A haptic digital tool to assist the design, planning and manufacture of micro- and nanostructures

Sun, J and Liu, Y and Ritchie, JM and Luo, X (2015) A haptic digital tool to assist the design, planning and manufacture of micro- and nanostructures. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 229 (4). pp. 290-298. ISSN 0954-4089 (https://doi.org/10.1177/0954408914530296)

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Abstract

This work addresses the engineering demands for precise interactive process planning for the manufacture of high precision in the manufacturing of 3D micro- and nanoproducts. It outlines the development of a digital tool based on a haptics-based human–machine interface. This interface is underpinned using an empirical model derived from a series of experimental results obtained from a focused ion beam machine through a series of experiments, which produced the surface topographies of a number of micro- and nanograting arrays; these were systemically analysed to provide an underpinning empirical database, which could be accessed via the haptic process planning system. On accessing these data, highly accurate geometrical models are then input into a haptics human machine interface to emulate the focused ion beam machining process as defined by the customised fabrication parameters. The haptic planning system predicts and simulates the shape and form of the finished product profiles as the haptic device is passed across a virtual substrate. Once the simulation is complete and the outputs verified by the user, the system then automatically outputs a stream file to drive the focused ion beam process to produce the surface topographies required. The simulation results reveal that compared with trial and error method, the haptics-based simulation method is a reliable way to plan and optimise the fabrication parameters in design and manufacture of micro- and nanogratings by focused ion beam machining cost-effectively. This could potentially provide substantial lead time and cost reductions associated with these currently inherently expensive unit cost products as well as demonstrate a novel tool not only for the planning of nanomachining cutting sequences but also for the interactive design of such products. This work also highlights the benefits of an empirical model as a means of underpinning and supporting real-time haptics interaction, something not possible using more numerical-based techniques.