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Test throughput is not always fast enough to inspect all solder joints within the manufacturing cycle time for the printed circuit assembly. A significant learning curve is required to become expert at developing solder joint tests with both low false accept and false reject rates.

Successful implementation of automated inspection systems into printed circuit assembly production lines requires a significant investment in training, process analysis, and system integration. The implementation can be a lengthy process that requires concerted effort by engineers or skilled technicians. Listed here are highlights of what several manufacturers have learned are key aspects of successfully implementing automated inspection systems:

If you need to know more about any of the topics discussed in this book, go to the Propeller Manual for details. The information provided in the manual is not repeated here. This being the case, I strongly recommend you obtain a copy of the Propeller Manual to use as your absolute reference as you study these chapters. A copy of the manual is also available in the Help section of the Propeller Tool. You should have the electronic copy open on your computer when programming the Propeller so that you

Assess requirements carefully Start by carefully assessing the requirements for automated inspection in the particular production environment into which the system will be integrated Determine exactly what kinds of defects are most important for the inspection system to detect, which measurements will most help with process improvement, and what benefits will generate the quickest financial return on investment3 This assessment must consider the testing and measurement capability that already has been implemented as well as new requirements arising from future printed circuit assembly designs Evaluate a select set of systems thoroughly Select a small number of automated inspection systems to evaluate thoroughly and compare them against the system requirements.

The evaluation should include a benchmark using printed circuit assemblies from production to determine the system s capabilities to detect accurately the important defect types within the required false reject rate, repeatedly make the required measurements, and not exceed the required test time Elements of cost of ownership should be well understood, including test development time, maintenance skills and cost, expected system downtime, supplier support infrastructure, and supplier maintenance services and prices Plan for factory system interfaces Consider and plan carefully for interfaces to other factory systems These systems include board-handling equipment, bar code reading systems, computer-aided design (CAD) systems for automatic download of board layout and component package information, and quality data management systems for SPC and historical quality tracking Focus on SPC measurements Start with a focus on SPC measurements instead of defect detection.

Until the process variation is reduced, most manufacturers will encounter either a false reject rate or a false accept rate that is higher than desired Allowing one rate or the other to be too high while focusing on reducing the process variation first avoids time-consuming, unproductive tweaking of acceptance thresholds Reducing process variation requires correlating measurements to the process parameters causing the variation and defects, and then properly adjusting these process parameters4.

Define defects carefully With an understanding of the selected system s capability, carefully define the defects that must be detected for product quality and reliability. Many of the visual inspection criteria used in the past are not appropriate for automated inspection systems because the system takes objective and different measurements. Invest enough resources Do not underestimate the initial resource investment required to obtain optimum benefit from an automated inspection system. The implementation plan should include dedicated technical support for the first six months of operation and test development. Developing a thorough understanding of the measurement results and correlating the data to process parameters are key to successful use of the system. Implementation should also address the fact that production personnel will have to be convinced of the accuracy of the system s test results before full benefit can be obtained from the system.