Pub Date : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984769
Tyler Cody, P. Beling, Laura Freeman
Modern automated penetration testing uses rule-based procedures and model-checking concepts to search through all possible attacks on network models and identify those that violate some correctness or security property by generating an attack graph. By generating all possible attacks, modern, top-down approaches inherently do not isolate the few attacks that matter the most. This weakness is exacerbated in future network settings like 5G and Internet of Things (IoT) settings where networks are expected to have thousands of hosts (or more) and evolve over time. This has created a perception that the attack graph concept itself is inadequate, in turn hindering the automation of cyber testing. Recent research re-positions automated attack graph generation as a best practice in cyber defense by applying deep reinforcement learning (RL). While recent research into penetration testing with RL has seen a rapid growth in interest, a clear concept of operational use has not been defined. We define and provide formalism for the concept of whole campaign emulation (WCE). We present WCE as both a challenge problem and a framework for automating cyber T&E with RL. This manuscript captures an RL-oriented perspective on the past, present, and future of attack graph generation, and serves as a primer from researchers and practitioners alike. With WCE, organizations from small businesses to nation-states can feasibly institute continuous cyber T&E with low test costs and low disruption to operations.
{"title":"Towards Continuous Cyber Testing with Reinforcement Learning for Whole Campaign Emulation","authors":"Tyler Cody, P. Beling, Laura Freeman","doi":"10.1109/AUTOTESTCON47462.2022.9984769","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984769","url":null,"abstract":"Modern automated penetration testing uses rule-based procedures and model-checking concepts to search through all possible attacks on network models and identify those that violate some correctness or security property by generating an attack graph. By generating all possible attacks, modern, top-down approaches inherently do not isolate the few attacks that matter the most. This weakness is exacerbated in future network settings like 5G and Internet of Things (IoT) settings where networks are expected to have thousands of hosts (or more) and evolve over time. This has created a perception that the attack graph concept itself is inadequate, in turn hindering the automation of cyber testing. Recent research re-positions automated attack graph generation as a best practice in cyber defense by applying deep reinforcement learning (RL). While recent research into penetration testing with RL has seen a rapid growth in interest, a clear concept of operational use has not been defined. We define and provide formalism for the concept of whole campaign emulation (WCE). We present WCE as both a challenge problem and a framework for automating cyber T&E with RL. This manuscript captures an RL-oriented perspective on the past, present, and future of attack graph generation, and serves as a primer from researchers and practitioners alike. With WCE, organizations from small businesses to nation-states can feasibly institute continuous cyber T&E with low test costs and low disruption to operations.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114516464","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}
In the field of automatic test systems, direct digital synthesis (DDS) technology plays a crucial role with features such as fast frequency switching speed, high-frequency resolution, and flexible waveforms. However, the timing resolution of the pulse waveform generated by DDS technology is limited by the storage depth of waveform memory and sampling rate. DDS generates a maximum 1 clock cycle jitter in the pulse waveform as the frequency tune word (FTW) changes driven by the sampling clock, and the pulse width modulation (PWM) of the pulse waveform is not possible with DDS technology. In this paper, a parallel pulse waveform synthesis method based on real-time computation is proposed. The pulse waveform generated by this method has a timing resolution that far exceeds the sampling period including rising time resolution, falling time resolution, pulse width resolution, and delay resolution. Since the pulse parameters such as rising time, falling time, and pulse width can be independently adjusted with phase continuity, and the waveform samples are generated by real-time computation, the method can easily implement PWM and various modulations. The waveform samples computed in real-time correspond precisely to their theoretical phases with extremely low phase truncation error, thus jitter is greatly reduced and the timing resolution can be significantly improved. In this paper, based on the real-time computation of waveform samples, the sampling rate is increased eight times by parallelizing the computation. Each computing channel is run at 156.25 MHz, and the sampling rate of 1.25 GSPS waveform samples is achieved by running in parallel with eight channels. Finally, the pulse waveform is generated with a timing resolution of 0.2 ps, which theoretically requires a sampling rate of 5 TSPS to achieve.
