Improvement of vision inspection during tip to tip measurement through parameter optimization - Rahman, Muhamad Hakim (2018)
During the running of mass production, yield loss is unavoidable. This can be due to various factors which include but not limited due to the incoming material quality, the machine itself or unnecessary rejection of a product. Unnecessary rejection of a good product often occurs during the vision inspection process within the semiconductor industry. The term is usually called over rejection which refers to the excellent unit or product is mistakenly identified as a reject unit by vision inspection system. One of the scenarios that are commonly occurring is at the Acceleration Machine (ACC). ACC machine is a final process within the test and taping process which consists singulation process, pick and place, acceleration test, vision inspection and lastly taping process. Before a device is taped to the reel, the device will go through two vision inspection process; the first is the sides vision inspection and the second is the top view vision inspection. This report presents the research on the optimisation of auto vision inspection at Acceleration Machine (ACC) focusing on the top view vision inspection. The top vision inspection includes checking the tip to tip, Delta lead to lead, lead to lead and laser marking. In this project, the focus is on the potential optimisation of the vision parameter that causes over rejection. The research starts with the identification of the vision parameter that contributes to the over rejection by the vision system. Three-factor has been identified which are the lead shutter time, laser shutter time and brightness value. All the factors will be tested in design expert software. A comprehensive data collection will be conducted to gather important measurements by the vision system. Upon completion of the data collection, the optimization of the parameters will be done using the full factorial method. At the end of this research, the optimize parameter setting will be validated into the dedicated machine to, and monitoring of the result will be conducted base on the defined timeline. Post to the optimized parameter setting, it is hope that the vision will be able to capture measurement value similar to the drawing value within the acceptable tolerance. This will undoubtedly reduce over rejection and indirectly improve the production rate. Validation of the optimal parameter value show that, vision inspection able to capture measurement value with zero delta measurement compare to scope measurement that indicates the optimal value is workable.