بررسي فناوري نمونه سازي و توليد سريع به روش FDM و ارزيابي متغيرها جهت شناسايي ميزان تاثير بر نمونه نهايي

چكيده انگليسي :

An Investigation into FDM Rapid Prototyping Process and Evaluation of Process Parameters on Workpiece Specification Davood Khorram d khorram@me iut ac ir Date of Submission 2013 01 22 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Alireza Fadaei mcjaft@cc iut ac ir Abstract In the past few years several new rapid prototyping methods have emerged These rapid prototyping systems use various methods to create physical parts from existing CAD files within a short amount of time Since less time is required to produce a prototype the final product is able to reach the market sooner The physical prototypes can then be used to evaluate the integrity of the design Whenever possible the prototype should be as similar as possible to the desired finished part Fused deposition modeling which is often referred to by its initials FDM is a type of rapid prototyping technology commonly used within engineering design The technology was developed by S Scott Crump in the late 1980s and was commercialized in 1990 The FDM technology is marketed exclusively by Stratasys Inc FDM is one of rapid prototyping process that uses thermoplastic materials such as ABS acrylonitrile butadiene styrene in the semi molten state to produce prototypes FDM is an additive process and the prototypes are made by layer by layer addition of the semi molten plastic material onto a platform from bottom to top The quality of FDM produced parts is significantly affected by various parameters used in the process This dissertation work aims to study the effect of three process parameters such as layer thickness sample orientation and raster angle on property of FDM processed parts Process parameters such as layer thickness raster angle and part orientation in addition to their interactions are studied in the present dissertation that influences the Impact resistance Fatigue resistance and dimensional accuracy of the part produced by the process of FDM Due to shrinkage of the filaments the dimensions of the CAD model does not match with the FDM processed part Influence of each parameter on responses such as impact resistance fatigue resistance and percentage change in length width and thickness of the build part are essentially studied The effect of process parameters on responses are studied via Response surface methodology RSM RSM is used to calculate the regression coefficients and the function is made with the significant factors In order to reduce experimental runs due to time saving and material cost response surface methodology based on box behnken design is adopted Specimens are prepared for test as per ISO standards and modeled in CATIA V5 software Specimens per experimental run are fabricated using Rapman 3 2 FDM machine Empirical relations among responses and process parameters are determined and their validity is proved using analysis of variance ANOVA and the normal probability plot of residuals MINITAB16 software is used for statistical analysis As FDM process involves large number of conflicting factors and complex phenomena for part building it is difficult to predict the output characteristics accurately by conventional method So an artificial neural network with back propagation algorithm has been adapted to model FDM process Then optimization of process parameters is made by genetic algorithm so as to maximize impact resistance fatigue resistance and minimized percentage change in dimensional of specimen Non dominated sorting genetic algorithm NSGA II is used to optimize three responses together MATLAB2011 software is used for implementation of ANN and GA algorithm Keywords Rapid prototyping FDM Genetic algorithm NSGA II ANOVA ANN PDF created with pdfFactory trial version www pdffactory com

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بررسي فناوري نمونه سازي و توليد سريع به روش FDM و ارزيابي متغيرها جهت شناسايي ميزان تاثير بر نمونه نهايي

سطح پاسخ , شبكه عصبي , الگوريتم ژنتيك , NSGA-II