Query: Reliability prediction of semiconductor devices using modified physics of failure approach

Candidate papers:

abstract: Traditional approaches like MIL HDBK, Telcordia, and PRISM etc. have limitation in accurately predicting the reliability due to advancement in technology, process, materials etc. As predicting the reliability is the major concern in the field of electronics, physics of failure approach gained considerable importance as it involves investigating the root cause which further helps in reliability growth by redesigning the structure, changing the parameters at manufacturer level and modifying the items at circuit level. On the other hand, probability and statistics methods provide quantitative data with reliability indices from testing by experimentation and by simulations. In this paper, qualitative data from PoF approach and quantitative data from the statistical analysis is combined to form a modified physics of failure approach. This methodology overcomes some of the challenges faced by PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is added to this approach to choose the best option from different failure data models, failure mechanisms, failure criteria and other factors.
author_names: Adithya Thaduri

Ajit Kumar Verma

Gopika Vinod

Rajesh Gopinath

Uday Kumar
title: Reliability prediction of semiconductor devices using modified physics of failure approach
venue: Int. J. Syst. Assur. Eng. Manag.
year: 2013

abstract: Traditional reliability prediction methods are being confounded by current and near future semiconductor technologies, as gate feature sizes shrink below 100 nanometers (nm) causing the emergence of atomic level failure mechanisms and early wearout. These devices and their failure characteristics are rapidly changing as the semiconductor industry aggressively pursues scaling in a highly competitive marketplace. The Physics of Failure (PoF) approach to reliability has advantages for assessing these technologies. Industry groups are adapting PoF research results for use in predicting reliability for these technologies. This paper describes industry collaborative efforts in developing new reliability prediction approaches to meet future industry challenges.
author_names: Lori E Bechtold
title: Industry consensus approach to physics of failure in reliability prediction
venue: 2010 Proceedings Annual Reliability and Maintainability Symposium (RAMS)
year: 2010

abstract: An original reliability prediction procedure is presented. The physics of failure accounts for the failure mechanisms involved (a lognormal distribution was presumed) the interactions (synergies) between the technology factors depending on the manufacturing techniques are considered. The basis of this methodology (called SYRP=synergetic reliability prediction) is the assessment of failure risk coefficients (FRC) based on fuzzy logic, for the potential failure mechanisms induced at each manufacturing step. These FRC are corrected at the subsequent steps by considering the synergy of the manufacturing factors, At the end of the manufacturing process, final FRC are obtained for each potential failure mechanism; the parameters of the lognormal distribution are calculated with a simple algorithm. Experimental results for four lots of the same type of semiconductor devices, each lot being manufactured with a slightly different technology, were obtained. SYRP forecasts for these four lots agree well with accelerated life test results. This is a fairly good result, because SYRP was used early, at the design phase.
author_names: Marius Bazu
title: A combined fuzzy logic and physics of failure approach to reliability prediction
year: 1995

