Precision glass molding: Toward an optimal fabrication of optical lenses

Liangchi ZHANG, Weidong LIU

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Front. Mech. Eng. ›› 2017, Vol. 12 ›› Issue (1) : 3-17. DOI: 10.1007/s11465-017-0408-3
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Precision glass molding: Toward an optimal fabrication of optical lenses

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Abstract

It is costly and time consuming to use machining processes, such as grinding, polishing and lapping, to produce optical glass lenses with complex features. Precision glass molding (PGM) has thus been developed to realize an efficient manufacture of such optical components in a single step. However, PGM faces various technical challenges. For example, a PGM process must be carried out within the super-cooled region of optical glass above its glass transition temperature, in which the material has an unstable non-equilibrium structure. Within a narrow window of allowable temperature variation, the glass viscosity can change from 105 to 1012 Pa·s due to the kinetic fragility of the super-cooled liquid. This makes a PGM process sensitive to its molding temperature. In addition, because of the structural relaxation in this temperature window, the atomic structure that governs the material properties is strongly dependent on time and thermal history. Such complexity often leads to residual stresses and shape distortion in a lens molded, causing unexpected changes in density and refractive index. This review will discuss some of the central issues in PGM processes and provide a method based on a manufacturing chain consideration from mold material selection, property and deformation characterization of optical glass to process optimization. The realization of such optimization is a necessary step for the Industry 4.0 of PGM.

Keywords

precision glass molding / optical lens / constitutive modeling / optimization / manufacturing chain / Industry 4.0

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Liangchi ZHANG, Weidong LIU. Precision glass molding: Toward an optimal fabrication of optical lenses. Front. Mech. Eng., 2017, 12(1): 3‒17 https://doi.org/10.1007/s11465-017-0408-3

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Acknowledgments

The work presented in this paper was financially supported by the Australian Research Council. This research was undertaken with the assistance of resources provided at the NCI National Facility systems at the Australian National University and Intersect Australia Ltd. through the National Computational Merit Allocation Scheme supported by the Australian Government.

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