Cheng, Shunfeng (Ph.D. Mechanical Engineering)
Prognostics and Health Management
During my Ph.D study, I have finished several projects including: 1) the selection of sensor systems for prognostics and health management: a guideline is generated to help users to select sensor systems for prognostics applications; 2) Prognostics for aging systems: the methodology and algorithms are developed to detect the anomaly of aging systems and to identify if the detected anomalies are duo to natural aging; 3) Prognostics for multilayer ceramic capacitors using data-driven methods: data-driven methods are developed and tested to detect the anomalies exhibiting in the monitored data and provide advanced warnings; 4) Failure tracking for medical devices. This project was worked with Food and Drug Administration to use codes to track failure of medical devices. Now I am working on prognostics for polymer positive temperature coefficient (PPTC) resettable fuses. PPTC resettable fuses are made of semi-crystalline polymer and conductive fillers. As a circuit protection component, the failure of the PPTC fuses will damage the circuit or cause to the improper operation of the circuit. In this research, the failure mechanisms of PPTC resettable fuses are been identified and the failure models are in development. The remaining useful life will be predicted based on the combination of the failure models and the data-driven methods.
Crandall, Mike (MS)
High Temperature Lead Free Solder
In 2009 CALCE identified the development of a high temperature lead free solder that minimizes interfacial IMC growth and thereby maximizing reliability as one of the greatest needs in high temperature electronics. Studies correlating IMC thickness to reliability at elevated temperatures is lacking. This study assesses the reliability of 2 commercial lead free solders and 3 novel lead free solder ideas by using steady state aging and a combined thermal and vibration cycling. During cycling samples are removed for shear strength testing and cross sectioning to measure the IMC layer at the joint interface. All solders use ENIG plated polyimide test boards.
Haddad, Gilbert (PhD)
Decision Support for Systems with Prognostic Capabilities
Developed maintenance options; and methodologies to quantify them. After a prognostic indication is obtained, the decision-maker is faced with multiple maintenance options. Quantifying such options results in a system-level value of PHM. Beyond my PhD dissertation, I worked on data-driven prognostics (machine learning and data mining) and decision support systems.
Jazouli, Taoufik ( PhD)
Design for Availability and PHM Cost Modeling
Development of a new “design for availability” methodology that starts with an availability requirement and uses this requirement to predict the necessary design (e.g., reliability), logistics and operations (e.g., spares inventory and maintenance planning) parameters. This includes the life cycle cost and return on investment prediction for the specific availability requirement. The method is general and can be applied when the inputs to the problem are uncertain. The method has been demonstrated on several examples with and without PHM.
Sharon, Gil (Ph.D. Mechanical Engineering)
Improved Flex Cracking Calculator and Failure Analysis for Multilayer Ceramic Capacitors
Develop improved failure analysis techniques for MLCCs with low insulation resistance, and apply these to capacitors from prior temperature-humidity-bias and storage tests. Use finite element modeling to analyze factors affecting cracking of flexible and standard termination capacitors and extend the CALCE flex cracking calculator.
Sotiris, Vasilis (PhD)
Stochastic Processes, Probability Theory, and Data Driven Prognostics
My research is centered on the area of Prognostics and Health Management (PHM) applied to electronic products and systems. The theoretical background is based on statistics and probability theory as well as computational science. One part of the research focuses on Support vector machine (SVM) and Gaussian process (PG) classification in development of Anomaly detection algorithms. I am interested in the Bayesian machine learning setting where non-parametric SVM function estimators can be used as priors to improve more general Gaussian process estimation models. The other part focuses on nonparametric and semi-parametric statistical estimation theory for survival and reliability problems related to electronics life time and survival data. Here event driven degradation processes are modeled using stochastic counting processes and Cox semi-parametric proportional hazard models. In this context I am interested in a) the competing risks environment of the event type random variables b) the likelihoods for censored, truncated and time dependent events c) the product limit estimator for the transition matrix in non homogeneous Markov Process models and d) inference in low population data sets.
Sinha, Koustav (PhD)
Mechanics of Non Planer Interfaces in Flip-Chip Interconnects
With the continued proliferation of low cost, portable consumer electronic products with greater functionality, there is an increasing demand for electronic packaging that is smaller, lighter and less expensive. Flip chip is an essential enabling technology for these products. From a structural perspective, these are multi-layered structures fabricated from highly dissimilar materials. Often, the interfaces between these materials are where failure is most likely to occur when the device is subjected to thermomechanical loading. Thus, understanding and being able to predict the behavior of critical interfaces in a device is directly related to the reliability of the system. To mitigate this it's important to make the interfacial bonding robust by optimizing the bond formation process parameters. This study is on two different interconnect types - the first one involves gold-gold interface in adhesively bonded flip-chip-on-flex packages based on a non conductive adhesive (NCA) bonding process and the second on the crack behavior at the solder-IMC interface in other flip chip joints. The effect of various bonding parameters, geometric features and material properties on the strength behavior of these joints is quantified. This can help optimize the process variables to get the desired strength at these critical interfaces and therefore result in a reliable product.