PCR for Derivation of Parameter Dependencies, Thermo-Mechanical Norris-Landzberg Acceleration Factors, Goldmann Fatigue Constants for Leadfree Electronics

2009 ◽  
Author(s):  
Pradeep Lall ◽  
Aniket Shirgaokar ◽  
Dineshkumar Arunachalam ◽  
Jeff Suhling ◽  
Mark Strickland ◽  
...  
Keyword(s):  
Test Data ◽  
Thermal Cycle ◽  
Regression Models ◽  
Reliability Prediction ◽  
Maximum Temperature ◽  
Temperature Cycle ◽  
Data Sets ◽  
Accelerated Test ◽  
Bga Packages ◽  
Part Selection

Goldmann Constants and Norris-Landzberg acceleration factors for lead-free solders have been developed based on principal component regression models (PCR) for reliability prediction and part selection of area-array packaging architectures under thermo-mechanical loads. Models have been developed in conjunction with Stepwise Regression Methods for identification of the main effects. Package architectures studied include, BGA packages mounted on copper-core and no-core printed circuit assemblies in harsh environments. The models have been developed based on thermo-mechanical reliability data acquired on copper-core and no-core assemblies in four different thermal cycling conditions. Packages with Sn3Ag0.5Cu solder alloy interconnects have been examined. The models have been developed based on perturbation of accelerated test thermo-mechanical failure data. Data has been gathered on nine different thermal cycle conditions with SAC305 alloys. The thermal cycle conditions differ in temperature range, dwell times, maximum temperature and minimum temperature to enable development of constants needed for the life prediction and assessment of acceleration factors. Goldmann Constants and the Norris-Landzberg acceleration factors have been benchmarked against previously published values. In addition, model predictions have been validated against validation data-sets which have not been used for model development. Convergence of statistical models with experimental data has been demonstrated using a single factor design of experiment study for individual factors including temperature cycle magnitude, relative coefficient of thermal expansion, and diagonal length of the chip. The predicted and measured acceleration factors have also been computed and correlated. Good correlations have been achieved for parameters examined. Previously, the feasibility of using multiple linear regression models for reliability prediction has been demonstrated for flex-substrate BGA packages [Lall 2004, 2005], flip-chip packages [Lall 2005] and ceramic BGA packages [Lall 2007]. The presented methodology is valuable in the development of fatigue damage constants for the application specific accelerated test data-sets and provides a method to develop institutional learning based on prior accelerated test data.

Ridge Regression Based Development of Norris-Landzberg Acceleration Factors and Goldmann Constants for Leadfree Electronics

2011 ◽  
Author(s):  
Pradeep Lall ◽  
Dinesh Arunachalam ◽  
Jeff Suhling
Keyword(s):  
Ridge Regression ◽  
Thermal Cycle ◽  
Regression Models ◽  
Coefficient Of Thermal Expansion ◽  
Model Development ◽  
High Sensitivity ◽  
Maximum Temperature ◽  
Temperature Cycle ◽  
Linear Regression Models ◽  
Part Selection

Goldmann Constants and Norris-Landzberg acceleration factors for lead-free solders have been developed based on ridge regression models (RR) for reliability prediction and part selection of area-array packaging architectures under thermo-mechanical loads. Ridge regression adds a small positive bias to the diagonal of the covariance matrix to prevent high sensitivity to variables that are correlated. The proposed procedure proves to be a better tool for prediction than multiple-linear regression models. Models have been developed in conjunction with Stepwise Regression Methods for identification of the main effects. Package architectures studied include, BGA packages mounted on copper-core and no-core printed circuit assemblies in harsh environments. The models have been developed based on thermo-mechanical reliability data acquired on copper-core and no-core assemblies in four different thermal cycling conditions. Packages with Sn3Ag0.5Cu solder alloy interconnects have been examined. The models have been developed based on perturbation of accelerated test thermo-mechanical failure data. Data has been gathered on nine different thermal cycle conditions with SAC305 alloys. The thermal cycle conditions differ in temperature range, dwell times, maximum temperature and minimum temperature to enable development of constants needed for the life prediction and assessment of acceleration factors. Norris-Landzberg acceleration factors have been benchmarked against previously published values. In addition, model predictions have been validated against validation datasets which have not been used for model development. Convergence of statistical models with experimental data has been demonstrated using a single factor design of experiment study for individual factors including temperature cycle magnitude, relative coefficient of thermal expansion, and diagonal length of the chip. The predicted and measured acceleration factors have also been computed and correlated. Good correlations have been achieved for parameters examined.

