Diagnosing multiple faulty chains with low pin convolution compressor using compressed production test set

2017 ◽  
Author(s):  
Subhadip Kundu ◽  
Kuldip Kumar ◽  
Rishi Kumar ◽  
Rohit Kapur
Keyword(s):  
Production Test ◽  
Test Set

An effective fault ordering heuristic for SAT-based dynamic test compaction techniques

2014 ◽  
Vol 56 (4) ◽  
Author(s):  
Stephan Eggersglüß ◽  
Rolf Drechsler
Keyword(s):  
Dynamic Test ◽  
Production Test ◽  
Test Set ◽  
Test Compaction ◽  
Test Sets ◽  
Post Production ◽  
Identification Phase ◽  
Compact Test

AbstractEach chip is subjected to a post-production test after fabrication. A set of test patterns is applied to filter out defective devices. The size of this test set is an important issue. Generally, large test sets increase the test costs. Therefore, test compaction techniques are applied to obtain a compact test set. The effectiveness of these technique is significantly influenced by fault ordering. This paper describes how information about hard-to-detect faults can be extracted from an untestable identification phase and be used to develop a fault ordering technique which is able to reduce the pattern counts of highly compacted test sets generated by a SAT-based dynamic test compaction approach.

scholarly journals Data analytics to reduce stop-on-fail test in electronics manufacturing

2019 ◽  
Vol 9 (1) ◽  
pp. 200-211 ◽  
Author(s):  
Ana Elsa Hinojosa Herrera ◽  
Stoyan Stoyanov ◽  
Chris Bailey ◽  
Chris Walshaw ◽  
Chunyan Yin
Keyword(s):  
Cycle Time ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Test Sequence ◽  
Production Cycle ◽  
Production Test ◽  
Test Set ◽  
Electronic Manufacturing ◽  
Computational Procedures ◽  
Incomplete Datasets

AbstractThe use of data driven techniques is popular in smart manufacturing. Machine learning, statistics or a combination of both have been used to improve processes in electronic manufacturing. This paper presents the application of classical techniques to reduce production cycle time by compacting a production test sequence. This set of tests is run on stop-on-fail scenario for quality assurance of an electronical device. Data generated in the production test-set on stop-on-fail scenario challenges the traditional application of the data driven techniques, because of the missing data characteristic. The developed computational procedures handle this application-specific data attribute. The novelty of this work is in the algorithm developed, which applies classical techniques in an iterative environment, as a strategy to analyse incomplete datasets. Results show that the method can reduce a production test set with parametric and non-parametric tests by building an accurate prognostic model. The results can reduce production cycle time and costs. The paper details and provides discussions on the advantages and limitations of the proposed algorithms.

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

RetroBioCat: Computer-Aided Synthesis Planning for Biocatalytic Reactions and Cascades

2020 ◽  
Author(s):  
William Finnigan ◽  
Lorna J. Hepworth ◽  
Nicholas J. Turner ◽  
Sabine Flitsch
Keyword(s):  
Organic Chemistry ◽  
Computer Aided Design ◽  
Selective Synthesis ◽  
Test Set ◽  
Synthesis Design ◽  
Computer Aided ◽  
Synthesis Planning ◽  
Enzymatic Cascades ◽  
Target Molecules ◽  
Aided Design

As the enzyme toolbox for biocatalysis has expanded, so has the potential for the construction of powerful enzymatic cascades for efficient and selective synthesis of target molecules. Additionally, recent advances in computer-aided synthesis planning (CASP) are revolutionizing synthesis design in both synthetic biology and organic chemistry. However, the potential for biocatalysis is not well captured by tools currently available in either field. Here we present RetroBioCat, an intuitive and accessible tool for computer-aided design of biocatalytic cascades, freely available at retrobiocat.com. Our approach uses a set of expertly encoded reaction rules encompassing the enzyme toolbox for biocatalysis, and a system for identifying literature precedent for enzymes with the correct substrate specificity where this is available. Applying these rules for automated biocatalytic retrosynthesis, we show our tool to be capable of identifying promising biocatalytic pathways to target molecules, validated using a test-set of recent cascades described in the literature.

PREDIKSI KUALITAS AIR SUNGAI CILIWUNG DENGAN MENGGUNAKAN ALGORITMA POHON KEPUTUSAN

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Mohammad Haekal ◽  
Henki Bayu Seta ◽  
Mayanda Mega Santoni
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Cross Validation ◽  
Online Monitoring ◽  
Training Set ◽  
Microsoft Excel ◽  
Test Set

