Based on the developed framework, a new TA Method using Artificial Neural Network (ANN) is developed and trained which can predict the value of Assembly Tolerance for the known Component Tolerances. What Is a Tolerance Stack Up (1) HLM method This method assumes that an output is the sum of individual contributors. To get the nominal dimension of our tolerance stack we simply add the means. When we add or subtract normally distributed variables, we can add or subtract the means. Based on the analysis and based on the identified merits and demerits of these methods, a framework for a new TA Method is developed. If we set the part tolerance to +/- 3 sigma, we would expect 99.7 of the parts to be good for a given dimension. Out of these methods, four major methods viz., Simulation Based Stack-Up Analysis, Second Order Tolerance Analysis, OpTol - Spatial Tolerance Analysis and Tolerance Analysis of 2D and 3D Assemblies are chosen for further study and comparative analysis. In Excel, the analysis for a three-component tolerance error (Ern) stack-up contribution would look something like this: SQRT (SUMSQ (ErA + ErB + ErB)). The literatures relevant to 15 methods of TA which are being used to determine Assembly Tolerance from Component Tolerances are collected and critically analyzed to gain an insight into the existing methods. The perception of Tolerance Analysis (TA)/Tolerance Stackup is imperative for every Design and Manufacturing Engineer because Tolerance is the criterion that should be compromised between the cost and function of a product.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |