;
a. In order to construct a triple exponential smoothing model, find the initial
intercept, slope and seasonal factors (for each month).
b. Using the forecasting model, find the forecasts for the rest of the year 3 and year 4.
Plot both the forecast and observed values on the same chart.
c. Assume that you have observed the data for September and October of year 3,
update the parameters of your forecasting model two times, one after each
observation. Use alpha = 0,15, beta = 0,09 and gamma = 0,1.
Note: Make sure that
1. Before you do the home work, multiply all the data points (not the parameters) by
a factor X which you will find as described below. If the resulting data values after
multiplication are fractional, keep them as fractional. Use two decimal points in your
calculations, at least;
X =max [0.05, (last two digits of the first group member’s ID/100 + last two digits of
the second group member’s ID/100)/2 ]
(If you do the homework alone, assume that the last two digits of the second group
member’s ID is equal to 50)
2. You must explain in the submitted assignment document what you have done in
excel files and how you have calculated the results, if you have used excel.
3. You must send the excel file to both teaching assistants via email. Their emails are
in the syllabus.
(emails nkarimi@etu.edu.tr cansuinanc@etu.edu.tr)
4. Excel file name should be st_1st member ID_2nd member ID.xls
Deliverables;
1. Assignment
2. Excel sheets print outs if needed, as an appendix.
3. Excel file emailed to both teaching assistants