{"title":"Design and implementation of a ultra-high timing resolution pulse generator based on real-time computation","authors":"Hanglin Liu, Hongliang Chen, Zaiming Fu, Shirui Qi, Yindong Xiao, Houjun Wang","doi":"10.1109/AUTOTESTCON47462.2022.9984792","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984792","url":null,"abstract":"In the field of automatic test systems, direct digital synthesis (DDS) technology plays a crucial role with features such as fast frequency switching speed, high-frequency resolution, and flexible waveforms. However, the timing resolution of the pulse waveform generated by DDS technology is limited by the storage depth of waveform memory and sampling rate. DDS generates a maximum 1 clock cycle jitter in the pulse waveform as the frequency tune word (FTW) changes driven by the sampling clock, and the pulse width modulation (PWM) of the pulse waveform is not possible with DDS technology. In this paper, a parallel pulse waveform synthesis method based on real-time computation is proposed. The pulse waveform generated by this method has a timing resolution that far exceeds the sampling period including rising time resolution, falling time resolution, pulse width resolution, and delay resolution. Since the pulse parameters such as rising time, falling time, and pulse width can be independently adjusted with phase continuity, and the waveform samples are generated by real-time computation, the method can easily implement PWM and various modulations. The waveform samples computed in real-time correspond precisely to their theoretical phases with extremely low phase truncation error, thus jitter is greatly reduced and the timing resolution can be significantly improved. In this paper, based on the real-time computation of waveform samples, the sampling rate is increased eight times by parallelizing the computation. Each computing channel is run at 156.25 MHz, and the sampling rate of 1.25 GSPS waveform samples is achieved by running in parallel with eight channels. Finally, the pulse waveform is generated with a timing resolution of 0.2 ps, which theoretically requires a sampling rate of 5 TSPS to achieve.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129183679","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984798
M. Dziuk, Lewis Edinburgh, Shawn Reynolds, Jim Rousseau, Jason Boots Winn
Department of Defense “Maintenance of the Future” capabilities will necessarily nest under the digital transformation banner and require near-term innovative solutions. The required attributes, while essentially common across the Services, will push long-standing, traditional maintenance facilities and practices out of comfort zones. Genuine transformation to agile software/hardware delivery, digital twins, information assured/resilient network architectures, 5G, Internet of Things (IoT), and Modular Open Systems Architecture (MOSA) represent both the challenges and opportunities to harness Maintenance for the Future transformation - easier said than done. Maintainers and facilities need tomorrow's answers, today. Fortunately, many are available and adaptable for immediate integration. For example, Air Force Material Command and the Air Force Sustainment Center have shared with industry various overviews of their image for Flightline-of-the-Future and Digital Depots concepts, outlining that the government is in the process of data gathering to shape requirements as well as understand the cutting-edge capabilities of industry. The purpose of this paper is to provide an overview of capabilities and solutions for what the Flightline of the Future can be and how continuity can be maintained between all maintenance levels (Organizational, Intermediate, and Depot). This paper also explores approaches for Next Generation Test Systems by highlighting current solutions and goals for the future. We focus on breaking from legacy implementations of backplanes and instrumentation as well as new capabilities for ensuring cybersecurity, streamlined processing of Authority to Operate (ATO), MOSA frameworks for interfacing to Industrial Internet of Things (IIoT), and potential schemas for advanced data analysis supporting logistical and predictive methodologies.
