Production Planning and Control

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Project Purpose: To demonstrate the application of the various items learned in the course (adding chapters 4, supplement chapter 7, and chapter 11) for Project 2. To demonstrate that the student understands the material.

NOTE: For partnerships, problem 1 A, B, C and D will be evaluated individually. Worth 40 points.

1. Forecasts For 2013 (45 points – each letter A, B, C and D below is worth 10 points, D is worth 10 points and E is worth 5 points) For items A, B, and C below – do the forecast for all the months of 2013 and total for the year 2013. START A NEW PAGE for each A, B, C, D and E below. Partners keep all problem A together, and then problem B, etc.
A. Regression Analysis Forecast - For all KC10 finished products with increasing sales use the “Regression Analysis” to forecast. Note: do a “Standard Error of the Estimate,” a “Coefficient of Correlation” and a “Coefficient of Determination” and explain what each of these measures mean as applicable to YOUR forecast and YOUR company (Good or bad, etc.). NOT book answers. Use the complete set of sales data from year 2012 (only one year data) in your regression analysis.
B. FIT Forecast Method - For all the finished products KC10 with increasing sales (problem 2-A above), use the FIT Method Chapter 4. You must establish the first (T) for Jan 2012 and the initial forecast (f) for Jan 2012. Important: Use this data to arrive at a forecast for the month of Jan 2013 ONLY. Use two different values of alpha (keep beta constant at .7) and compare the results of your forecast using the actual demand data from 2012 compared to your calculated forecast amounts for year 2012. Calculate the (MAD) to pick the alpha that you feel gives the best forecast and justify your answer. Use the chosen alpha from above to calculate your final and best estimate of the forecast for January 2013. Note: the same

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