Lens production enhancement by adoption of artificial influence functions and a knowledge-based system in a magnetorheological finishing process

Elmar Pitschke; Peter Sperber; Rolf Rascher; Richard Stamp; Melvyn Smith; Lyndon Smith; Markus Schinhaerl

doi:10.1117/12.761356

14 September 2007 Lens production enhancement by adoption of artificial influence functions and a knowledge-based system in a magnetorheological finishing process

Elmar Pitschke, Peter Sperber, Rolf Rascher, Richard Stamp, Melvyn Smith, Lyndon Smith, Markus Schinhaerl

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Proceedings Volume 6671, Optical Manufacturing and Testing VII; 66711J (2007) https://doi.org/10.1117/12.761356
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

High quality optical lenses are usually finished by magnetorheological finishing (MRF). In this process an abrasive fluid, with the ability to stiffen in a magnetic field, is used as the polishing tool in a computer-controlled machine tool. Although the machine is automated it is necessary for a skilled operator to set the machine and make judgments with regard to its operation. An investigation has been under way to examine the detailed operation of the MRF process, and the information that is necessary to establish best practice. This has resulted in the incorporation of a knowledge based system (KBS) into the machine control regime, and a methodology for the creation of artificial polishing tool characteristics, the machine influence function. The incorporation of the these elements has been instrumental in the operation of an enhanced MRF machine. This has been subject to extensive test procedures, and it has been demonstrated that the production process may be enhanced significantly and consistently. Batch production time may be significantly reduced, a figure in excess of a 50% reduction was met consistently during prolonged operation. Furthermore the incorporation of the KBS is instrumental in increasing the automation of the MRF process, reducing the levels of manual input necessary to manage machine operation.

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Elmar Pitschke, Peter Sperber, Rolf Rascher, Richard Stamp, Melvyn Smith, Lyndon Smith, and Markus Schinhaerl "Lens production enhancement by adoption of artificial influence functions and a knowledge-based system in a magnetorheological finishing process", Proc. SPIE 6671, Optical Manufacturing and Testing VII, 66711J (14 September 2007); https://doi.org/10.1117/12.761356

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KEYWORDS

Polishing

Neural networks

Magnetorheological finishing

Surface finishing

Manufacturing

Optics manufacturing

Polishing equipment

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