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Table 3: Machine setup time (Hours) after changeTable 4: Error in prediction values after changeIntervalActualMoving AverageExponentialSmoothing (Note-2)IntervalMovingAverage Error (Hours)ExponentialSmoothing Error (Hours)1 6 - 6 (Note-1)2 3.45 - 63 3.35 4.73 3.964 3.45 3.40 3.885 3.25 3.40 3.966 4.55 3.35 3.87 - 3.90 4.841 - -2 - -2.63 -1.4 -0.64 0.0 -0.45 -0.2 -0.76 1.2 0.8featureNotes: 1. Initial Prediction Value is six hours.2. Smoothing Constant of 0.8 on actual value.Graph 2: Machine setup time trend after change• Error in PredictionPrediction error is the difference betweenthe actual and predicted value. It is notpossible to achieve zero error.• Unpredictable EventsSporadic occurrences are design failuresthat will cause unpleasant things tohappen. It is unpredictable. It occursdue to many unknown factors. It is onlyknown when it occurs.One well known technique toanalyse failure data is Failure Mode andEffects Analysis FMEA. This method isa tool that will build in quality into theproduct or service. It requires a lot ofexperience and knowledge to removethe defect(s) from the product or servicein analysing possible failures and theactions that are required to avoid.Management involvement, I believe, canremove possible failure in the project.Applying the two predictive methodson setup time shows a trend. This trendis shown in Graph 1. Table 1 showsthe actual time taken to setup the lineand prediction values using the aboveformulae. Table 2 shows the error.By recording the time after eachactivity, a trend can be seen in this project.The personnel involved in the activityworked towards a common goal to reducethe setup time. The prediction valuesbased on equation [1] and [2] ascertainthat the setup time is in control. Based onthe predictive equations, the next setuptime will either increase or reduce a little,ensuring a quantitative approach.The equations are only a mathematicalguide to determine the next unknownvalue. Based on the first equation, it iscalculated by the average of two pastvalues. Based on the second equation, thenext value is based on a weighted factor ofan actual value and a predicted value. Thesmoothing constant determines whetherthe next value is closer to the past valueor the past prediction.By calculating the average of theprediction errors (sum of errors dividedby 20), a prediction limit is found. In thiscase, it is +/-0.3 hours for the movingaverage method and +/-0.2 for theexponential smoothing method.Diagram 1 shows that the predictionvalue based on the moving averagemethod or the exponential smoothingmethod is either more or less than 0.2to 0.3 hours of the predicted value(approximately 10-20 minutes).After recording the time, somechanges were made to the productionline. The following data shows theresult. The time taken to setup the lineis more stable. The setup time is shownin Table 3 and the error is tabulated inTable 4.In conclusion, it is not possible topredict an actual value. Predictionequations only assure methodologicallythat a value is within the limit. It is onlytrue provided that factors in setting upthe machine are the same. A trend linehas to be established. The equationsroughly predict the next value. nJurutera May 200913