{"title":"Solution Approaches from Industry for Flightline of the Future and Next Generation Test Systems","authors":"M. Dziuk, Lewis Edinburgh, Shawn Reynolds, Jim Rousseau, Jason Boots Winn","doi":"10.1109/AUTOTESTCON47462.2022.9984798","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984798","url":null,"abstract":"Department of Defense “Maintenance of the Future” capabilities will necessarily nest under the digital transformation banner and require near-term innovative solutions. The required attributes, while essentially common across the Services, will push long-standing, traditional maintenance facilities and practices out of comfort zones. Genuine transformation to agile software/hardware delivery, digital twins, information assured/resilient network architectures, 5G, Internet of Things (IoT), and Modular Open Systems Architecture (MOSA) represent both the challenges and opportunities to harness Maintenance for the Future transformation - easier said than done. Maintainers and facilities need tomorrow's answers, today. Fortunately, many are available and adaptable for immediate integration. For example, Air Force Material Command and the Air Force Sustainment Center have shared with industry various overviews of their image for Flightline-of-the-Future and Digital Depots concepts, outlining that the government is in the process of data gathering to shape requirements as well as understand the cutting-edge capabilities of industry. The purpose of this paper is to provide an overview of capabilities and solutions for what the Flightline of the Future can be and how continuity can be maintained between all maintenance levels (Organizational, Intermediate, and Depot). This paper also explores approaches for Next Generation Test Systems by highlighting current solutions and goals for the future. We focus on breaking from legacy implementations of backplanes and instrumentation as well as new capabilities for ensuring cybersecurity, streamlined processing of Authority to Operate (ATO), MOSA frameworks for interfacing to Industrial Internet of Things (IIoT), and potential schemas for advanced data analysis supporting logistical and predictive methodologies.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128265968","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984781
Stephen T. Sargeant, A. Wells
Organizational Level (O-Level) Maintenance personnel face tremendous pressure to maintain the mission readiness of aircraft and weapons systems in some of the most inhospitable conditions imaginable. Whether deployed on an aircraft carrier in the middle of the Atlantic, or on a remote airbase in Alaska, maintainers are only as effective as their training and test equipment. This can be especially challenging for the armament maintainer as new weapons systems and munitions are developed and fielded, and commonly utilized alongside legacy munitions. Test equipment must not only address the legacy test requirements, but must include new capabilities; this results in the proliferation of multiple types and generations of test equipment that impacts test execution performance, training, logistics and ultimately aircraft mission readiness. O-Level armament maintenance includes scheduled and unscheduled activities; scheduled test occurs after installation or scheduled maintenance, and unscheduled test occurs in support of fault analysis and troubleshooting. For this reason, the USAF has employed two versions of O-Level testers for most fighter aircraft. The first is a simple reliability tester most often known as the Armament Circuit Preload Test Set (ACPTS), and the second is an advanced tester (COLT, SST, 198, etc.) used for functional checkouts. Furthermore, O-Level armament support for the F-16 may require up to five different testers (5060, SST, FIST, MBFI and Viper), with each tester being employed for a different function or mission. Clearly this poses significant training and proficiency challenges for the maintainer, but also impacts logistics as any deployment must also include each of these test sets along with associated cable assemblies. This paper will explore the need for a universal O-Level armament test set that combines all O-Level armament tests into one test set, and identify the reliability and functional test requirements that must be addressed to support legacy as well as new and emerging aircraft armament and weapons.
