Pub Date : 2012-10-22DOI: 10.1109/AUTEST.2012.6334569
T. Gohel
The challenges of test development and system setup using Automated Test Equipment (ATE) change when transitioning from a world where clock and data are transmitted separately on wide parallel buses to a world where the clock is embedded in data transmitted on fewer high-speed serial lanes. Parallel buses transmit and receive data with a synchronous clock and typically operate at data rates less than 1Gb/s. The challenges in meeting timing requirements for large high-speed parallel buses have limited the growth of parallel bus standards. These challenges have brought a growth in high-speed serial bus standards. Both parallel and serial data transmission come with system design challenges. ATE designed to test high-speed parallel and serial buses includes features to minimize design challenges for the test engineer. This paper discusses critical features in ATE that enable reliable testing of parallel buses with synchronous clocks as well as serial buses with embedded clocks.
{"title":"The practical realities of high-speed digital test in a production environment","authors":"T. Gohel","doi":"10.1109/AUTEST.2012.6334569","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334569","url":null,"abstract":"The challenges of test development and system setup using Automated Test Equipment (ATE) change when transitioning from a world where clock and data are transmitted separately on wide parallel buses to a world where the clock is embedded in data transmitted on fewer high-speed serial lanes. Parallel buses transmit and receive data with a synchronous clock and typically operate at data rates less than 1Gb/s. The challenges in meeting timing requirements for large high-speed parallel buses have limited the growth of parallel bus standards. These challenges have brought a growth in high-speed serial bus standards. Both parallel and serial data transmission come with system design challenges. ATE designed to test high-speed parallel and serial buses includes features to minimize design challenges for the test engineer. This paper discusses critical features in ATE that enable reliable testing of parallel buses with synchronous clocks as well as serial buses with embedded clocks.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130798497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1109/AUTEST.2012.6334523
S. Oonk, F. J. Maldonado, T. Politopoulos
Condition monitoring systems capable of efficiently and accurately diagnosing and identifying faults is a current need for ensuring the proper operation of critical systems. Distributed health monitoring leveraging large sensor networks that provide validated data ensures the proper operation and performance of systems. A key consideration is to have non-intrusive embedded sensors that can be easily added or removed. These needs have motivated the realization of a distributed intelligent health monitoring framework described in this paper based on standardized methods, advanced health monitoring functions at the sensor and system levels, and a state-of-the-art low-power miniature smart sensor (termed the coremicro Reconfigurable Embedded Smart Sensor Node). Major involved technologies consist of: (a) miniature embedded hardware; (b) embedded sensor health monitoring functions (e.g. sensor self-diagnostics, self-healing, and calibration); (c) distributed and intelligent health monitoring at the various system levels; (d) standardized design and communications leveraging the IEEE 1451 standards; and (e) an efficient anomaly awareness mechanism that merges the health monitoring and standardized design aspects.
{"title":"Distributed intelligent health monitoring with the coremicro Reconfigurable Embedded Smart Sensor Node","authors":"S. Oonk, F. J. Maldonado, T. Politopoulos","doi":"10.1109/AUTEST.2012.6334523","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334523","url":null,"abstract":"Condition monitoring systems capable of efficiently and accurately diagnosing and identifying faults is a current need for ensuring the proper operation of critical systems. Distributed health monitoring leveraging large sensor networks that provide validated data ensures the proper operation and performance of systems. A key consideration is to have non-intrusive embedded sensors that can be easily added or removed. These needs have motivated the realization of a distributed intelligent health monitoring framework described in this paper based on standardized methods, advanced health monitoring functions at the sensor and system levels, and a state-of-the-art low-power miniature smart sensor (termed the coremicro Reconfigurable Embedded Smart Sensor Node). Major involved technologies consist of: (a) miniature embedded hardware; (b) embedded sensor health monitoring functions (e.g. sensor self-diagnostics, self-healing, and calibration); (c) distributed and intelligent health monitoring at the various system levels; (d) standardized design and communications leveraging the IEEE 1451 standards; and (e) an efficient anomaly awareness mechanism that merges the health monitoring and standardized design aspects.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"5 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131150610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1109/AUTEST.2012.6334531
Ioana Geanta, Benoît Iung, Didier Theilliol, Michel Schieber, Yann Fusero
This paper proposes a cartography investigation on diagnostics and prognostics techniques accomplished in order to setup the health management for complex vehicle systems in accordance with IVHM (Integrated Vehicle Health Management) principles. Relevant reviews and surveys of the existing approaches are generally realized as statements of the achievements in these fields; however they rarely tackle both diagnostics and prognostics. As classic criteria do not respond to current needs in IVHM, this paper has isolated several main features in order to formally prove the accordance and the effective choice between the system-of-interest, its maintenance system and diagnostics and prognostics algorithms. Thus, the proposed criteria are oriented on the target and on the maintenance systems. The investigated classification established through a multi-criteria selection reveals new orientations which should be considered in IVHM and it also enables further research on future pertinent methods for building a smart multi-model vehicle health assessment reasoner.
