The world of the semiconductor industry is becoming increasingly competitive and forcing manufacturers to achieve significant reductions in time to market. As a result, every step in the manufacturing process needs to be completed in less time while maintaining a high level of control and quality.
Given the significant quantity of data collected at every stage of a manufacturing lot and the sometimes-limited statistics available to describe the problem, traditional techniques are not always adequate for resolving the issues faced by the yield engineer. This paper will delve into a number of practical ways to make use of partitioning techniques to address these challenges through two case studies.
The first involves using partitioning for root-cause identification in the case of a loss of electrical yield that is not detected during the manufacturing process; the second examines a variation in electrical yield detected during manufacturing.