Untuk memprediksi kualitas air sungai Ciliwung, telah dilakukan pengolahan data-data hasil pemantauan secara Online Monitoring dengan menggunakan Metode Data Mining. Pada metode ini, pertama-tama data-data hasil pemantauan dibuat dalam bentuk tabel Microsoft Excel, kemudian diolah menjadi bentuk Pohon Keputusan yang disebut Algoritma Pohon Keputusan (Decision Tree) mengunakan aplikasi WEKA. Metode Pohon Keputusan dipilih karena lebih sederhana, mudah dipahami dan mempunyai tingkat akurasi yang sangat tinggi. Jumlah data hasil pemantauan kualitas air sungai Ciliwung yang diolah sebanyak 5.476 data. Hasil klarifikasi dengan Pohon Keputusan, dari 5.476 data ini diperoleh jumlah data yang mengindikasikan sungai Ciliwung Tidak Tercemar sebanyak 1.059 data atau sebesar 19,3242%, dan yang mengindikasikan Tercemar sebanyak 4.417 data atau 80,6758%. Selanjutnya data-data hasil pemantauan ini dievaluasi menggunakan 4 Opsi Tes (Test Option) yaitu dengan Use Training Set, Supplied Test Set, Cross-Validation folds 10, dan Percentage Split 66%. Hasil evaluasi dengan 4 opsi tes yang digunakan ini, semuanya menunjukkan tingkat akurasi yang sangat tinggi, yaitu diatas 99%. Dari data-data hasil peneltian ini dapat diprediksi bahwa sungai Ciliwung terindikasi sebagai sungai tercemar bila mereferensi kepada Peraturan Pemerintah Republik Indonesia nomor 82 tahun 2001 dan diketahui pula bahwa penggunaan aplikasi WEKA dengan Algoritma Pohon Keputusan untuk mengolah data-data hasil pemantauan dengan mengambil tiga parameter (pH, DO dan Nitrat) adalah sangat akuran dan tepat. Kata Kunci : Kualitas air sungai, Data Mining, Algoritma Pohon Keputusan, Aplikasi WEKA.

Failure Analysis of CDM-ESD Damage in a GaAs RFIC

2000 ◽  
Author(s):  
Amy Poe ◽  
Steve Brockett ◽  
Tony Rubalcava
Keyword(s):  
Radio Frequency ◽  
Failure Analysis ◽  
Integrated Circuit ◽  
Production Test ◽  
Analysis Techniques ◽  
Device Model ◽  
Charged Device ◽  
Subsequent Failure

Abstract The intent of this work is to demonstrate the importance of charged device model (CDM) ESD testing and characterization by presenting a case study of a situation in which CDM testing proved invaluable in establishing the reliability of a GaAs radio frequency integrated circuit (RFIC). The problem originated when a sample of passing devices was retested to the final production test. Nine of the 200 sampled devices failed the retest, thus placing the reliability of all of the devices in question. The subsequent failure analysis indicated that the devices failed due to a short on one of two capacitors, bringing into question the reliability of the dielectric. Previous ESD characterization of the part had shown that a certain resistor was likely to fail at thresholds well below the level at which any capacitors were damaged. This paper will discuss the failure analysis techniques which were used and the testing performed to verify the failures were actually due to ESD, and not caused by weak capacitors.

ATE Failure Isolation Methodologies for Failure Analysis, Design Debug and Yield Enhancement

1998 ◽  
Author(s):  
D.S. Patrick ◽  
L.C. Wagner ◽  
P.T. Nguyen
Keyword(s):  
Integrated Circuits ◽  
Failure Analysis ◽  
Yield Enhancement ◽  
Production Test ◽  
Final Test ◽  
Critical Design ◽  
The Past ◽  
Product Engineering ◽  
Time Savings ◽  
Analysis Design

Abstract Failure isolation and debug of CMOS integrated circuits over the past several years has become increasingly difficult to perform on standard failure analysis functional testers. Due to the increase in pin counts, clock speeds, increased complexity and the large number of power supply pins on current ICS, smaller and less equipped testers are often unable to test these newer devices. To reduce the time of analysis and improve the failure isolation capabilities for failing ICS, failure isolation is now performed using the same production testers used in product development, multiprobe and final test. With these production testers, the test hardware, program and pattern sets are already available and ready for use. By using a special interface that docks the production test head to failure isolation equipment such as the emission microscope, liquid crystal station and E-Beam prober, the analyst can quickly and easily isolate the faillure on an IC. This also enables engineers in design, product engineering and the waferfab yield enhancement groups to utilize this equipment to quickly solve critical design and yield issues. Significant cycle time savings have been achieved with the migration to this method of electrical stimulation for failure isolation.

Temperature-Dependent Logic Failure in a GaAs Power Amplifier-Duplexer Module Caused by a Subtle Parasitic Schottky Diode

2014 ◽  
Author(s):  
Rose Emergo ◽  
Steve Brockett ◽  
Pat Hamilton
Keyword(s):  
Power Amplifier ◽  
Schottky Diode ◽  
Production Test ◽  
Temperature Dependent ◽  
Cold Temperatures ◽  
Collector Junction ◽  
Power Mode ◽  
The Difference ◽  
Base Contact ◽  
Single Power

Abstract A single power amplifier-duplexer device was submitted by a customer for analysis. The device was initially considered passing when tested against the production test. However, further electrical testing suggested that the device was stuck in a single power mode for a particular frequency band at cold temperatures only. This paper outlines the systematic isolation of a parasitic Schottky diode formed by a base contactcollector punch through process defect that pulled down the input of a NOR gate leading to the incorrect logic state. Note that this parasitic Schottky diode is parallel to the basecollector junction. It was observed that the logic failure only manifested at colder temperatures because the base contact only slightly diffused into the collector layer. Since the difference in the turn-on voltages between the base-collector junction and the parasitic Schottky diode increases with decreasing temperature, the effect of the parasitic diode is only noticeable at lower temperatures.

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