ICOS Vision Systems
ICOS, a division of KLA Tencor, is a world leader in vision technology, offering vision and inspection solutions for the semiconductor and the electronics assembly markets.
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CI-3050 - Component Inspection The CI-3050 is the smallest automatic Component Inspector available. Due to its small footprint and easy operation the CI-3050 is renowned for its userfriendliness
WI-2xx0 - Wafer Inspectors The WI-2200 and -2300 Wafer Inspectors perform 100% automated optical inspection and metrology of microelectronic devices on a variety of wafer substrates, surface inspection, and 2D bump inspection. Key market segments for this automated optical inspection system include semiconductor IC, optoelectronics, advanced packaging, and MEMS.
CI-T120-T130 - Component Inspection The CI-T120 and -T130 Component Inspectors are configured for high-volume inspection of Gull Wing, BGA, CSP and QFN devices, as well as memory cards. With a default 10-head, pick-and-place handling system and a quadruple pick-and-place head for taping, the CI series offers extraordinary throughput. In addition, changeover time has been reduced to a minimum. The CI series provides high performance at a minimum cost of ownership.
WI-22xx Series - Wafer Inspector The ICOS® WI-22xx Wafer Inspector performs automated optical inspection and metrology of microelectronic devices on a variety of wafer substrates, surface inspection, and 2D bump inspection. The WI-22xx Wafer Inspector offers a dramatic improvement in wafer inspection speed, allowing manufacturers to transition to larger LED and MEMS wafer sizes.
PVI-6 Solar - Automated Optical In-line Solar Wafer and Cell Inspection The PVI-6? is designed for optical in-line dual sided inspection of photovoltaic (PV) wafers and cells. The newest addition to KLA-Tencor?s ICOS division?s PV portfolio, the PVI-6 provides customers with the capability to inspect solar wafers and cells at the highest speed and accuracy for all stages of the production process. These new capabilities enable solar manufacturers to achieve substantial yield improvements and more accurate product classification
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