Norris–Landzberg Acceleration Factors and Goldmann Constants for SAC305 Lead-Free Electronics

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Pradeep Lall ◽  
Aniket Shirgaokar ◽  
Dinesh Arunachalam
Keyword(s):  
Regression Models ◽  
Flip Chip ◽  
Reliability Prediction ◽  
Harsh Environments ◽  
Mechanical Reliability ◽  
Accelerated Test ◽  
Thermal Reliability ◽  
Area Array ◽  
Bga Packages ◽  
Part Selection

Goldmann constants and Norris–Landzberg acceleration factors for SAC305 lead-free solders have been developed based on principal component regression models (PCR) for reliability prediction and part selection of area-array packaging architectures under thermo-mechanical loads. Models have been developed in conjunction with stepwise regression methods for identification of the main effects. Package architectures studied include ball-grid array (BGA) packages mounted on copper-core and no-core printed circuit assemblies in harsh environments. The models have been developed based on thermomechanical reliability data acquired on copper-core and no-core assemblies in four different thermal cycling conditions. Packages with Sn3Ag0.5Cu solder alloy interconnects have been examined. The models have been developed based on perturbation of accelerated test thermomechanical failure data. Data have been gathered on nine different thermal cycle conditions with SAC305 alloys. The thermal cycle conditions differ in temperature range, dwell times, maximum temperature, and minimum temperature to enable development of constants needed for the life prediction and assessment of acceleration factors. Goldmann constants and the Norris–Landzberg acceleration factors have been benchmarked against previously published values. In addition, model predictions have been validated against validation datasets which have not been used for model development. Convergence of statistical models with experimental data has been demonstrated using a single factor design of experimental study for individual factors including temperature cycle magnitude, relative coefficient of thermal expansion, and diagonal length of the chip. The predicted and measured acceleration factors have also been computed and correlated. Good correlations have been achieved for parameters examined. Previously, the feasibility of using multiple linear regression models for reliability prediction has been demonstrated for flex-substrate BGA packages (Lall et al., 2004, “Thermal Reliability Considerations for Deployment of Area Array Packages in Harsh Environments,” Proceedings of the ITherm 2004, 9th Intersociety Conference on Thermal and Thermo-mechanical Phenomena, Las Vegas, Nevada, Jun. 1–4, pp. 259–267, Lall et al., 2005, “Thermal Reliability Considerations for Deployment of Area Array Packages in Harsh Environments,” IEEE Trans. Compon. Packag. Technol., 28(3), pp. 457–466., flip-chip packages (Lall et al., 2005, “Decision-Support Models for Thermo-Mechanical Reliability of Leadfree Flip-Chip Electronics in Extreme Environments,” Proceedings of the 55th IEEE Electronic Components and Technology Conference, Orlando, FL, Jun. 1–3, pp. 127–136) and ceramic BGA packages (Lall et al., 2007, “Thermo-Mechanical Reliability Based Part Selection Models for Addressing Part Obsolescence in CBGA, CCGA, FLEXBGA, and Flip-Chip Packages,” ASME InterPACK Conference, Vancouver, British Columbia, Canada, Jul. 8–12, Paper No. IPACK2007-33832, pp. 1–18). The presented methodology is valuable in the development of fatigue damage constants for the application specific accelerated test datasets and provides a method to develop institutional learning based on prior accelerated test data.

