EBK PRODUCTION AND OPERATIONS ANALYSIS
EBK PRODUCTION AND OPERATIONS ANALYSIS
7th Edition
ISBN: 9781478628385
Author: Olsen
Publisher: WAVELAND PRESS (ECONTENT)
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Chapter 2.7, Problem 18P
Summary Introduction

To determine: The two step ahead prediction for July till December 2013 using a four month moving average.

Introduction: Forecasting is the main function of predicting the future using the information available for decision making. It is a mechanism for planning decisions based on the predicted information.

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The following table shows the actual demand observed over the last 11​ years:                                                                                                                                             Year 1 2 3 4 5 6 7 8 9 10 11 Demand 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with   α ​=   0.30 and a forecast for year 1 of   6.0​, provide the forecast from periods 2 through 12 ​(round your responses to one decimal​ place).                                                       Part 3 Provide the forecast from periods 2 through 12 using the naive approach ​(enter your responses as whole​ numbers).
Month Demand Forecast Error 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Abs Error Problem 6: The demand manager of Maverick Jeans is responsible for ensuring sufficient warehouse space for the finished jeans that come from the production plants. It has occasionally been necessary to rent public warehouse space, something that Maverick would like to avoid. In order to estimate the space requirements the demand manager is evaluating moving-average forecasts. The demand (in 1,000 case units) for the last fiscal year is shown below. Bias MAD (mean error) Month 1 2 3 4 5 6 7 8 9 10 11 12 Demand 20 18 21 25 24 27 22 30 23 20 29 22 Use a three-month moving average to estimate the month-in- advance forecast of demand for months 4-12. Calculate the Bias and MAD. (Note: Adjust all cell values to two decimal points.)
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:     Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19   2 March 18   3 April 15   4 May 20   5 June 18   6 July 22   7 August 20   8 September    ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19 A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
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