AI techniques for reliability prediction for electronic components:
In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair...
Gespeichert in:
Weitere Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
2019.
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components. |
Beschreibung: | Description based upon print version of record. |
Beschreibung: | 23 PDFs (330 pages) Also available in print. |
Format: | Mode of access: World Wide Web. |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781799814665 |
Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
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245 | 0 | 0 | |a AI techniques for reliability prediction for electronic components |c Cherry Bhargava, editor. |
246 | 3 | |a Artificial intelligence for reliability prediction for electronic components | |
264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c 2019. | |
300 | |a 23 PDFs (330 pages) | ||
336 | |a text |2 rdacontent | ||
337 | |a electronic |2 isbdmedia | ||
338 | |a online resource |2 rdacarrier | ||
500 | |a Description based upon print version of record. | ||
504 | |a Includes bibliographical references and index. | ||
505 | 0 | |a Chapter 1. Reliability analysis: need and techniques -- Chapter 2. Reliability study of polymers -- Chapter 3. Reliability of CNTFET and NW-FET devices -- Chapter 4. Traditional and non-traditional optimization techniques to enhance reliability in process industries -- Chapter 5. Residual life estimation of humidity sensor DHT11 using artificial neural networks -- Chapter 6. Nanocomposite-based humidity sensor: reliability prediction using artificial intelligence techniques -- Chapter 7. Role of artificial neural network for prediction of gait parameters and patterns -- Chapter 8. Modelling analysis and simulation for reliability prediction for thermal power system -- Chapter 9. High level transformation techniques for designing reliable and secure DSP architectures -- Chapter 10. Design for testability of high-speed advance multipliers: design for testability -- Chapter 11. A novel moth-flame algorithm for PID-controlled processes with time delay -- Chapter 12. Artificial intelligence for interface management in wireless heterogeneous networks -- Chapter 13. PVT variability check on UCM architectures at extreme temperature-process changes -- Chapter 14. Frequency-based RO-PUF -- Chapter 15. PID plus second order derivative controller for automatic voltage regulator using linear quadratic regulator -- Chapter 16. 40-ghz inductor less VCO. | |
506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
520 | 3 | |a In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components. | |
530 | |a Also available in print. | ||
538 | |a Mode of access: World Wide Web. | ||
588 | |a Description based on title screen (IGI Global, viewed 10/31/2019). | ||
650 | 0 | |a Artificial intelligence |x Industrial applications. | |
650 | 0 | |a Electronic apparatus and appliances |x Reliability. | |
650 | 0 | |a Electronic apparatus and appliances |x Service life. | |
650 | 0 | |a Electronic apparatus and appliances |x Testing |x Data processing. | |
655 | 0 | |a Electronic books. | |
700 | 1 | |a Bhargava, Cherry, |e editor. | |
710 | 2 | |a IGI Global, |e publisher. | |
776 | 0 | 8 | |i Print version: |z 1799814645 |z 9781799814641 |
856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1464-1 |3 Volltext |
912 | |a ZDB-98-IGB | ||
049 | |a DE-863 |
Datensatz im Suchindex
DE-BY-FWS_katkey | ZDB-98-IGB-00233140 |
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adam_text | |
any_adam_object | |
author2 | Bhargava, Cherry |
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author_facet | Bhargava, Cherry |
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callnumber-search | TK7870.23 .A44 2019e |
callnumber-sort | TK 47870.23 A44 42019E |
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collection | ZDB-98-IGB |
contents | Chapter 1. Reliability analysis: need and techniques -- Chapter 2. Reliability study of polymers -- Chapter 3. Reliability of CNTFET and NW-FET devices -- Chapter 4. Traditional and non-traditional optimization techniques to enhance reliability in process industries -- Chapter 5. Residual life estimation of humidity sensor DHT11 using artificial neural networks -- Chapter 6. Nanocomposite-based humidity sensor: reliability prediction using artificial intelligence techniques -- Chapter 7. Role of artificial neural network for prediction of gait parameters and patterns -- Chapter 8. Modelling analysis and simulation for reliability prediction for thermal power system -- Chapter 9. High level transformation techniques for designing reliable and secure DSP architectures -- Chapter 10. Design for testability of high-speed advance multipliers: design for testability -- Chapter 11. A novel moth-flame algorithm for PID-controlled processes with time delay -- Chapter 12. Artificial intelligence for interface management in wireless heterogeneous networks -- Chapter 13. PVT variability check on UCM architectures at extreme temperature-process changes -- Chapter 14. Frequency-based RO-PUF -- Chapter 15. PID plus second order derivative controller for automatic voltage regulator using linear quadratic regulator -- Chapter 16. 40-ghz inductor less VCO. |
ctrlnum | (CaBNVSL)slc00000046 (OCoLC)1126231487 |
dewey-full | 621.38150285/63 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 621 - Applied physics |
dewey-raw | 621.38150285/63 |
dewey-search | 621.38150285/63 |
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dewey-tens | 620 - Engineering and allied operations |
discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
format | Electronic eBook |
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genre | Electronic books. |
genre_facet | Electronic books. |
id | ZDB-98-IGB-00233140 |
illustrated | Not Illustrated |
