Paper
15 February 1989 Automatic Inspection In Industry Today
Richard A. Brook
Author Affiliations +
Proceedings Volume 1010, Industrial Inspection; (1989) https://doi.org/10.1117/12.949190
Event: 1988 International Congress on Optical Science and Engineering, 1988, Hamburg, Germany
Abstract
With increasing competition in the manufacturing industries product quality is becoming even more important. The shortcomings of human inspectors in many applications are well know, however, the eye/brain combination is very powerful and difficult to replace. At best, any system only simulates a small subset of the human's operations. The economic justification for installing automatic inspection is often difficult without previous applications experience. It therefore calls for confidence and long-term vision by those making the decisions. Over the last ten years the use of such systems has increased as the technology involved has matured and the risks have diminished. There is now a complete spectrum of industrial applications from simple, low-cost systems using standard sensors and computer hardware to the higher cost, custom-designed systems using novel sensors and processing hardware. The underlying growth in enabling technology has been in many areas; sensors and sensing techniques, signal processing and data processing have all moved forward rapidly. This paper will examine the currrent state of automatic inspection and look to the future. The use of expert systems is an obvious candidate. Parallel processing, giving massive increases in the speed of data reduction, is also likely to play a major role in future systems.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard A. Brook "Automatic Inspection In Industry Today", Proc. SPIE 1010, Industrial Inspection, (15 February 1989); https://doi.org/10.1117/12.949190
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Cited by 5 scholarly publications.
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KEYWORDS
Inspection

Manufacturing

Sensors

Computer aided design

Computing systems

Data processing

Process control

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