Models for Component Selection and Thermo-Mechanical Reliability Trade-Offs to Address Component Obsolescence in Military Electronics

2008 ◽  
Author(s):  
Pradeep Lall ◽  
Aniket Shirgaokar ◽  
Jeffrey Suhling
Keyword(s):  
Regression Models ◽  
Operating Conditions ◽  
System Level ◽  
Reliability Prediction ◽  
Harsh Environments ◽  
Minimal Risk ◽  
Mechanical Reliability ◽  
Trade Offs ◽  
Bga Packages ◽  
Part Selection

Product miniaturization trends in microelectronics industry are driving the need for smaller, faster, more reliable, less expensive IC’s. Area array packages have been increasingly targeted for use in harsh environments such as automotive underhood, military and space applications but system-level decision support and part-selection tools and techniques for thermo-mechanical reliability trade-offs while addressing part obsolescence in extreme environments are scarce. The models presented in this paper provide decision guidance for smart selection and substitution to address component obsolescence by perturbing product designs for minimal risk insertion of new packaging technologies. It is conceivable for commercial off the shelf parts to become unavailable during the production-life of a product. Typical Commercial-of-the-Shelf parts are manufactured for a period of two to four years, and IC manufacturing processes are available for five to six years. It is envisioned that the reliability assessment models will enable turn-key evaluation of geometric architecture, material properties, and operating conditions effects on thermo-mechanical reliability. The presented approach enables the evaluation of qualitative parameter interaction effects, which are often ignored in closed-form modeling, have been incorporated in this work. Previously, the feasibility of using multiple linear regression models for reliability prediction has been demonstrated for flex-substrate BGA packages [1, 2], flip-chip packages [3, 4] and ceramic BGA packages [5]. In this paper, principal component regression models (PCR) have been investigated for reliability prediction and part selection of area package architectures under thermo-mechanical loads in conjunction with stepwise regression methods. Package architectures studied include, BGA packages mounted on CU-CORE and NO-CORE printed circuit assemblies in harsh environments. The models have been developed based on thermo-mechanical reliability data acquired on copper-core and no-core assemblies in four different thermal cycling conditions. Solder alloys examined include SnPb and SAC Alloys.

What Induces Central Australian Arid Zone Trees and Shrubs to Flower and Fruit?

1993 ◽  
Vol 41 (3) ◽  
pp. 307 ◽  
Author(s):  
MH Friedel ◽  
DJ Nelson ◽  
AD Sparrow ◽  
JE Kinloch ◽  
JR Maconochie
Keyword(s):  
Regression Models ◽  
Arid Zone ◽  
Late Summer ◽  
Maximum Temperature ◽  
Data Sets ◽  
Animal Populations ◽  
Time Periods ◽  
Trees And Shrubs ◽  
Term Data

We developed two sets of regression models for flowering and fruiting of arid zone trees and shrubs, based on (i) rainfall in the current and preceding seasons and (ii) soil moisture lagged over varying time periods combined with mean maximum temperature and daylength in the month prior to phenological observations. Using up to 4 years of flowering and fruiting records, we found that both approaches identified responses matching those reported in two other long-term data sets or in the literature, for some species but not for all. The second approach appeared to provide better correlations than the first but we were unable to predict flowering and fruiting effectively. Flowering and fruiting of central Australian trees and shrubs were least in late summer, creating potential limitations on animal populations dependent on them for food. With better predictive capabilities, there is some scope for managing the trees and shrubs for particular purposes. However, very long-term phenological records are needed to improve predictions.

Reliability prediction using limited test data

2017 ◽  
Author(s):  
Darryl Kellner ◽  
Steve Rogers ◽  
Antonio Scappaticci ◽  
Elizabeth Schwartz
Keyword(s):  
Test Data ◽  
Reliability Prediction

Mapping genetic variation and seed zones for Bromus carinatus in the Blue Mountains of eastern Oregon, USAIn this article, mention of companies or trade names does not constitute an endorsement of any product or procedure.

