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Blended Lean Six Sigma Black Belt Training – ABInBev ©2010 ASQ. All Rights Reserved. Answers to DDC Study “Improve”
© 2010 ASQ. All Rights Reserved. 2 About this Module You are the coach for the Green Belt doing the Brazil DDC project. He is planning to conduct a DoE This is his first DoE so he has asked you for help filling out the DoE planning sheet.
© 2010 ASQ. All Rights Reserved. 3 Where He Is So Far He indicates that he has completed the form as far as he can go without your help. (DoE Plan DDC.doc). He also indicates he has budget approval for 16 runs. What would you recommend and why?
© 2010 ASQ. All Rights Reserved. 4 Determining the Factors From the Pareto we know the four leading causes to test those we decided to use the following factors 1.Number of orders 2.Route in minutes 3.Truck loading time 4.Release time
© 2010 ASQ. All Rights Reserved. 5 What Types of Experiment Could We Do? Stat>DoE>Create Factorial Design> Display Available Designs Viable designs
© 2010 ASQ. All Rights Reserved. 6 The Viable Options A full factorial design without replication –Advantage No alias or confounding –Disadvantage No measure of error (saturated model) if all main effects and interactions are significant A half faction factorial design with two replicates –Advantage The replication provides a measure of error –Disadvantage Aliasing may be difficult for an inexperienced Green Belt to understand and fully explain
© 2010 ASQ. All Rights Reserved. 7 Design Choice Consensus was a full factorial design with the factor levels set at. 1.Number of orders1732 2.Route in minutes 5673 3.Truck loading time5.57.5 4.Release time 3 9 Complete the DoE Matrix
© 2010 ASQ. All Rights Reserved. 8 Create the DoE Matrix
© 2010 ASQ. All Rights Reserved. 9 Analyze the Data The experiment was performed and the data saved in DDC DoE.mtw Analyze the data and prepare to present the results
© 2010 ASQ. All Rights Reserved. 10 Analyze the DoE Stat>DoE>Factorial Analyze Factorial Design
© 2010 ASQ. All Rights Reserved. 11 Analyze the DoE For the initial model include all main effects and interactions
© 2010 ASQ. All Rights Reserved. 12 First Model Reduce the model
© 2010 ASQ. All Rights Reserved. 13 First Reduction
© 2010 ASQ. All Rights Reserved. 14 Second Model Reduce the model again
© 2010 ASQ. All Rights Reserved. 15 Final Model
© 2010 ASQ. All Rights Reserved. 16 Final Model
© 2010 ASQ. All Rights Reserved. 17 Check the Residuals The residuals are normally distributed with a mean of zero and constant variance. No reason to reject the model.
© 2010 ASQ. All Rights Reserved. 18 Optimize the Performance Stat>DoE>Analyze Factorial Design>Response Optimizer
© 2010 ASQ. All Rights Reserved. 19 Setup the Optimizer
© 2010 ASQ. All Rights Reserved. 20 Optimizer Output Non delivered orders are minimized by using the lower route time and lower release time. The model shows we should be able to achieve an average of ~2.5 non delivered orders.
© 2010 ASQ. All Rights Reserved. 21 How Much of the Variation is Explained? Stat>ANOVA>General Linear Model
© 2010 ASQ. All Rights Reserved. 22 Session Window Source DF Seq SS Adj SS Adj MS F P Route in Min 1 537.08 537.08 537.08 99.43 0.000 Release Time in Min 1 312.41 312.41 312.41 57.83 0.000 Error 13 70.22 70.22 5.40 Total 15 919.71 Remove the spaces that are interior to the column and source names.
© 2010 ASQ. All Rights Reserved. 23 Prepare to Graph Source DF SeqSS AdjSS AdjMS F P RouteinMin 1 537.08 537.08 537.08 99.43 0.000 ReleaseTimeiMin 1 312.41 312.41 312.41 57.83 0.000 Error 13 70.22 70.22 5.40 Total 15 919.71 Your session window should like like this. Copy this data excluding the total row to the clipboard then paste starting in the title row of the worksheet.
© 2010 ASQ. All Rights Reserved. 24 Create the Graph Graph>Pie Chart
© 2010 ASQ. All Rights Reserved. 25 Specify the Labels
© 2010 ASQ. All Rights Reserved. 26 Pie Chart Over 92% for the change in Non delivered orders is explained by release time and route time.
© 2010 ASQ. All Rights Reserved. 27 Conclusions The DoE has identified factors that must be controlled to minimize the non-delivered orders which in turn should increase the sales rate.
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