{"title":"Organizational Level Armament Test Reimagined","authors":"Stephen T. Sargeant, A. Wells","doi":"10.1109/AUTOTESTCON47462.2022.9984781","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984781","url":null,"abstract":"Organizational Level (O-Level) Maintenance personnel face tremendous pressure to maintain the mission readiness of aircraft and weapons systems in some of the most inhospitable conditions imaginable. Whether deployed on an aircraft carrier in the middle of the Atlantic, or on a remote airbase in Alaska, maintainers are only as effective as their training and test equipment. This can be especially challenging for the armament maintainer as new weapons systems and munitions are developed and fielded, and commonly utilized alongside legacy munitions. Test equipment must not only address the legacy test requirements, but must include new capabilities; this results in the proliferation of multiple types and generations of test equipment that impacts test execution performance, training, logistics and ultimately aircraft mission readiness. O-Level armament maintenance includes scheduled and unscheduled activities; scheduled test occurs after installation or scheduled maintenance, and unscheduled test occurs in support of fault analysis and troubleshooting. For this reason, the USAF has employed two versions of O-Level testers for most fighter aircraft. The first is a simple reliability tester most often known as the Armament Circuit Preload Test Set (ACPTS), and the second is an advanced tester (COLT, SST, 198, etc.) used for functional checkouts. Furthermore, O-Level armament support for the F-16 may require up to five different testers (5060, SST, FIST, MBFI and Viper), with each tester being employed for a different function or mission. Clearly this poses significant training and proficiency challenges for the maintainer, but also impacts logistics as any deployment must also include each of these test sets along with associated cable assemblies. This paper will explore the need for a universal O-Level armament test set that combines all O-Level armament tests into one test set, and identify the reliability and functional test requirements that must be addressed to support legacy as well as new and emerging aircraft armament and weapons.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121573215","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984735
M. Don, Nathan L. Schomer, Mitchell Grabner, Cory Miller, Jonathan M. Hallameyer
The DEVCOM Army Research Laboratory has redesigned its Multi-functional Instrumentation and Data Ac-quisition System (MIDAS) to support an embedded Linux-based flight controller for its smart munitions research. This includes field-programmable gate array development of a serial peripheral interface between the sensor board and flight controller, integration of three new digital sensors using a soft-core processor, and the design of a custom Linux software stack. This new version of MIDAS has been successfully used in several flight experiments, and will continue to support future smart munitions research and development.
{"title":"An Instrumentation System for an Embedded Linux-Based Flight Controller","authors":"M. Don, Nathan L. Schomer, Mitchell Grabner, Cory Miller, Jonathan M. Hallameyer","doi":"10.1109/AUTOTESTCON47462.2022.9984735","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984735","url":null,"abstract":"The DEVCOM Army Research Laboratory has redesigned its Multi-functional Instrumentation and Data Ac-quisition System (MIDAS) to support an embedded Linux-based flight controller for its smart munitions research. This includes field-programmable gate array development of a serial peripheral interface between the sensor board and flight controller, integration of three new digital sensors using a soft-core processor, and the design of a custom Linux software stack. This new version of MIDAS has been successfully used in several flight experiments, and will continue to support future smart munitions research and development.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121674603","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984764
Yan Rodriguez Ramirez
The design of modern Automated Test Equipment (ATE) is now being enabled to support the IEEE standards for ATML. These standards are IEEE 1671.1 (Test Description) and 1641 (Signal and Test Definition). The critical task is now defining the processes to develop and support the Test Program Sets to ensure they follow the standards. This is feasible by using existing commercial tools that allow creating System Model Language (SysML®) and generating ATML Test Description (ATML 1671.1) and Signals (ATML 1641) that define the test and signals expected to be present in the TPS. Conversion tools are then used to generate NI TestStand™ sequences based on the test and signals defined in the ATML Test Description. Once developed, the TPS must be validated to submit or load on the designated ATE. Using this process, we recommend following a TPS style guide to fully benefit the capabilities and features of the ATE Test Executive. The objective of this paper is to show the process and steps taken to create and ATML compliant TPS with the proper validation for submitting it to a designated ATE platform.
