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Design of experiments using Moldflow Analysis.

Design of experiments using Moldflow Analysis.

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- 1. Design of ED i f Experiments i t using Moldflow. g
- 2. What is DOE ?DOE – D i Of E Design Experiment i tDesign of Experiment is a systematic approach for evaluatingthe relationship between the input factors & quality criteriausing statistical methods. Why to use DOE?A DOE analysis will provide you with information about thesensitivity of the input parameters about a given partdesign.
- 3. Type of DOE Analyzing Methods: -T f A l i M th d• Taguchi Screening Analysis•F t i l Factorial Full Factorial Analysis• Taguchi & Factorial Runs Taguchi analysis to determine the primaryfactors which will be used for the factorial Analysis
- 4. Input Parameters for DOE Analysis: - Input Parameters which can be used for Running DOE Analysis in I tP t hi h b df R i A l i i Moldflow: -• Mold Temperature• Melt Temperature• Injection Time• Injection Profile Multiplier• Thickness Multiplier• Packing Time (only for DOE Flow)• Packing Profile Multiplier (only for DOE Flow)
- 5. Possible reasons to run a DOE Analysis : -P ibl t A l i To optimize the wall thickness of the part. To indentify the process parameters to keep the shear rate within the recommended limit while maintaining the shrinkage variation in the p component. To determine the molding conditions to keep clamp force within the maximum machine limit. To determine interrelation between Volumetric Shrinkage & packing time. To determine how to solve problem of warpage caused due to differential Shrinkage Shrinkage. To optimize cycle time considering part weight.
- 6. Taguchi Analysis : -Taguchi analysis will filter out the main factors from large number offactors which mostly affects the quality of the product. This is calledas screening analysis. With this method, the parameters are rankedas per the effect on the final part quality.When the screening analysis is complete it shows the weighting foreach of the quality criteria : -• Flow Front Temperature• Shear Stress• Injection Pressure• Overall Quality
- 7. Procedure to run the Taguchi Analysis: -P d t th T hi A l i Steps to Run Taguchi Analysis: - Select the Analysis sequence as DOE (Fill) Then t th Th set the process parameter to mid-range.(Page1) t t id (P 1)
- 8. Procedure to run the Taguchi Analysis: -P d t th T hi A l i Setting for page 2 Select the Experiment type to Taguchi & then Set the range to analyze for the respective parameter as shown in the figure figure. Then Run the analysis.
- 9. Screening Analysis Results: -S i A l i R ltOnce the screening analysis is completed,MPI shows the DOE: weighting as shownin the figurefor each of the quality criteria (factor).From these results we need to list out theVitalVi l parameter which affect the quality of hi h ff h li fthe product. These vital parameters will beconsidered as input while runningFactorial Analysis.
- 10. Factorial Analysis : - The Vital process p p parameters which are derived from the results of screening analysis are used as the input, while running the factorial analysis. In our case the vital parameters which are affecting part quality are : - Melt Temperature. Global thickness multiplier. Mold wall temperature.
- 11. Procedure to run the Factorial Analysis: -P d t th F t i l A l iSteps to Run Factorial Analysis: - Select the Analysis sequence as DOE (Fill) Then set the DOE Experiment type to Factorial Set the range, to analyze for the respective parameter as shown in the figure. 11
- 12. Procedure to run the Factorial Analysis: -P d t th F t i l A l iRank the quality criteria based on theresults from Taguchi analysis as shown in the figure.Then run the analysis.After running the analysis moldflow will runVarious iteration considering various combinations,To get the optimized parameters as shown in the adjoining figure figure.
- 13. Factorial A l i RF t i l Analysis Results: - lt Considering the three most effective parameters which are figured out from the screening analysis, it launches a set of experiments to determine the input factor for the quadratic function of the response surface methodology.
- 14. Factorial A l i RF t i l Analysis Results: - lt Plot shows the XY Plots for flow front temperature & Injection pressure by which locking one of the factor y can see how it affects the q g you quality. y
- 15. Factorial A l i RF t i l Analysis Results: - ltWhile reviewing the factorial results plots we need to seeat the response curves. Shallow or flat response curve The larger the variation the steeper will be the slope & more sensitive Steep response curve will be the factor factor.
- 16. Taguchi & then Factorial Analysis : -In “taguchi then factorial” analysis, moldflow runs the g y ,taguchi analysis & then identifies the vital factors & use it forrunning factorial analysis.Response Su ace ( et od) object e The e pe e is espo se Surface (method) objective: e experiment sdesigned to allow us to estimate interaction and evenquadratic effects, and therefore give us an idea of the (local) shape of the response surface we are investigating.For this reason they are termed response surface method reason,(RSM) designs.RSM designs are used to: Find improved or optimal p p p process settings g Troubleshoot process problems and weak points Make a product or process more robust against external and non- controllable influences. "Robust" means relatively insensitiveto these influences. influences
- 17. Procedure to run the Taguchi then Factorial Analysis: - Steps to Run Taguchi then Factorial Analysis: - Select the Analysis sequence as DOE (Fill) Then set the DOE Experiment type to Taguchi then Factorial & set the number of factors . Set the delta value for the parameters & also rank quality criteria based on results f b d lt from ttaguchi analysis & th run th analysis. hi l i then the l i
- 18. “Taguchi then Factorial” Analysis Results: -“T hi th F t i l” A l i R ltScreen output for the Analysis: - Moldflow will run various iterations considering the quality criteria specified. If with some processing condition there are chances to get short molding, then it will adjust the parameter & re-run the iteration.
- 19. “Taguchi then Factorial” Analysis Results: -“T hi th F t i l” A l i R lt
- 20. Conclusion: - DOE is a good tool to understand the inter-relation between the parameters & the quality of the component. DOE will tell you which factor needs to be controlled to get good quality product. It will help you to reduce the process variations. Process Variation observed Process Variation reduced
- 21. POLYSMART TECHNOLOGIES PVT LTD LTD.94,Bombay Talkies Compound, Shreenath Chambers, 3rd Floor,Malad (West) B-66 & 67, Gyaneshwar Paduka Chowk,Mumbai:- 400064 Ferguson College Road,India. Pune: - 411005.Tel:- +91-22-28824448, e 9 88 8, Tel: - +91-020-25520311 / 312 +91 020 25520311 312. +91-22-28823241,91-22-28813508.Fax:- +91-22-28820629Website:-W b it www.polysmart.com l t

Full NameComment goes here.ben_guhmanthanxArun Prasadat Cipet 2 years ago