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Accuracy Validation Finds Hidden Problems Affecting DPMO
Accuracy Validation Finds Hidden Problems Affecting DPMO
This paper discusses individual process step validation methods with real examples of improvement that contribute to defect per million opportunities (DPMO) reduction.
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Authored By:
Michael Sivigny, CeTaQ Americas
Bedford, NH

Summary
If you don't measure, you don't know. These are appropriate words for the application of statistical methods for measuring machine and process capabilities in surface mount technology (SMT) manufacturing.

Only through diagnostic measurement and analysis of SMT equipment can quality performance improvement be realized. Measured mean values can be used to ‘soft’ calibrate machines to a higher level of accuracy than available through original equipment manufacturer (OEM) standard calibrations.

With the complexity of high-speed automation combined with high accuracy requirements for product miniaturization, it is necessary to dig deeper with statistically significant data collection methods to understand and solve the root cause of sub-component machine failures which impact product quality.

When machines are allowed to run in ‘maximum accuracy mode', they are more confident and capable to produce today's high reliability electronics with fewer defects. Defect contribution in each process step needs detailed analysis to reduce cost. When costs are minimized, the underlying inherent process efficiencies go way up which contributes to higher productivity and bottom line profitability. The improvement effects of process optimization have a number of intrinsic benefits that can easily maintain high manufacturing productivity.

This paper discusses individual process step validation methods with real examples of improvement that contribute to defect per million opportunities (DPMO) reduction. In stencil printing the characterization considers accuracy of the alignment system and dynamic measurement of squeegee force. During placement, accuracy and placement Z-force are looked at to calibrate head/angle offset associations and dynamically check individual spindle forces and energy dissipation. All while each process step is characterized, the underlying objective is to verify OEM specifications and prove that machines are capable for intended quality performance. This allows engineers to streamline efforts and focus on other areas of improvement.

Conclusions
The effects of regular capability measurement in every process step is critical to improving manufacturing quality of printed circuit boards. With the complexity of today’s products and the ever-challenging size reduction. Better measurement methods are required to understand where defects come from and be able to move to the next level of improvement.

The intrinsic benefits are numerous, and the productivity gains have a penetrating effect on profitability which is what drives the need for improvement.

Initially Published in the SMTA Proceedings

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