Guide Reliability Physics and Engineering: Time-To-Failure Modeling

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Reliability Physics and Engineering: Time-To-Failure Modeling

Customers who bought this item also bought. Stock Image. Published by Springer New Hardcover Quantity Available: 1. Seller Rating:. It was to return to a common and consistent method for estimating the inherent reliability of an eventually mature design during acquisition so that competitive designs could be evaluated by a common process.

Transitioning to Physics of Failure Reliability Assessments for Electronics

Since Rev F failure rate data and models are a frozen snapshot of conditions from over 15 years ago that are well out of date. Many organizations attempted to improve their reliability estimates by using modified or alternative prediction methods. These efforts to make better predictions and more reliable systems were encouraged by many reliability professionals.


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However, the diversity made it difficult for acquisition personnel and program managers to evaluate proposals for new systems. Concerns were raised at the Rev G kickoff meeting that developing better reliability assessment methods should be considered along with the needs of the acquisition community when defining the goals for updating for the first time in many years. Therefore as second phase to the project to develop proposals for better reliability prediction methods for a future revision H was also started.

The Phase II task was to research and define a proposal for an improved reliability prediction methodology and the best means to implement it. This effort compiled and documented the needs of potential reliability prediction results users and correlated them into functions and tasks for achieving the objective. The QFD analysis identified that a more holistic approach to reliability prediction was needed that could more accurately evaluate the risks of specific issues in addition to overall reliability.

A need to evaluate the time to first failure in addition to MTBF and a way to deal with the constant emergence of new technologies that did not require years of field performance before reliability predictions could be made were also identified. After considerable evaluation, the Phase II team converged on two basic approaches: 1 To improve the empirical reliability predictions approach and 2 to embrace and standardize the science-based Physics of Failure PoF approach where cause and effects deterministic relationships are analyzed using fundamental engineering principles.

Eventually a two-part hybrid approach was developed where first an updated and improved empirical approach based on the RIAC Plus methodology [11] was proposed to support acquisition comparison and program management activities during the early stages of an acquisition program.

The proposed second part would define Physics of Failure PoF modeling and simulation methods for use during the actual engineering phases of a program. This method would assess the susceptibility and durability of design alternatives to various failure mechanisms under the intended usage profile and application environment. In this way items that lacked the required durability and reliability required for an application can be screened out early, at low cost during the design phase resulting in more reliable hardware and systems.

Since the Plus approach has been well defined in other publications [11], the rest of this paper will provide an overview to the PoF approach proposed for Rev H. PoF also known as Reliability Physics applies analysis early in the design process to assess the reliability and durability of design alternatives in specific applications. This enables designers to make design and manufacturing choices that minimize failure opportunities, which produces reliability optimized, robust products. PoF focuses on understanding the cause and effect physical processes and mechanisms that cause degradation and failure of materials and components.

It is based in the analysis of loads and stresses in an application and evaluating the ability of materials to endure them from a strength and mechanics of material point of view. This approach integrates reliability into the design process via a science-based process for evaluating materials, structures and technologies. These techniques known as load-to-strength interference analysis are a basic part of mechanical, structural, construction and civil engineering processes.

Since electrical engineers were not trained in or familiar with structural analysis techniques and the miniaturization of electronics had not yet reached the point where structural and strength optimization was required. As with any new technology, the reasons for failures were not initially well understood. Due to these difficulties, actuarial reliability methods were adapted instead and became so entrenched that the development of better alternatives were stifled.

Failure analysis research has led PoF methods to be organized around 3 generic root cause failure categories which are: Errors and Excessive Variation, Wearout Mechanisms and Overstress Mechanisms. In items that are well designed for the loads in their application, overstress failures are rare and random. They occur only under conditions that are beyond the design intent of the device, such as acts of god or war, such as being struck by lightning or submerged in a flood.

Understand Product Performance with Life Data Analysis using Weibull

Overstress is the PoF engineering view of random failures from traditional reliability theory. If overstress failures occur frequently, then the device may not be not suited for the application or the range of application stresses were underestimated. PoF load-stress analysis is used to determine the strength limits of a design for stresses like shock and electrical transients and to assess if they are adequate.

Wearout in PoF is defined as stress driven damage accumulation of materials which covers failure mechanisms like fatigue and corrosion. Numerous methods for stress analysis in structural materials have been developed by mechanical engineers. These techniques are readily adapted to the microstructures of electronics once material properties have been characterized. PoF wearout analysis identifies the most likely components or features in a device to fail 1st, 2nd , 3rd.

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Reliability Physics and Engineering : Time-To-Failure Modeling

Designers can then identify items that are prone to various types of wearout during the intended service life of a new product. The design can then be optimized until susceptibility to wearout risks during the desired service life are designed out. Errors and excessive variation issues comprise the PoF view of the traditional concept of infant mortality. Opportunities for error and variation touch every aspect of design, supply chain and manufacturing processes. These types of failures are the most diverse and challenging category.

Since diverse, random, stochastic events are involved, these types of failures can not be modeled or predicted using a deterministic PoF cause and effect approach.


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However, reliability improvements are still possible when PoF knowledge and lessons learned are used to evaluate and select manufacturing processes that are proven to be capable, ensure robustness and implement error proofing. The WG developed a dual approach for integrating PoF overstress and wearout analysis into Rev. H along side improved empirical prediction methods. These sections are meant to serve as a guide to the type of PoF models and methods that exist for reliability assessments.

Introduction to Physics of Failure Models

The proposed PoF component section focuses on the failure mechanisms and reliability aspects of semiconductor dies, microcircuit packaging, interconnects and wearout mechanisms of components such as capacitors. A current key industry concern is the expected reduction in lifetime reliability due to the scaling reduction of IC die features that have reached nanoscale levels of 90, 65 and 45 nanometers nm [12].

The proposed PoF circuit card assembly section defines 4 categories of analysis techniques See Figure 1 that can be performed with currently available Computer Aided Engineering CAE software. A probabilistic mechanics [14] approach is used to account for variation issues.

The 4 categories are:. Results are provided in terms of time to first failure, the expected failure distribution in an ordered list of 1st, 2nd, 3rd.