{"title":"Multi-criteria cartography investigation on diagnostics and prognostics techniques suited for system and vehicle health maintenance","authors":"Ioana Geanta, Benoît Iung, Didier Theilliol, Michel Schieber, Yann Fusero","doi":"10.1109/AUTEST.2012.6334531","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334531","url":null,"abstract":"This paper proposes a cartography investigation on diagnostics and prognostics techniques accomplished in order to setup the health management for complex vehicle systems in accordance with IVHM (Integrated Vehicle Health Management) principles. Relevant reviews and surveys of the existing approaches are generally realized as statements of the achievements in these fields; however they rarely tackle both diagnostics and prognostics. As classic criteria do not respond to current needs in IVHM, this paper has isolated several main features in order to formally prove the accordance and the effective choice between the system-of-interest, its maintenance system and diagnostics and prognostics algorithms. Thus, the proposed criteria are oriented on the target and on the maintenance systems. The investigated classification established through a multi-criteria selection reveals new orientations which should be considered in IVHM and it also enables further research on future pertinent methods for building a smart multi-model vehicle health assessment reasoner.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134377692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1109/AUTEST.2012.6334584
D. Carey
The electronics industry and the Department of Defense (DoD), has thousands of obsolete legacy automated test systems (ATS). There are many systems, with different hardware and software architectures, that cannot be upgraded. The inability to reliably test products, diagnose faults, and collect historical data is having an effect on mission readiness. This paper describes a test and diagnostic system model that provides a means to use historical test and repair data from all levels of operation. The process reduces rework costs and decreases maintenance and repair costs through earlier and more accurate fault isolation. This work recoups the efforts of the original developer and captures test and diagnostic knowledge for the future. Consequently, the concept has been proposed for implementation within the Army ATS/TPS centers for use at the Army maintenance depots. Additional benefits from this work: development of a reliability database for system, subsystem, component by test type and ATS; tracking system reliability and mission performance data for use in developing requirements for new or upgrade system procurement specifications; and for pushing diagnostic knowledge and support from the sustainment level to the field and vice versa. The work presented will change the process of developing, maintaining and migrating diagnostic test now and into the future.
{"title":"Legacy test program sets migration using fault modeling and dynamic reasoning","authors":"D. Carey","doi":"10.1109/AUTEST.2012.6334584","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334584","url":null,"abstract":"The electronics industry and the Department of Defense (DoD), has thousands of obsolete legacy automated test systems (ATS). There are many systems, with different hardware and software architectures, that cannot be upgraded. The inability to reliably test products, diagnose faults, and collect historical data is having an effect on mission readiness. This paper describes a test and diagnostic system model that provides a means to use historical test and repair data from all levels of operation. The process reduces rework costs and decreases maintenance and repair costs through earlier and more accurate fault isolation. This work recoups the efforts of the original developer and captures test and diagnostic knowledge for the future. Consequently, the concept has been proposed for implementation within the Army ATS/TPS centers for use at the Army maintenance depots. Additional benefits from this work: development of a reliability database for system, subsystem, component by test type and ATS; tracking system reliability and mission performance data for use in developing requirements for new or upgrade system procurement specifications; and for pushing diagnostic knowledge and support from the sustainment level to the field and vice versa. The work presented will change the process of developing, maintaining and migrating diagnostic test now and into the future.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116618440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1109/AUTEST.2012.6334575
M. Dewey, J. Lauffer
Today's complex electronic assemblies employ sophisticated and advanced automated test solutions to verify functional performance - both at the time of manufacture and for depot repair scenarios. Providing go / no-go test solutions are routinely created for all types of electronic assemblies. However, the task of diagnosing today's failed UUTs or systems is not a process that is easily automated. Older generation and less complex electronic assemblies may have employed automated diagnostics such as guided probe but with the complexity of today's electronic assemblies, coupled with long program development time, automated diagnostics has largely been abandoned by OEMs and Depot test / repair facilities. However, with products becoming increasingly complex and with the extended life-cycles of many mil-aero and commercial systems and platforms, the need for automated diagnostics remains in high demand, and this demand continues to increase - particularly at the Depot level where the ability to efficiently and accurately diagnose and repair products is acute. This paper discusses how advances in diagnostic tools can be incorporated with ATE software to create a comprehensive test environment supporting, go / no-go, as well as automated diagnostics. By integrating the diagnostics design knowledge with the test station, test confidence is taken to the highest level and, in the event of a UUT failure, rapid identification of the failed component is now embedded in the test station. Today's high tech test systems provide excellent confidence testing; however, the extended time required to troubleshoot and analyze a faulty UUT complicates support logistics and drives up over all support / maintenance and Unit Production Costs (UPC). Repairing today's complex UUTs requires a high skill level to isolate the failure to the root cause component. By employing an advanced UUT diagnostics design methodology which provides an enhanced understanding of the unit's test capability, coupled with the design knowledge of the UUT, the capabilities of an existing test station can be extended to included advanced diagnostics.
