Intelligent Direct Metallic Rapid Tooling with Embedded MEMS based Microsensors

碩士 === 國立中正大學 === 電機工程所 === 94 === Rapid Prototyping is already applied successfully to the industrial circle, it achieve the purpose of fast designing and producing the products. Since the quantity demand for complicated mold of high level products is increasing, Rapid Tooling (RT) technology has a...

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Bibliographic Details
Main Authors: Yen-lin Pan, 潘彥霖
Other Authors: R. C. Luo
Format: Others
Language:en_US
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/33335941143712352101
Description
Summary:碩士 === 國立中正大學 === 電機工程所 === 94 === Rapid Prototyping is already applied successfully to the industrial circle, it achieve the purpose of fast designing and producing the products. Since the quantity demand for complicated mold of high level products is increasing, Rapid Tooling (RT) technology has a very fast development. Rapid Tooling can be used to produce temporary mold, even permanent mold in mass production and makes more benefit from design stage to mass production. The objectives of this thesis are to integrate the Laser Powered Direct Metallic RT System and the MEMS-based micro temperature sensors, and to develop the intelligent direct metallic rapid tooling mold with embedded MEMS-based microsensors. The Laser Powered Direct Metallic RT System has been successfully developed. The metallic RT mold insert was fabricated, and the plastic injection molded parts (PMMA) also was produced successfully; The MEMS-based micro temperature sensors also successfully fabricated. It is proofed to have temperature effect, and obtain accurate temperature measurement after calibration. The micro sensor embedded approaches are proposed in order to rapidly measure global or local temperature and pressure distribution inside rapid tooling’s core and cavity during the injection, hold and cooling process; The MEMS-based microsensors can improve the problems of existing temperature sensors embed in the mold. In the case of measuring temperature distribution, the results using Moldflow software and Back-Propagation Network are compared with. The differentiations of simulate data and factual data are proofed the on-line monitor accomplishment using MEMS-based temperature microsensors embed in the mold. It will improve industrial competition in injection molding field.