SMT Magazine

SMT-Dec2017

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62 SMT Magazine • December 2017 by Marco Lajoie and Alain Breton C-MAC MICROELECTRONICS The volume of solder deposition, like any process, has variations that may be character- ized by a statistical distribution curve, wheth- er normal (from causes inherent to the process and of predictable probability) or non-normal (impacted by special causes, intermittent or in- herently unpredictable). For assemblies of mod- erate complexity, density, cost, and reliabili- ty requirements, one may tolerate fairly large variations in volume and still obtain accept- able yields and quality of solder joints, assum- ing that a solder paste inspection (SPI) will ef- fectively segregate gross defects like bridges and misalignment. Surely, this eases the task since a few hours of engineering suffice to launch a new product using standard recipes, and manu- facturing may flow with minimal interruptions from SPI calls or process inputs sliding off tight windows of operation. Solder Printing Process Inputs Impacting Distribution of Paste Volume Why Does it Matter? As complexity, density, cost and reliabili- ty requirements increase, there may be value in narrowing the distribution curve. It is com- mon sense that less variation serves the interest of quality of the more complex and dense circuit boards. It can also affect the cost as it should in- crease the yield and reduce rework and scrap. It does this by reducing the normal variations but also by revealing the outliers, driven by identifi- able special causes which, otherwise, would have remained hidden in larger acceptance windows. Reliability is typically assessed by tests per- formed on relatively small sample size of prod- ucts from a limited number of lots, sometimes repeated at relatively long intervals. In other words, how much of the actual distribution was represented in the samples tested and how dif- ferent are the parts produced between test inter- vals? Narrower distribution should help ensure reproducibility of reliability performance across test samples and production units alike. FEATURE

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