abstract: Modern electronics typically consist of microprocessors and other complex integrated circuits (ICs) such as FPGAs, ADCs, and memory. They are susceptible to electrical, mechanical and thermal modes of failure like other components on a printed circuit board, but due to their materials, complexity and roles within a circuit, accurately predicting a failure rate has become difficult, if not impossible. Development of these critical components has conformed to Moore's Law, where the number of transistors on a die doubles approximately every two years. This trend has been successfully followed over the last four decades through reduction in transistor sizes creating faster, smaller ICs with greatly reduced power dissipation. Although this is great news for developers and users of high performance equipment, including consumer products and analytical instrumentation, a crucial, yet underlying reliability risk has emerged. Semiconductor failure mechanisms, which are far worse at these minute feature sizes (tens of nanometers) result in higher failure rates, shorter device lifetimes and unanticipated early device wearout. This is of special concern to users whose requirements include long service lifetimes and rugged environmental conditions, such as aerospace, defense, and other high performance (ADHP) industries. To that end, the Aerospace Vehicle Systems Institute (AVSI) has conducted research in this area, and DfR Solutions has performed much of the work as a contractor to AVSI. Physics of Failure (PoF) knowledge and an accurate mathematical approach which utilizes semiconductor formulae, industry accepted failure mechanism models, and device functionality can access reliability of those integrated circuits vital to system stability. Currently, four semiconductor failure mechanisms that exist in silicon based ICs are analyzed: Electromigration (EM) Time Dependent Dielectric Breakdown (TDDB) Hot Carrier Injection (HCI) and Negative Bias Temperature Instability (NBTI) Mitigation of these inherent failure mechanisms, including those considered wearout, is possible only when reliability can be quantified. Algorithms have been folded into a software application not only to calculate a failure rate, but also to produce confidence intervals and lifetime curves, using both steady state and wearout failure rates, for the IC under analysis. The algorithms have been statistically verified through testing and employ data and formulae from semiconductor materials (including technology node parameters) circuit fundamentals, transistor behavior, circuit design and fabrication processes. Initial development has yielded a user friendly software module with the ability to address siliconbased integrated circuits of the 0.35m, 0.25m, 0.18m, 0.13m and 90nm technology nodes. INTRODUCTION In the ADHP industries, there is considerable interest in assessing the long term reliability of electronics whose anticipated lifetimes extend beyond those of consumer "throw away" electronics. Because complex integrated circuits within their designs may face wearout or even failure within the period of useful life, it is necessary to investigate the effects of use and environmental conditions on these components. The main concern is that submicron process technologies drive device wearout into the regions of useful life well before wearout was initially anticipated to occur. The continuous scaling down of semiconductor feature sizes raises challenges in electronic circuit reliability prediction. Smaller and faster circuits cause higher current densities, lower voltage tolerances and higher electric fields, which make the devices more vulnerable to early failure. Emerging new generations of electronic devices require improved tools for reliability prediction in order to investigate new manifestations of existing failure mechanisms, such as NBTI, EM, HCI, and TDDB. Working with AVSI, DfR Solutions has developed an integrated circuit (IC) reliability calculator using a multiple failure mechanism approach. This approach successfully models the simultaneous degradation behaviors of multiple failure mechanisms on integrated circuit devices. The multiple mechanism model extrapolates independent acceleration factors for each semiconductor mechanism of concern based on the transistor stress states within each distinct functional group. Integrated circuit lifetime is calculated from semiconductor materials and technology node, IC complexity, and operating conditions. A major input to the tool is integrated circuit complexity. This characteristic has been approached by using specific functionality cells called functional groups. The current set of functional groups covers memory based devices and analog todigital conversion circuitry. Technology node process parameters, functional groups and their functionality, and field/test operating conditions are used to perform the calculations. Prior work verified the statistical assessment of the algorithms for aerospace electronic systems and confirmed that no single semiconductor failure mechanism dominates failures in the field. Two physics of failure approaches are used within the tool to determine each of four semiconductor failure mechanisms' contribution to the overall device failure rate. The tool calculates a failure rate and also produces confidence intervals and a lifetime curve, using both steady state and wearout failure rates, for the part under analysis. Reliability prediction simulations are the most powerful tools developed over the years to cope with these challenging demands. Simulations may provide a wide range of predictions, starting from the lower level treatment of physics of failure (PoF) mechanisms up to high level simulations of entire devices [1, 2] As with all simulation problems, primary questions need to be answered, such as: "How accurate are the simulation results in comparison to in service behavior?" and "What is the confidence level achieved by the simulations?" Thus the validation and calibration of the simulation tools becomes a most critical task. Reliability data generated from field failures best represents the electronic circuit reliability in the context of the target system/application. Field failure rates represent competing failure mechanisms' effects and include actual stresses, in contrast to standard industry accelerated life tests. In this paper, the failure rates of recorded field data from 2002 to 2009 were determined for various device process technologies and feature sizes (or "technology nodes" Theses failure rates are used to verify the PoF models and a competing failure approach, as implemented in the software. Comparison of the actual and simulated failure rates shows a strong correlation. Furthermore, comparing the field failure rates with those obtained from the standard industry High Temperature Operating Life (HTOL) Test reveals the inadequacy of the HTOL to predict integrated circuit (IC) failure rates. The validation process and its data sources are illustrated in Figure 1.
author_names: Edward J Wyrwas

