PPT-Weighted moving average charts for detecting small shifts in process mean or trends
Author : calandra-battersby | Published Date : 2018-09-17
The wonders of JMP 1 Shifts in the Process Mean and process knowledge The Xbar chart is designed to detect changes in the Process Mean In a mature Process there
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Weighted moving average charts for detecting small shifts in process mean or trends: Transcript
The wonders of JMP 1 Shifts in the Process Mean and process knowledge The Xbar chart is designed to detect changes in the Process Mean In a mature Process there may be a body of Process knowledge which suggests which types of changes in the Process Mean are likely to occur this can be important in finding ways to detect relatively small changes in the mean which the four rules are unlikely to detect. By Keith M Bower Some of the most widelyused form of control charts are X R charts and Individuals charts These are frequently referred to as Shewhart charts after the control charting pioneer Walter Shewhart who originated such techniques These cha 1 The Cumulative Sum Control Chart The chart is a good method for monitoring a process mean when the magnitude of the shift in the mean to be detected is relatively large If the actual process shift is relatively small eg in the range of to 1 the cha are constants with 0 is Gaussian white noise wn0 Note that is uncorrelated with 1 brPage 2br In operator form where the moving average operator is 1 Compare with the autoregressive model The moving average process is stationary for any val Problems (short) 1-2. 1. . Given the following data, compute 3-period moving average forecast for period 6?. Period 1 2 3 4 5 . Demand 73 68 65 72 67. (65+72+67)/3 = 68. 2. . Monthly sales for the past five months were as follows: April (15), May (20), June (18), July (22), August (20). Determine a September forecast, using a 4-period moving average.. Dr. . Ron Lembke. All-Time Average. To forecast next period, take the average of all previous periods. Advantages: Simple to use. Disadvantages: Ends up with a lot of data. Gives equal importance to very old data. We will review the following techniques:. Simple extrapolation (the “naïve” model).. Moving average model. Weighted moving average model. The Naïve Model. If your time series exhibits little variation. 1. 2. - Forecasting techniques based on exponential smoothing. General assumption for the above models: times series data are represented as the sum of two distinct components (. deterministc. & random). of point-normal pairs in 2D and 3D. with application to subdivision schemes.. Evgeny. . Lipovetsky. School of Computer Sciences, Tel-Aviv University. This work is part of my research towards Ph.D. under the supervision of . Terry R. Head. President – International Association of Movers. Who / What is . IAM. ?. The largest . international . trade association & advocacy group for household goods forwarders, movers, removal companies, logistics & service providers. Similarities Between Job-Order and Process Costing. Both systems assign material, labor and overhead costs to products and they provide a mechanism for computing unit product costs.. Both systems use the same manufacturing accounts, including Manufacturing Overhead, Raw Materials, Work in Process, and Finished Goods.. Ship Smart Inc. is a small moving company near me that offers a variety of services to accommodate your specific requirements. Visit: https://www.shipsmart.com/small-move Ship Smart Inc. is a first-class small movers near me that offers hassle-free and affordable small moving services. Visit: https://www.shipsmart.com/small-move Ship Smart Inc. offers Small long distance moves, safely, securely, and affordably. Willing and able to offer you the services you need at a price that fits and works best with your budget. Visit: https://www.shipsmart.com/small-move Dr.. Raghu . Nandan. . Sengupta. Professor. Department of Industrial and Management Engineering. All figures are taken from(unless otherwise mentioned): . Introduction to Statistical process Control .
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