In the semiconductor manufacturing industry, because of the expensive and complex processes, it is extremely important to maintain product yield, cycle time, and quality. Maintaining the stability of the manufacturing process and cultivating the ability to quickly return the process to normal when it is unstable due to a special cause have a large impact on quality, cost, and delivery, and are extremely important issues.
NXP Semiconductors has developed a systematic problem-solving approach and promotes continuous improvement. By using this approach, integrated with Six Sigma, the company has been able to logically identify the cause and solution to return product characteristics or manufacturing processes to normal in the shortest possible time.
This presentation will use several different problem examples to explain how to use the basic problem-solving tools of Six Sigma, as well as statistical modeling and screening functions used in machine learning (ML), to analyze big data and narrow down the possible causes from dozens to a small number of causes effectively and quickly.
