NEPCON West - Fiberoptic Expo Conference Proceedings


INTELLIGENT SPC METHODOLOGY USING AOI/XRAY DATA CORRELATION

Author: Jeff Harrell
Company: Agilent Technologies
Date Published: 12/3/2002   Conference: NEPCON West - Fiberoptic Expo


Abstract: High-yield process control techniques in SMT manufacturing have historically been very challenging with many difficulties in implementation [1]. In addition, with the current state of the marketplace and resulting economic pressure to manage workforce size, manufacturers have been forced to increase the workload of individuals, making the discipline of good process control a very cumbersome task.

Therefore, manufacturers have looked to more automated inspection and audit tools to gather data for proper process characterization and actionable process feedback. The use of imaging (automated optical inspection, or AOI, and X-Ray) test platforms throughout the process allows the manufacturer to select the best inspection parameters based on how each platform excels.

In order to have efficient and beneficial data correlation, two conditions have to be met: (1) Data integrity or quality of data must be maintained at a high level to gain confident feedback, and (2) The typical fault spectrum based upon board type, complexity, and process must dictate a specific test strategy, one that is both economical and efficient. With this approach, the most comprehensive, high-quality data can be generated to provide process feedback.

Once this information is obtained, it can be processed through intelligent Statistical Process Control (SPC) filters. These sophisticated conjunctive data filters can establish root cause of defects significantly faster, and provide actionable feedback to correct problems and improve process rather than simply identify common defects and trends. Additional benefits of this methodology occur when there are redundancies in test coverage.

These would include both the analysis of operator error dispositions to validate quality of data from inspection platforms, and the ability to identify false passes at a single tester and to feed back necessary information to make each inspection or test more robust.



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