{"title":"Creating automated test and repair solutions with advanced diagnostics and ATE software","authors":"M. Dewey, J. Lauffer","doi":"10.1109/AUTEST.2012.6334575","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334575","url":null,"abstract":"Today's complex electronic assemblies employ sophisticated and advanced automated test solutions to verify functional performance - both at the time of manufacture and for depot repair scenarios. Providing go / no-go test solutions are routinely created for all types of electronic assemblies. However, the task of diagnosing today's failed UUTs or systems is not a process that is easily automated. Older generation and less complex electronic assemblies may have employed automated diagnostics such as guided probe but with the complexity of today's electronic assemblies, coupled with long program development time, automated diagnostics has largely been abandoned by OEMs and Depot test / repair facilities. However, with products becoming increasingly complex and with the extended life-cycles of many mil-aero and commercial systems and platforms, the need for automated diagnostics remains in high demand, and this demand continues to increase - particularly at the Depot level where the ability to efficiently and accurately diagnose and repair products is acute. This paper discusses how advances in diagnostic tools can be incorporated with ATE software to create a comprehensive test environment supporting, go / no-go, as well as automated diagnostics. By integrating the diagnostics design knowledge with the test station, test confidence is taken to the highest level and, in the event of a UUT failure, rapid identification of the failed component is now embedded in the test station. Today's high tech test systems provide excellent confidence testing; however, the extended time required to troubleshoot and analyze a faulty UUT complicates support logistics and drives up over all support / maintenance and Unit Production Costs (UPC). Repairing today's complex UUTs requires a high skill level to isolate the failure to the root cause component. By employing an advanced UUT diagnostics design methodology which provides an enhanced understanding of the unit's test capability, coupled with the design knowledge of the UUT, the capabilities of an existing test station can be extended to included advanced diagnostics.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131213549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-01DOI: 10.1109/AUTEST.2012.6334542
A. Lowe
With a data awareness culture in place within the organization with data storage, reporting, analysis and real-time SPC, the data infrastructure can easily be recognized as a strategic asset. When customers inquire about test data regarding a problem in the field, it is quickly queried and analyzed in a productive manner. With an SPC system in place, there will be fewer escapes and therefore less returned merchandise to be analyzed. A data infrastructure also provides a vehicle for standardized problem solving. If multiple departments or sites within an organization have a standard database and SPC system implementation, then resources can effectively combine efforts when it comes to data analysis. In an organization with a data awareness culture, everyone knows where the data is, how to get it, and how to use it. This is the strategic implication of a well architected database system. Clearly, the investment in a database implementation will be worth the effort.
{"title":"Data awareness from ATE","authors":"A. Lowe","doi":"10.1109/AUTEST.2012.6334542","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334542","url":null,"abstract":"With a data awareness culture in place within the organization with data storage, reporting, analysis and real-time SPC, the data infrastructure can easily be recognized as a strategic asset. When customers inquire about test data regarding a problem in the field, it is quickly queried and analyzed in a productive manner. With an SPC system in place, there will be fewer escapes and therefore less returned merchandise to be analyzed. A data infrastructure also provides a vehicle for standardized problem solving. If multiple departments or sites within an organization have a standard database and SPC system implementation, then resources can effectively combine efforts when it comes to data analysis. In an organization with a data awareness culture, everyone knows where the data is, how to get it, and how to use it. This is the strategic implication of a well architected database system. Clearly, the investment in a database implementation will be worth the effort.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116902019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-01DOI: 10.1109/AUTEST.2012.6334520
A. Smith, H. Wanigaratne
Many organizations today struggle with getting meaningful insights out of their Test Data. Partly this is due to the complexity of the collection and aggregation of the data, and also partly due to the actual types of data that is recorded at the Test Stations. With some careful planning, the Test Data can be full of rich insights if some standard tags are added to the overall Test Data format.
{"title":"Application of ATML test results and intrastage to facilitate intelligent data analysis","authors":"A. Smith, H. Wanigaratne","doi":"10.1109/AUTEST.2012.6334520","DOIUrl":"https://doi.org/10.1109/AUTEST.2012.6334520","url":null,"abstract":"Many organizations today struggle with getting meaningful insights out of their Test Data. Partly this is due to the complexity of the collection and aggregation of the data, and also partly due to the actual types of data that is recorded at the Test Stations. With some careful planning, the Test Data can be full of rich insights if some standard tags are added to the overall Test Data format.","PeriodicalId":142978,"journal":{"name":"2012 IEEE AUTOTESTCON Proceedings","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115335014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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