现代自动化测试设备(ATE)的设计现在可以支持IEEE的ATML标准。这些标准是IEEE 1671.1(测试描述)和1641(信号和测试定义)。现在的关键任务是定义开发和支持测试程序集的过程，以确保它们遵循标准。这是可行的，通过使用现有的商业工具，允许创建系统模型语言(SysML®)和生成ATML测试描述(ATML 1671.1)和信号(ATML 1641)，定义测试和信号预计将出现在TPS。然后使用转换工具根据ATML测试描述中定义的测试和信号生成NI TestStand™序列。一旦开发完成，TPS必须经过验证才能在指定的ATE上提交或加载。使用此过程，我们建议遵循TPS风格指南，以充分利用ATE Test Executive的功能和特性。本文的目的是展示创建和兼容ATML的TPS的过程和步骤，并将其提交到指定的ATE平台进行适当的验证。
{"title":"Lockheed Martin ATE's Support Automatic Test-Markup Language (ATML) 1671.1 and 1641","authors":"Yan Rodriguez Ramirez","doi":"10.1109/AUTOTESTCON47462.2022.9984764","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984764","url":null,"abstract":"The design of modern Automated Test Equipment (ATE) is now being enabled to support the IEEE standards for ATML. These standards are IEEE 1671.1 (Test Description) and 1641 (Signal and Test Definition). The critical task is now defining the processes to develop and support the Test Program Sets to ensure they follow the standards. This is feasible by using existing commercial tools that allow creating System Model Language (SysML®) and generating ATML Test Description (ATML 1671.1) and Signals (ATML 1641) that define the test and signals expected to be present in the TPS. Conversion tools are then used to generate NI TestStand™ sequences based on the test and signals defined in the ATML Test Description. Once developed, the TPS must be validated to submit or load on the designated ATE. Using this process, we recommend following a TPS style guide to fully benefit the capabilities and features of the ATE Test Executive. The objective of this paper is to show the process and steps taken to create and ATML compliant TPS with the proper validation for submitting it to a designated ATE platform.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124976630","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984785
M. J. Smith, W. J. Headrick
The Performance Based Logistics (PBL) approach to platform sustainment is greatly enhanced when informed by high quality information about the current state of critical fleet assets, and a reliable estimate of anticipated future needs. Aircraft platform sustainment stakeholders have long used information from data analytic software to inform PBL teams and make more efficient and cost optimized decisions on operations, maintenance, and supply chain actions. These analytics consume platform operational data sources, and fleet asset parametric data to provide a wide range of information including fault diagnostics, failure prognostics, and part order demand forecasts. The branches of the U.S. Armed Forces operate and maintain a “fleet” of Automated Test Equipment (ATE) used to evaluate and diagnose critical Line Replaceable Units (LRUs) removed across a wide range of vehicle platforms. These critical test platforms generate comprehensive log files for test procedures including: self-diagnostic tests, calibration, and LRU Unit Under Test (UUT) evaluations. Generally speaking, this data is not finding its way back to a central repository where it can be analyzed, processed by automated analytic processes, and used for platform analysis and decision making. This paper describes a design for Automated Test Equipment test log analytics to provide enhanced information to test platform Performance Based Logistics. Examples are provided to show how results for a fleet of test instruments can be aggregated into central repository appropriate for human and machine learning processes. When a representative dataset is compiled, models can be trained achieve analytics goals of increasing sophistication from simple anomaly detection, through fault isolation diagnostics, to projections of future maintenance and supply chain needs. Also covered is how these test log based analytics can be combined with information extracted from other operational data sources including UUT test findings, test station maintenance logs, and part orders to provide additional test platform benefits. Finally, the implementation of test log analytics has potential benefits to the UUT platforms as well. This includes providing a path to accelerated component diagnostics through smart Test Program Sets (TPSs) that self-optimize based upon an understanding of historic test results.
