Computer vision for automatic inspection of complex metal patterns on multichip modules (MCM-D)

Computer vision techniques have been developed and implemented in a high volume manufacturing environment for automatic optical inspection (AOI) of multichip modules with thin films (MCM-D). Inspection-of complex thin film metal patterns for critical defects despite high topological and cosmetic variation is discussed in this paper. An Orbot TF501 inspection platform was used to implement the procedures and algorithms. The techniques presented are capable of detecting both electrical and non-electrical defects. Electrical defects include near shorts, resistive opens, and near opens such as dishdowns where there may be a local height reduction in a signal line. Non-electrical defects include wrong metallurgy, defects with height and contamination. AOI may be used to shorten cycle time, improve yields and better control latent defects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>