Artificial intelligent and computer simulation are the technological powerful tools for solving complex problems in the manufacturing industries. Additive Manufacturing is one of the powerful manufacturing techniques that provide design flexibilities to the products. The products with complex shapes are directly manufactured without the need of any machining and tooling using Additive Manufacturing. However, the main drawback of the components produced using the Additive Manufacturing processes is the quality of the surfaces. This study aims to minimize the defects caused during Additive Manufacturing with the aid of Artificial Intelligence. The developed AI system has three layers, each layer is trying to eliminate or minimize the production errors. The first layer of the AI system optimizes the digitization of the 3D CAD model of the product and hence reduces the stair case errors. The second layer of the AI system optimizes the 3D printing machine parameters in order to eliminate the warping effect. The third layer of AI system helps to choose the surface finishing technique suitable for the printed component based on the Degree of Complexity of the product and the material. The efficiency of the developed AI system was examined on the functional parts such as gears.
High-technology applications which are using high precision optic components in high and medium quantities
have increased during recent years. One possibility to mass-produce e.g. such lenses is the precision glass molding
(PGM) process. Especially for aspheric and free-form elements the PGM process has certain advantages. Premise
is to manufacture accurate press molds, which have to feature smaller figure errors as the required lenses and
may be made of materials, which are difficult to machine, like silicon nitride ceramics. These work pieces
have to be machined in economical and steady process chains. However, due to the complex shapes and the
corresponding accuracy an error dependent polishing is required. The Magnetorheological Finishing (MRF) as a
high precision computer controlled polishing (CCP) technique is used and will further be presented in this work.
To achieve the postulated demands a previous study of the material removal at selected machining parameters
is needed. Changing machining parameters modify the removal, which is presented through values like the peak
and volume removal rate. The value changes during the controlled variation of process parameters are described
and discussed. Magnetorheological Finishing (MRF) provides one of the best methods to finish PGM molds that
are relatively inaccurate to high precision in an economical, steady and efficient way. This work indicates the
MRF removal selection and removal interference for the correction and finishing of precise silicon nitride molds
for the precision glass molding.
KEYWORDS: Control systems, Process control, Surface finishing, Polishing, Optics manufacturing, Databases, Power supplies, Lens grinding equipment, Surface roughness, Software development
The main objective of this article is to introduce a novel power device for electrical-assisted micro-grinding, which could
reduce the ambiguities reported and experienced during grinding. For example, the device's software is equipped with a
knowledge database that automatically sets suitable electrical parameters for the instructed fine grinding parameters. The
parameters are controlled throughout the process in order to achieve the stringent specifications required for further
advanced polishing processes or establishing mirror surface finish on optical components.
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