{"title":"Automated Test Equipment Data Analytics in a PBL Environment","authors":"M. J. Smith, W. J. Headrick","doi":"10.1109/AUTOTESTCON47462.2022.9984785","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984785","url":null,"abstract":"The Performance Based Logistics (PBL) approach to platform sustainment is greatly enhanced when informed by high quality information about the current state of critical fleet assets, and a reliable estimate of anticipated future needs. Aircraft platform sustainment stakeholders have long used information from data analytic software to inform PBL teams and make more efficient and cost optimized decisions on operations, maintenance, and supply chain actions. These analytics consume platform operational data sources, and fleet asset parametric data to provide a wide range of information including fault diagnostics, failure prognostics, and part order demand forecasts. The branches of the U.S. Armed Forces operate and maintain a “fleet” of Automated Test Equipment (ATE) used to evaluate and diagnose critical Line Replaceable Units (LRUs) removed across a wide range of vehicle platforms. These critical test platforms generate comprehensive log files for test procedures including: self-diagnostic tests, calibration, and LRU Unit Under Test (UUT) evaluations. Generally speaking, this data is not finding its way back to a central repository where it can be analyzed, processed by automated analytic processes, and used for platform analysis and decision making. This paper describes a design for Automated Test Equipment test log analytics to provide enhanced information to test platform Performance Based Logistics. Examples are provided to show how results for a fleet of test instruments can be aggregated into central repository appropriate for human and machine learning processes. When a representative dataset is compiled, models can be trained achieve analytics goals of increasing sophistication from simple anomaly detection, through fault isolation diagnostics, to projections of future maintenance and supply chain needs. Also covered is how these test log based analytics can be combined with information extracted from other operational data sources including UUT test findings, test station maintenance logs, and part orders to provide additional test platform benefits. Finally, the implementation of test log analytics has potential benefits to the UUT platforms as well. This includes providing a path to accelerated component diagnostics through smart Test Program Sets (TPSs) that self-optimize based upon an understanding of historic test results.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117124774","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984774
Vi T Weaver, Juan E Ramos
Test equipment used to support engineering design development typically differs from the test equipment used to perform acceptance testing in a production factory. Because the timeframe in which engineering and production test equipment are needed during a product lifecycle is staggered, a program will develop two sets of test equipment for a single product. The primary driver for this strategy results from the long development cycles typically required of production test equipment or Special Test Equipment (STE). This drives the product design engineers to develop their own test benches, or lash-up equipment, so that they can begin integrating and testing their hardware as soon as it arrives. However, what if the barrier for the long STE development cycle were removed? What if a program could deliver test equipment within a 10-month timeframe, from when detailed physical block diagrams and requirements for the product were available to when the test equipment was built and ready to be integrated with the Unit Under Test (UUT)? With the right planning and test strategy, the need for unique engineering test benches would be eliminated. This paper explores the strategy for developing a single STE, which can be used throughout the entire life of a program from development to design verification to production. Additionally, the paper explores the methodology for implementing a 10-month STE development cycle through the use of a common core test capability, composable test capabilities for product unique capabilities, and product artifacts required to interface the test equipment to the product.
{"title":"From Design Development to Production, One STE to Test Them All","authors":"Vi T Weaver, Juan E Ramos","doi":"10.1109/AUTOTESTCON47462.2022.9984774","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984774","url":null,"abstract":"Test equipment used to support engineering design development typically differs from the test equipment used to perform acceptance testing in a production factory. Because the timeframe in which engineering and production test equipment are needed during a product lifecycle is staggered, a program will develop two sets of test equipment for a single product. The primary driver for this strategy results from the long development cycles typically required of production test equipment or Special Test Equipment (STE). This drives the product design engineers to develop their own test benches, or lash-up equipment, so that they can begin integrating and testing their hardware as soon as it arrives. However, what if the barrier for the long STE development cycle were removed? What if a program could deliver test equipment within a 10-month timeframe, from when detailed physical block diagrams and requirements for the product were available to when the test equipment was built and ready to be integrated with the Unit Under Test (UUT)? With the right planning and test strategy, the need for unique engineering test benches would be eliminated. This paper explores the strategy for developing a single STE, which can be used throughout the entire life of a program from development to design verification to production. Additionally, the paper explores the methodology for implementing a 10-month STE development cycle through the use of a common core test capability, composable test capabilities for product unique capabilities, and product artifacts required to interface the test equipment to the product.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124836198","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984731
C. Sparr, Robert A. Fox, Ross Myers, Richard G. Lawrence
The 5th generation of United States Navy and Marine Corps aircraft have Electrical Power System test requirements that far exceed the power capability of power supplies utilized in the Navy's current suite of Intermediate Level Automatic Test Systems (ATS). The Navy's latest ATS, the electronic Consolidated Support System (eCASS), will deploy on thirteen aircraft carriers, eleven amphibious assault ships, and several shore sites. This paper will focus on the hardware and software challenges of integrating a 50 kW DC power supply and a 25 kW DC power supply into eCASS using existing calibration standards and maintenance procedures while allowing dynamic ranges of capability if a component is not available. Power supply paralleling and automated reconfiguration after power supply failures are some of the methods employed to overcome the hardware and software challenges. Addition of the power supplies also requires integration of new environmental monitoring and power subsystem control hardware that interfaces with the existing eCASS power subsystem. Safe and responsive control of the additional power delivery devices is important to ensure operator and facility integration and safety. The allowable heat generated from the ATS augmentation is limited by facility HVAC capacity to ensure the shipboard equipment remains reliable and the ATS operator comfortable. The existing power control unit software of eCASS is expanded on to support new environmental monitoring infrastructure.
