An IC manufacturing yield model considering intra-die variations

2006 ◽  
Author(s):  
J. Luo ◽  
S. Sinha ◽  
Q. Su ◽  
J. Kawa ◽  
C. Chiang
Keyword(s):  
Yield Model ◽  
Ic Manufacturing ◽  
Manufacturing Yield

An IC manufacturing yield model considering intra-die variations

2006 ◽  
Author(s):  
Jianfeng Luo ◽  
Subarna Sinha ◽  
Qing Su ◽  
Jamil Kawa ◽  
Charles Chiang
Keyword(s):  
Yield Model ◽  
Ic Manufacturing ◽  
Manufacturing Yield

Application of the Strip Yield Model to Crack Growth Predictions for Structural Steel

2010 ◽  
Vol 57 (1) ◽  
pp. 1-20
Author(s):  
Małgorzata Skorupa ◽  
Tomasz Machniewicz
Keyword(s):  
Structural Steel ◽  
Crack Growth ◽  
Model Calibration ◽  
Load History ◽  
Yield Model ◽  
Variable Amplitude Loading ◽  
Variable Amplitude ◽  
Constraint Factors ◽  
Strip Yield Model ◽  
Closure Mechanism

Application of the Strip Yield Model to Crack Growth Predictions for Structural SteelA strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.

ESTIMASI HASIL AIR DARI DAERAH TANGKAPAN AIR DANAU RAWA PENING DENGAN MENGGUNAKAN MODEL INVEST

2017 ◽  
Vol 19 (2) ◽  
pp. 157
Author(s):  
Nunung Puji Nugroho
Keyword(s):  
Spatial Distribution ◽  
Ecosystem Services ◽  
Water Resources ◽  
High Water ◽  
Water Yield ◽  
Accurate Information ◽  
Yield Model ◽  
Catchment Areas ◽  
Integrated Valuation ◽  
Valuation Of Ecosystem Services

<p class="JudulABSInd"><strong>ABSTRAK</strong></p><p class="abstrak">Informasi hasil air dari suatu ekosistem sangat penting dalam pengelolaan sumber daya air. Dalam perencanaan kegiatan konservasi sumber daya air, informasi sebaran spasial hasil air diperlukan untuk menentukan prioritas wilayah terkait dengan alokasi anggaran. Hasil air dari suatu ekosistem atau daerah aliran sungai (DAS) dapat diestimasi dengan menggunakan model hidrologi. Penelitian ini bertujuan untuk mendapatkan informasi tentang hasil air, baik besaran maupun sebaran spasialnya, dari daerah tangkapan air (DTA) Danau Rawa Pening. Hasil air dari lokasi penelitian dihitung dengan menggunakan model hasil air pada InVEST (<em>the Integrated Valuation of Ecosystem Services and Tradeoffs</em>), yang didasarkan pada pendekatan neraca air. Hasil perhitungan menunjukkan bahwa volume hasil air di DTA Danau Rawa Pening pada tahun 2015 adalah sekitar 337 juta m<sup>3</sup>. SubDAS Galeh, sebagai subDAS terluas, merupakan penghasil air terbesar (72,4 juta m<sup>3</sup>) diikuti oleh subDAS Sraten (66,8 juta m<sup>3</sup>) dan Parat (62,4 juta m<sup>3</sup>). Secara spasial, hasil air di lokasi kajian mempunyai nilai antara 0 hingga 29.634,19 m<sup>3</sup>/ha. Wilayah hulu dan tengah subDAS Sraten secara umum mempunyai hasil air yang lebih tinggi, sedangkan wilayah danau dan sekitarnya serta hulu subDAS Galeh mempunyai hasil air yang lebih rendah dibandingkan dengan wilayah lainnya. Wilayah dengan hasil air tinggi dapat diprioritaskan dalam kegiatan konservasi sumber daya air untuk mendukung pasokan air ke Danau Rawa Pening.</p><p><strong><em>Kata kunci</em></strong><em>: hasil air, daerah tangkapan air, model InVEST, Danau Rawa Pening</em><em></em></p><p class="judulABS"><strong>ABSTRACT</strong></p><p class="Abstrakeng">Accurate information on water yield from an ecosystem is very important in the management of water resources. In the planning of water resources conservation activities, the information on the spatial distribution of water yield is needed to determine regional priorities related to budget allocations. The water yield from an ecosystem or watershed can be estimated using a hydrological model. This study aimed to obtain information about the water yield, both the magnitude and their spatial distribution, from the catchment areas of Lake Rawa Pening. The water yield from the study area was calculated using the water yield model in InVEST (the Integrated Valuation of Ecosystem Services and Tradeoffs), which based on the water balance approach. The results indicated that the volume of water yield in Lake Rawa Pening for 2015 is approximately 337 million m<sup>3</sup>. Galeh subwatershed, as the largest subwatershed, is the largest water producer (72.4 million m<sup>3</sup>), followed by Sraten subwatershed (66.8 million m<sup>3</sup>) and Parat subwatershed (62.4 million m<sup>3</sup>). Spatially, the water yield at the study site has a value between 0 to 29,634.19 m<sup>3</sup>/ha. Upstream and middle areas of Sraten subwatershed generally have higher water yield, while the lake and its surrounding areas as well as the upstream of Galeh subwatershed have lower water yield compared to other regions. The regions with high water yield can be prioritized in water resource conservation activities to support the supply of water to Lake Rawa Pening.</p><p><strong><em>Keywords</em></strong><em>: water yield, catchment areas, InVEST model, Lake Rawa Pening</em><em></em></p>

