Can reliability and production testing keep pace with the explosive growth in microelectromechanical system (MEMS) based product volumes? Soon it will be the rare consumer product that does not include a MEMS device bringing us closer to the possibility of a $1 trillion MEMS market. In order to achieve greater adoption of the technology, cost and quality goals will need to be met through testing and reliability. This was the focus of the MEMS Testing and Reliability 2012 conference produced by MEMS Journal and MicroElectronics Packaging and Test Council (MEPTEC).
Mervi Paulasto-Kröckel (Professor, Aalto University) in “On the Reliability Characterization of MEMS Devices” examined the current methods for reliability assessment in MEMS devices and identified necessary improvements. Currently, the reliability of MEMS devices are evaluated in the functioning state. A sensor is tested by applying a known stimulus and comparing the sensor output while varying the test conditions such as temperature, humidity, etc. MEMS actuators are similarly tested by providing a known input and measuring the output of the actuator over the range of test conditions. Significant deviation between the expected and measured result indicates a failure. Simple functional test is appropriate for manufacturing quality testing however it is inadequate for measuring and improving device reliability.
Professor Paulasto-Kröckel compared these processes commonly used to estimate MEMS reliability to those used in the microelectronics industry. She identified major methodology changes required in MEMS testing based upon the extensive experience of the microelectronics industry. Today’s reliability testing can be considered a three step circular process: Design of Experiment (DOE), Functionality Test, and Observation. The Observation step is where the engineer analyzes the data to see what happened during the test. The engineer then suggests changes to the design which if needed requires a new cycle starting with the DOE to confirm the changes. This is clearly a trial and error based method typically leading to long delays due to the design and manufacturing process required before additional tests can be performed. Testing the device simply as a black box does not lend itself to the understanding of the physics of the failures to improve future designs.
The microelectronics industry has adopted a more robust method for reliability testing which uses a four step circular process: DOE, Reliability Test, Failure Analysis (FA), and Device Modeling. There are two significant differences from the methodology currently used for MEMS. First, reliability testing is designed to stress the device based upon known or predicted failure modes not to simply test the device over a wide range of test conditions. And secondly, the failure analysis goes beyond the functional test results to determine the fundamental physics of why the failure occurred. This data is then used to update the device models used to predict the behavior of the device based upon the fundamental physics. The models are then used to predict how the changes will improve the device and to start another cycle of reliability testing.
MEMS devices should be tested through a similar four step process. Unlike electronics which do not move, MEMS devices are more complex in terms of the fundamental physics and physical properties. This makes the modeling more challenging since energetics and kinetics need to be clearly understood and how they impact the microstructures of the device during operation. For example, a stress-strain analysis needs to be performed to make sure that the limits of the material and design are not exceeded within the specified operation range of the MEMS device.
Examples of applying this four step methodology to a MEMS gyroscope and microphone were reviewed in depth by Professor Paulasto-Kröckel. Even though the test conditions were different, the same process was used in both cases. The gyroscopes were tested for shock impact and surprisingly the electronics failed sooner than the package itself at roughly half the force. FA and modeling were done to understand the failure of the electronics, package, and MEMS structure. The MEMS failure modes predicted by the models were confirmed by microscopy. Shock testing on the microphones confirmed two failure modes suspected in the design by the initial finite element analysis (FEA) modeling. These results show the value of this four step methodology and includes a better understanding of the physics of the failures.
High temperature and humidity testing was also performed on both devices. Lastly, corrosion tests were performed on the microphones. The team is currently analyzing these results and will work to update the models to better understand the physical basis of potential failures under these conditions.
In “Dynamic Product Performance Testing of Capacitive MEMS Elements at Wafer Level”, Hugh Miller (Founder, Chairman and CEO of Solidus Technologies) reviewed how MEMS devices can be dynamically tested on wafer using only electrical stimuli. The Solidus system performs this dynamic test by electrostatically activating the MEMS structure, applying a drive voltage and measuring the system response. Typical sensors, unlike actuators, are not designed to be electrostatically actuated. However, it is often possible to excite the sensor structure using a voltage to drive the sense elements (often a comb structure whose movement is designed to be sensed by the change in capacitance) electrostatically. The voltage levels required to initiate movement may be significantly different from those used to measure the capacitance. Therefore, these voltages are best applied by the test system rather than the electronics packaged in the MEMS device.
There are several different tests that can be applied in this manner. The first is applying the drive voltage as a pulse and then measuring the output (typically the capacitance) to determine the step response of the particular unit. Like a typical damped oscillator, most MEMS devices will resonate from the initial pulse and the signal will decay over time. The resonant frequency, Q, and damping ratio can all be calculated. A variation in any of these factors from baseline would indicate a difference in the particular device due to a defect or manufacturing variation. These factors can also be correlated to final package or system performance thereby eliminating bad devices earlier in the manufacturing process. By performing this test at the wafer level, the cost of packaging and testing a bad device can be avoided. The fact that a MEMS device often has an integrated application specific integrated circuit (ASIC) inside the package makes it even more important to eliminate bad MEMS devices before packaging to lower costs and avoid wasting good ASICs.
Other waveforms can be used to perform tests in a similar fashion. A signal that ramps up and then down can be used to test the range of motion of the element, to determine if there is no stiction, and to measure the hysteresis of the device. A sweep frequency waveform can also be used to determine the resonant frequency of the part. As with the step response, using these and other tests the response of the particular unit can be compared to the baseline to identify unit to unit variation and potential defects. The baseline is determined either through modeling and/or characterization of reference parts. By performing these tests at wafer before packaging, not only will there be cost savings but quicker feedback if process or design adjustments are required.