Challenges in the assembly and handling of thin film capped MEMS devices

The Impact of Housing on the Characteristics of Ceramic Pressure Sensors--An Issue of Design for Manufacturability

An exploratory study of the impact of housing on the characteristics of a low-temperature co-fired ceramic (LTCC) pressure sensor is presented. The ceramic sensor structure is sealed in a plastic housing. This may have non-negligible effect on the final characteristics and should be considered in the early design phase. The manufacturability issue mainly concerning the selection of available housing and the most appropriate materials was considered with respect to different requirements for low and high pressure ranges of operation. Numerical predictions showed the trends and helped reveal the critical design parameters. Proper selection of the adhesive material remains an essential issue. Curing of the epoxy adhesive may introduce non-negligible residual stresses, which considerably influence the sensor’s characteristics.

Improving electronic sensor reliability by robust outlier screening

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.