Application of EDS Technique for OSP Film Thickness Measurement

2006 ◽  
Author(s):  
Prong Kongsubto ◽  
Sirarat Kongwudthiti
Keyword(s):  
Thin Film ◽  
Quantitative Analysis ◽  
Joint Strength ◽  
Critical Factor ◽  
Thickness Measurement ◽  
Ic Manufacturing ◽  
And Control ◽  
Film Thickness Measurement ◽  
Non Destructive

Abstract Organic solderability preservatives (OSPs) pad is one of the pad finishing technologies where Cu pad is coated with a thin film of an organic material to protect Cu from oxidation during storage and many processes in IC manufacturing. Thickness of OSP film is a critical factor that we have to consider and control in order to achieve desirable joint strength. Until now, no non-destructive technique has been proposed to measure OSP thickness on substrate. This paper reports about the development of EDS technique for estimating OSP thickness, starting with determination of the EDS parameter followed by establishing the correlation between C/Cu ratio and OSP thickness and, finally, evaluating the accuracy of the EDS technique for OSP thickness measurement. EDS quantitative analysis was proved that it can be utilized for OSP thickness estimation.

Effect of Ordered Transplanting and Optimized Broadcasting on Super High Yield and Photosynthetic Productivity and Exploration of Rice Super High Yield Model

2013 ◽  
Vol 39 (9) ◽  
pp. 1652 ◽  
Author(s):  
Ke XU ◽  
Bao-Wei GUO ◽  
Hong-Cheng ZHANG ◽  
Xing-Tao ZHOU ◽  
Hou-Cun CHEN ◽  
...  
Keyword(s):  
High Yield ◽  
Yield Model ◽  
Photosynthetic Productivity

Enhancement of Drucker-Prager yield model by adding corner points for pressure-dependent materials

2021 ◽  
Vol 35 (3) ◽  
pp. 1017-1027
Author(s):  
Kwangmin Lee ◽  
Karuppasamy Pandian Marimuthu ◽  
Jungmoo Han ◽  
Hyungyil Lee
Keyword(s):  
Yield Model ◽  
Corner Points

Palweed:Wheat: A Bioeconomic Decision Model for Postemergence Weed Management in Winter Wheat (Triticum aestivum)

Weed Science ◽  
1995 ◽  
Vol 43 (4) ◽  
pp. 595-603 ◽  
Author(s):  
Tae-Jin Kwon ◽  
Douglas L. Young ◽  
Frank L. Young ◽  
Chris M. Boerboom
Keyword(s):  
Winter Wheat ◽  
Weed Management ◽  
Decision Model ◽  
Damage Function ◽  
Yield Response ◽  
Density Functions ◽  
Yield Model ◽  
Weed Density ◽  
Annual Grasses ◽  
Winter Annual

Based on six years of data from a field experiment near Pullman, WA, a bioeconomic decision model was developed to annually estimate the optimal post-emergence herbicide types and rates to control multiple weed species in winter wheat under various tillage systems and crop rotations. The model name, PALWEED:WHEAT, signifies a Washington-Idaho Palouse region weed management model for winter wheat The model consists of linear preharvest weed density functions, a nonlinear yield response function, and a profit function. Preharvest weed density functions were estimated for four weed groups: summer annual grasses, winter annual grasses, summer annual broadleaves, and winter annual broadleaves. A single aggregated weed competition index was developed from the four density functions for use functions for use in the yield model. A yield model containing a logistic damage function performed better than a model containing a rectangular hyperbolic damage function. Herbicides were grouped into three categories: preplant nonselective, postemergence broadleaf, and postemergence grass. PALWEED:WHEAT was applied to average conditions of the 6-yr experiment to predict herbicide treatments that maximized profit. In comparison to average treatment rates in the 6-yr experiment, the bioeconomic decision model recommended less postemergence herbicide. The weed management recommendations of PALWEED:WHEAT behaved as expected by agronomic and economic theory in response to changes in assumed weed populations, herbicide costs, crop prices, and possible restrictions on herbicide application rates.

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