College Park

Lloyd W Condra

Avshalom Hava
title: Accurate Quantitative Physics of Failure Approach to Integrated Circuit Reliability
year: 2011

abstract: Conventionally, reliability prediction of electronic components is carried out using standard handbooks such as MIL STD 217 plus, Telcordia, etc. But these methods fail to provide a realistic estimate of reliability for upcoming technologies. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. Industries employ different technologies like CMOS, BJT and BICMOS for various applications. The possibility of chance of failure at interdependencies of materials, processes, and characteristics under operating conditions is the major concern which affects the performance of the devices. They are characterized by several failure mechanisms at various stages such as wafer level, interconnection, etc. For this, the dominant failure mechanisms and stress parameters needs to be identified. Optocouplers are used in input protection of several instrumentation systems providing safety under over stress conditions. Hence, there is a need to study the reliability and safety aspects of optocouplers. Design of experiments is an efficient and prominent methodology for finding the reliability of the item, as the experiment provides a proof for the hypothesis under consideration. One of the important techniques involved is Taguchi method which is employed for finding the prominent failure mechanisms in semiconductor devices. By physics of failure approach, the factors that are affecting the performance on both environmental and electrical parameters with stress levels for optocouplers are identified. By constructing a 2 stage Taguchi array with these parameters where output parameters decides the effect of top two dominant failure mechanisms and their extent of chance of failure can be predicted. This analysis helps us in making the appropriate modifications considering both the failure mechanisms for the reliability growth of these devices. This paper highlights the application of design of experiments for finding the dominant failure mechanisms towards using physics of failure approach in electronic reliability prediction of optocouplers for application of instrumentation.
author_names: Adithya Thaduri

Ajit Kumar Verma

Gopika Vinod

Mr Rajesh

Uday Kumar
title: TWO STAGE DESIGN OF EXPERIMENTS APPROACH FOR PREDICTION OF RELIABILITY OF OPTOCOUPLERS
year: 2012

abstract: This paper presents a probabilistic approach based reliability prediction model of semiconductor light emitting devices. Using this model with given initial light emitting performance and degradation behavior otherwise determined by experiment, the reliability function of the devices is obtained, and the results correlate well with experimental results. (Modeling the initial light emitting performance and the degradation behavior is still an on going effort and is not included in this paper. Eventually, this model will include both parts of the modeling to provide complete analytical results of reliability prediction. This study is a step to develop a complete physics of failure based reliability prediction methodology for semiconductor light emitting devices. It provides an approach and proves the feasibility of determining a reliability function based on fundamental parameters of device performance.
author_names: Jingsong Xie

Michael G Pecht
title: Reliability prediction modeling of semiconductor light emitting device
year: 2003

abstract: Conventionally, reliability prediction of electronic components is carried out using standard handbooks such as MIL STD 217plus, Telecordia, etc. But these methods fail to provide a realistic estimate of reliability for upcoming technologies. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. Industries employ different technologies like CMOS, BJT and BICMOS for various applications. The possibility of chance of failure at interdependencies of materials, processes, and characteristics under operating conditions is the major concern which affects the performance of the devices. They are characterized by several failure mechanisms at various stages such as wafer level, interconnection, etc. For this, the dominant failure mechanisms and stress parameters needs to be identified. Optocouplers are used in input protection of several instrumentation systems providing safety under over stress conditions. Hence, there is a need to study the reliability and safety aspects of optocouplers. Design of experiments is an efficient and prominent methodology for finding the reliability of the item, as the experiment provides a proof for the hypothesis under consideration. One of the important techniques involved is Tagauchi method which employs for finding the prominent failure mechanisms in semiconductor devices. By physics of failure approach, the factors that are affecting the performance on both environmental and electrical parameters with stress levels for optocouplers are identified. By constructing a 2 stage tagauchi array with these parameters where output parameters decides the effect of top two dominant failure mechanisms and their extent of chance of failure can be predicted. This analysis helps us in making the appropriate modifications considering both the failure mechanisms for the reliability growth of these devices. This paper highlights the application of design of experiments for finding the dominant failure mechanisms towards using physics of failure approach in electronic reliability prediction of optocouplers for application of instrumentation.
author_names: Adithya Thaduri

