Original Date: 01/23/1995
Revision Date: 01/18/2007
Information : Automated Cleaning of Electronic Components
Because of high reliability requirements of their products, Sandia National Laboratories (SNL) pays particular attention to all manufacturing process steps that could impact that reliability, including cleaning. It is imperative that all assembly residues, especially potential long-term corrosives such as skin oils and flux, be completely removed. Since many SNL designs use leadless devices that allow very little space between the component and the printed wiring board, cleaning poses an exceptional challenge. The Intelligent Systems and Robotics Center, in conjunction with the Kansas City manufacturing facility, have developed an automated workcell approach to this cleaning issue.
Because chlorofluorocarbon cleaning materials are no longer permitted, the facility is investigating aqueous cleaning materials, and current cleaning processes in the production facility are mostly manual. This combination has created a lack of precision and lack of control in the cleaning process, as well as excessive cleaning time and solvent usage. In addition, because of the long cleaning cycles and new processes, operators experience a great deal of fatigue and uncertainty. The necessary process control is difficult to establish and maintain.
Therefore, SNL has developed an automated workcell for cleaning electronic components which uses aqueous microdroplet spray technology. CAD data is input into the system which generates a solid model of the printed wiring assembly. Then, using rule-based process knowledge integration, a spray pattern is generated and utilized in the cleaning process. The system then automatically completes a wash, rinse, dry cycle.
By implementing this process, spray control can be improved by increased repeatability and precision control. The automated method can also generate an audit trail for the product processed as well as how it was processed. Cleaning quality is improved, and handling and cleaning required will be reduced.
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