Rohit Kumar 
A computer-aided approach for gating system design for multi-cavity dies [PDF ebook] 

Ondersteuning

Master’s Thesis from the year 2017 in the subject Engineering – Mechanical Engineering, grade: 8, , language: English, abstract: This work presents a system that would help in automatic design of multi-gates for multi-cavities dies. The system is able to automate: (i) the determination of the placement of gate, and (ii) determination of the shape of gate for die-casting parts having simple shapes. The system has to be implemented in GUI of MATLAB 7.10 using the best industry practices and recommendations from NADCA for gating-system design. The proposed system is able to generate parameters of multi-cavity gating-system for parts requiring multi-gates from the part model data. The other information required for working of the system includes material properties, die-casting process parameters and die-casting casting machine parameters which comes under the data initialization process. The parameters of the gating-system which are determined by the system are used for design of gating-system for the multi-cavity dies. This is done by updating the parameters of pre-modeled gating-system features stored as feature library. Chapter 3 , 4 and 5 present the various modules of the system along with its implementation on case-study parts. The results from the case-studies are quite encouraging and are in-line with the best industry practices.
The present work describes a novel methodology for computer-aided automatic placement of the gating system for a die-casting part. it uses the parting line information to identify the probable positions for the placement of the gating system. This aspect of die-design has not received due attention of the researchers in the past. Moreover, the automated gating-system design for die-casting parts that require multiple agates in a multi-cavity die has not been attempted. Both these features provide the originality to the present work.

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Taal Engels ● Formaat PDF ● ISBN 9783668542723 ● Bestandsgrootte 2.7 MB ● Uitgeverij GRIN Publishing ● Stad München ● Land DE ● Gepubliceerd 2017 ● Editie 1 ● Downloadbare 24 maanden ● Valuta EUR ● ID 5247316 ● Kopieerbeveiliging zonder

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