Botany ◽  
2010 ◽  
Vol 88 (8) ◽  
pp. 725-736 ◽  
Author(s):  
R. C. Johnson ◽  
Vicky J. Erickson ◽  
Nancy L. Mandel ◽  
J. Bradley St Clair ◽  
Kenneth W. Vance-Borland
Keyword(s):  
Environmental Variables ◽  
Regression Models ◽  
Plant Traits ◽  
Seed Source ◽  
Maximum Temperature ◽  
Blue Mountains ◽  
Seed Transfer ◽  
Bromus Carinatus ◽  
Seed Zones ◽  
Transfer Zones

Seed transfer zones ensure that germplasm selected for restoration is suitable and sustainable in diverse environments. In this study, seed zones were developed for mountain brome ( Bromus carinatus Hook. & Arn.) in the Blue Mountains of northeastern Oregon and adjoining Washington. Plants from 148 Blue Mountain seed source locations were evaluated in common-garden studies at two contrasting test sites. Data on phenology, morphology, and production were collected over two growing seasons. Plant traits varied significantly and were frequently correlated with annual precipitation and annual maximum temperature at seed source locations (P < 0.05). Plants from warmer locations generally had higher dry matter production, longer leaves, wider crowns, denser foliage, and greater plant height than those from cooler locations. Regression models of environmental variables with the first two principal components (PC 1 and PC 2) explained 46% and 40% of the total variation, respectively. Maps of PC 1 and PC 2 generally corresponded to elevation, temperature, and precipitation gradients. The regression models developed from PC 1 and PC 2 and environmental variables were used to map seed transfer zones. These maps will be useful in selecting mountain brome seed sources for habitat restoration in the Blue Mountains.

Analytical stress-strain relation for soils

2021 ◽  
Author(s):  
Kristian Krabbenhoft ◽  
J. Wang
Keyword(s):  
Test Data ◽  
Narrow Range ◽  
Strain Range ◽  
Data Sets ◽  
Soil Tests ◽  
Stress Strain ◽  
Strain Relation ◽  
Stress Strain Relation ◽  
Typical Test ◽  
Typical Soil

A new stress-strain relation capable of reproducing the entire stress-strain range of typical soil tests is presented. The new relation involves a total of five parameters, four of which can be inferred directly from typical test data. The fifth parameter is a fitting parameter with a relatively narrow range. The capabilities of the new relation is demonstrated by the application to various clay and sand data sets.

Improving SAR Altimeter processing over the coastal zone and inland waters - the ESA HYDROCOASTAL project

2021 ◽  
Author(s):  
David Cotton ◽  
Keyword(s):  
Coastal Zone ◽  
Test Data ◽  
River Discharge ◽  
Altimeter Data ◽  
Inland Waters ◽  
Data Sets ◽  
Data Set ◽  
Discharge Data ◽  
Processing Algorithms ◽  
The Impact

&lt;p&gt;&lt;strong&gt;Introduction&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;HYDROCOASTAL is a two year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products.&lt;/p&gt;&lt;p&gt;New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets.&lt;/p&gt;&lt;p&gt;A series of case studies will assess these products in terms of their scientific impacts.&lt;/p&gt;&lt;p&gt;All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;The scientific objectives of HYDROCOASTAL are to enhance our understanding&amp;#160; of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small scale processes that govern these interactions. Also the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes&lt;/p&gt;&lt;p&gt;The technical objectives are to develop and evaluate&amp;#160; new SAR&amp;#160; and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also an improved Wet Troposphere Correction will be developed and evaluated.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Project&amp;#160; Outline&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;There are four tasks to the project&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Scientific Review and Requirements Consolidation: Review the current state of the art in SAR and SARin altimeter data processing as applied to the coastal zone and to inland waters&lt;/li&gt; &lt;li&gt;Implementation and Validation: New processing algorithms with be implemented to generate a Test Data sets, which will be validated against models, in-situ data, and other satellite data sets. Selected algorithms will then be used to generate global coastal zone and river discharge data sets&lt;/li&gt; &lt;li&gt;Impacts Assessment: The impact of these global products will be assess in a series of Case Studies&lt;/li&gt; &lt;li&gt;Outreach and Roadmap: Outreach material will be prepared and distributed to engage with the wider scientific community and provide recommendations for development of future missions and future research.&lt;/li&gt; &lt;/ul&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Presentation&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;The presentation will provide an overview to the project, present the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and early results from the evaluation of the initial test data set.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

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