Ajit Kumar Verma

Gopika Vinod

Rajesh Gopalan
title: Reliability prediction of optocouplers for the safety of digital instrumentation
venue: 2011 IEEE International Conference on Quality and Reliability
year: 2011

abstract: Abstract Power electronics uses semiconductor technology to convert and control electrical power. Demands for efficient energy management, conversion and conservation, and the increasing take up of electronics in transport systems has resulted in tremendous growth in the use of power electronics devices such as Insulated Gate Bipolar Transistors (IGBT's) The packaging of power electronics devices involves a number of challenges for the design engineer in terms of reliability. For example, IGBT modules will contain a number of semiconductor dies within a small footprint bonded to substrates with aluminum wires and wide area solder joints. To a great extent, the reliability of the package will depend on the thermo mechanical behavior of these materials. This paper details a physics of failure approach to reliability predictions of IGBT modules. It also illustrates the need for a probabilistic approach to reliability predictions that include the effects of design variations. Also discussed are technologies for predicting the remaining life of the package when subjected to qualification stresses or in service stresses using prognostics methods.
author_names: Hua Lu

Chris Bailey

Chunyan Yin
title: Design for reliability of power electronics modules
venue: Microelectron. Reliab.
year: 2009

abstract: A method for reliability prediction, called SYRP (synergetic reliability prediction) is presented, based on a combined fuzzy logic physics of failure approach. SYRP is used for a semiconductor device (thermal sensors) and the estimations, compared with experimental results, prove to be accurate enough. Also, the problems to be solved for using this method for MEMS are presented. The specific case of a MEMS Fabry Perot interferometer is analyzed and the failure rate estimations are discussed. The method seems to be particularly useful for the reliability analysis made by virtual prototyping
author_names: Marius Bazu

Catalin Tibeica

Lucian Galateanu

Virgil Emil Ilian
title: Fuzzy Logic Reliability Predictions in Microtechnologies
venue: International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA IAWTIC'06)
year: 2005

abstract: Because of increased manufacturing competitiveness, new methods for reliability estimation are being developed. Intelligent manufacturing relies upon accurate component and product reliability estimates for determining warranty costs, as well as optimal maintenance, inspection, and replacement schedules. Accelerated life testing is one approach that is used for shortening the life of products or components or hastening their performance degradation with the purpose of obtaining data that may be used to predict device life or performance under normal operating conditions. The proportional hazards (PH) model is a non parametric multiple regression approach for reliability estimation, in which a baseline hazard function is modified multiplicatively by covariates (i.e. applied stresses) While the PH model is a distribution free approach, specific assumptions need to be made about the time behavior of the hazard rates. A neural network (NN) is particularly useful in pattern recognition problems that involve capturing and learning complex underlying (but consistent) trends in the data. Neural networks are highly non linear, and in some cases are capable of producing better approximations than multiple regression. This paper reports on the comparison of PH and NN models for the analysis of time dependent dielectric breakdown data for a metal oxide semiconductor integrated circuit. In this case, the NN model results in a better fit to the data based upon minimizing the mean square error of the predictions when using failure data from an elevated temperature and voltage to predict reliability at a lower temperature and voltage.
author_names: James T Luxhoj

Huan-Jyh Shyur
title: Comparison of proportional hazards models and neural networks for reliability estimation
venue: J. Intell. Manuf.
year: 1997