derive the learning curve function (Please show your work by using the formulas in Lesson 02). What is the rate of learning (or learning curve percentage)? d. Based on the learning curve obtained from part c‚ estimate the time that would take you to produce the 150th unit? 2. (4 points) Professor Cook teaches Operations Management at an Ontario University. She is scheduled to give her class of 55 students a final exam on the last day of the exam week‚ and she is leaving town the same day. She is concerned
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the text‚ exercise 9.1 provides data for Palmdale Human Services. In this exercise it asks for the 20X5 figures using several forecasting models. The process of find 20X5 will include the use of moving averages‚ weighted moving averages‚ and exponential smoothing. The Palmdale Human Services personal expenses for the past four years are represented in the following data: Fiscal Year | Expense | 20X1 | $5‚250‚000 | 20X2 | $5‚500‚000 | 20X3 | $6‚000‚000 | 20X4 | $6‚750‚000 | For moving averages
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PERENCANAAN & PENGENDALIAN PRODUKSI TIN 4113 Pertemuan 2 • Outline: – – – – – Karakteristik Peramalan Cakupan Peramalan Klasifikasi Peramalan Metode Forecast: Time Series Simple Time Series Models: • Moving Average (Simple & Weighted) • Referensi: – Smith‚ Spencer B.‚ Computer Based Production and Inventory Control‚ Prentice-Hall‚ 1989. – Tersine‚ Richard J.‚ Principles of Inventory and Materials Management‚ Prentice-Hall‚ 1994. – Pujawan‚ Demand Forecasting Lecture Note‚ IE-ITS‚ 2011
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SCM 485 Exam 1 Review Forecast Notes Supply Chain Management Sequence of activities and organizations involved in producing and delivering a good or service SCM Define by Council of Supply Chain Management Professionals (CSCMP) Supply Chain Management encompasses the planning and management of all activity involved in sourcing and procurement‚ conversion‚ and all logistics management activities. Importantly‚ it also includes coordination and collaboration with channel partners‚ which can
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several factors that should be considered when making this analysis. It has been provided that the costs of reconditioning the current equipment will be $50‚000 fixed costs and $1‚000‚000 variable costs. Additionally‚ purchasing new equipment will produce fixed costs of $200‚000 and variable costs of $500‚000 and outsourcing will have no fixed costs with variable costs of $300‚000. These figures can be input into the breakeven cost volume analysis module in POM for Windows and it can be determined
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to write the name‚ student # and section # for each student in the group on the cover page of the assignment 1. Suppose you/your group is the owner of a company that produces e-readers. The present production rate is 1000 e-readers /day and the selling price is $210/unit. It requires 200 workers working 8 hours/day to produce the e-readers and they are paid $20/hour. The material cost is $100/unit and overhead cost is $50‚000/day. a) What is the unitless multi-factor (labor + material + overhead)
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FORECASTING FORECASTING The Role of the Manager Planning Organizing Staffing Leading Controlling Future ? Data Information • Short-range • Medium-range • Long-range Features Common to All Forecasts Forecasting techniques generally assume that same underlying causal system that existed in the past will continue to exist in the future. Forecasts are rarely perfect. Forecasts for groups of items tend to be more accurate than forecasts for individual items. Forecast
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period) MAD ≈ 32.403 Exponential Smoothing or ES (adjusted for trend and seasonality) MAD ≈ 13.258 6 Q2: Forecast for January – April 2012 Month Mean Base Period MR SR ES January 0.61 49 825.27 745.12 720.56 February 0.88 50 1107.05 1082.68 1039.50 March 0.87 51 1105.66 1078.04 1027.69 April 1.05 52 1296.43 1310.32 1240.31 7 Q3: Best Forecast: Exponential smoothing forecast has lowest MAD Disadvantages: the exponential smoothing forecast should be updated
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203.50 3. EXPONENTIAL SMOOTHING: α=0.1 Ft+1 = α Xt + (1 - α ) Ft Let the starting point forecast be Jan sales‚ F1=200. And X1=200 Forecast for Feb‚ F2=200. Actaul Sales‚ X2=135 F3 (forecast for March)= α *X2+(1- α)*F2=0.1*135+0.9*200 In EXCEL: For the cell‚ F3 enter =$E$16*C2+(1-$E$16)*F2 where $E$16 is value of 0.1‚ which is the smoothing constant‚ α. So‚ the forecast for Dec is 205.56 The following shows the plot for Forecast by 3 MA‚ 5MA and Exponential Smoothing‚ 0.1 In last
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RMSE/Mean* MAPE RMSE RMSE/Mean* Winter’s exponential smoothing 6.65% 4.65 7.74% 5.92% 6.73 28.74% Decomposition with exponential smoothing trend 5.45% 3.97 6.61% 4.63% 5.77 24.64% ARIMA(1‚0‚0)(2‚0‚0) 7.23% 5.11 8.51% 8.02% 6.56 28.01% *Mean of NHS for the historical period is 60.08 and for the holdout period is 23.42 The best model should be the one with the smallest error. Among these three time-series models‚ the decomposition with exponential smoothing trend has the smallest MAPE and RMSE
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