indexdate | 2024-11-26T14:51:55Z |
institution | BVB |
isbn | 9781799814665 |
language | English |
oclc_num | 1126231487 |
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owner | DE-863 DE-BY-FWS |
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physical | 23 PDFs (330 pages) Also available in print. |
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publishDate | 2019 |
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publishDateSort | 2019 |
publisher | IGI Global, |
record_format | marc |
spelling | AI techniques for reliability prediction for electronic components Cherry Bhargava, editor. Artificial intelligence for reliability prediction for electronic components Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, 2019. 23 PDFs (330 pages) text rdacontent electronic isbdmedia online resource rdacarrier Description based upon print version of record. Includes bibliographical references and index. Chapter 1. Reliability analysis: need and techniques -- Chapter 2. Reliability study of polymers -- Chapter 3. Reliability of CNTFET and NW-FET devices -- Chapter 4. Traditional and non-traditional optimization techniques to enhance reliability in process industries -- Chapter 5. Residual life estimation of humidity sensor DHT11 using artificial neural networks -- Chapter 6. Nanocomposite-based humidity sensor: reliability prediction using artificial intelligence techniques -- Chapter 7. Role of artificial neural network for prediction of gait parameters and patterns -- Chapter 8. Modelling analysis and simulation for reliability prediction for thermal power system -- Chapter 9. High level transformation techniques for designing reliable and secure DSP architectures -- Chapter 10. Design for testability of high-speed advance multipliers: design for testability -- Chapter 11. A novel moth-flame algorithm for PID-controlled processes with time delay -- Chapter 12. Artificial intelligence for interface management in wireless heterogeneous networks -- Chapter 13. PVT variability check on UCM architectures at extreme temperature-process changes -- Chapter 14. Frequency-based RO-PUF -- Chapter 15. PID plus second order derivative controller for automatic voltage regulator using linear quadratic regulator -- Chapter 16. 40-ghz inductor less VCO. Restricted to subscribers or individual electronic text purchasers. In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 10/31/2019). Artificial intelligence Industrial applications. Electronic apparatus and appliances Reliability. Electronic apparatus and appliances Service life. Electronic apparatus and appliances Testing Data processing. Electronic books. Bhargava, Cherry, editor. IGI Global, publisher. Print version: 1799814645 9781799814641 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1464-1 Volltext |
spellingShingle | AI techniques for reliability prediction for electronic components Chapter 1. Reliability analysis: need and techniques -- Chapter 2. Reliability study of polymers -- Chapter 3. Reliability of CNTFET and NW-FET devices -- Chapter 4. Traditional and non-traditional optimization techniques to enhance reliability in process industries -- Chapter 5. Residual life estimation of humidity sensor DHT11 using artificial neural networks -- Chapter 6. Nanocomposite-based humidity sensor: reliability prediction using artificial intelligence techniques -- Chapter 7. Role of artificial neural network for prediction of gait parameters and patterns -- Chapter 8. Modelling analysis and simulation for reliability prediction for thermal power system -- Chapter 9. High level transformation techniques for designing reliable and secure DSP architectures -- Chapter 10. Design for testability of high-speed advance multipliers: design for testability -- Chapter 11. A novel moth-flame algorithm for PID-controlled processes with time delay -- Chapter 12. Artificial intelligence for interface management in wireless heterogeneous networks -- Chapter 13. PVT variability check on UCM architectures at extreme temperature-process changes -- Chapter 14. Frequency-based RO-PUF -- Chapter 15. PID plus second order derivative controller for automatic voltage regulator using linear quadratic regulator -- Chapter 16. 40-ghz inductor less VCO. Artificial intelligence Industrial applications. Electronic apparatus and appliances Reliability. Electronic apparatus and appliances Service life. Electronic apparatus and appliances Testing Data processing. |
title | AI techniques for reliability prediction for electronic components |
title_alt | Artificial intelligence for reliability prediction for electronic components |
title_auth | AI techniques for reliability prediction for electronic components |
title_exact_search | AI techniques for reliability prediction for electronic components |
title_full | AI techniques for reliability prediction for electronic components Cherry Bhargava, editor. |
title_fullStr | AI techniques for reliability prediction for electronic components Cherry Bhargava, editor. |
title_full_unstemmed | AI techniques for reliability prediction for electronic components Cherry Bhargava, editor. |
title_short | AI techniques for reliability prediction for electronic components |
title_sort | ai techniques for reliability prediction for electronic components |
topic | Artificial intelligence Industrial applications. Electronic apparatus and appliances Reliability. Electronic apparatus and appliances Service life. Electronic apparatus and appliances Testing Data processing. |
topic_facet | Artificial intelligence Industrial applications. Electronic apparatus and appliances Reliability. Electronic apparatus and appliances Service life. Electronic apparatus and appliances Testing Data processing. Electronic books. |
url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1464-1 |
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