{"title":"Test system constraints with emerging Avionics power requirements","authors":"C. Sparr, Robert A. Fox, Ross Myers, Richard G. Lawrence","doi":"10.1109/AUTOTESTCON47462.2022.9984731","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984731","url":null,"abstract":"The 5th generation of United States Navy and Marine Corps aircraft have Electrical Power System test requirements that far exceed the power capability of power supplies utilized in the Navy's current suite of Intermediate Level Automatic Test Systems (ATS). The Navy's latest ATS, the electronic Consolidated Support System (eCASS), will deploy on thirteen aircraft carriers, eleven amphibious assault ships, and several shore sites. This paper will focus on the hardware and software challenges of integrating a 50 kW DC power supply and a 25 kW DC power supply into eCASS using existing calibration standards and maintenance procedures while allowing dynamic ranges of capability if a component is not available. Power supply paralleling and automated reconfiguration after power supply failures are some of the methods employed to overcome the hardware and software challenges. Addition of the power supplies also requires integration of new environmental monitoring and power subsystem control hardware that interfaces with the existing eCASS power subsystem. Safe and responsive control of the additional power delivery devices is important to ensure operator and facility integration and safety. The allowable heat generated from the ATS augmentation is limited by facility HVAC capacity to ensure the shipboard equipment remains reliable and the ATS operator comfortable. The existing power control unit software of eCASS is expanded on to support new environmental monitoring infrastructure.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126226169","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 : 2022-08-29DOI: 10.1109/AUTOTESTCON47462.2022.9984772
Kaleb S. Romero, Jared J. Boyden, W. J. Headrick
Automatic Test Equipment (ATE) have been key in the laboratory testing, calibration, and maintenance of Unit Under Test (UUT) and Line Replaceable Components (LRC), maintaining a high standard in the sustainment of complex systems. In a wide market full of unique capabilities, spanning from legacy systems to cutting-edge technologies, it only makes sense to evolve the ATE world adopting a modular architecture from inception to deployment. A modular mentality applied to every aspect of a system design, shifts away from a rigid perspective and towards a flexible environment where customer ideas and goals can thrive. From utilizing AGILE strategies in execution of design and documentation, taking “vertical slices” on complex designs, utilizing Model-Based Systems Engineering to derive system requirements, using collaborative, cloud-based tools to maximize productivity and shorten program-execution schedules, developing full kit-based solutions, to the virtualization of the ATE design, test and manufacturing plans; All in support of a product that offers confidence during design and execution, maximizes future upgradeability, obsolescence management and field-sustainment, while minimizing non-recurring costs experienced on a traditional, fixed, waterfall ATE design environment. This paper will describe how Digital Transformation in a modular test system makes this possible and enables customers to achieve and maintain success for years to come.
{"title":"Digital Transformation for Automated Test Systems","authors":"Kaleb S. Romero, Jared J. Boyden, W. J. Headrick","doi":"10.1109/AUTOTESTCON47462.2022.9984772","DOIUrl":"https://doi.org/10.1109/AUTOTESTCON47462.2022.9984772","url":null,"abstract":"Automatic Test Equipment (ATE) have been key in the laboratory testing, calibration, and maintenance of Unit Under Test (UUT) and Line Replaceable Components (LRC), maintaining a high standard in the sustainment of complex systems. In a wide market full of unique capabilities, spanning from legacy systems to cutting-edge technologies, it only makes sense to evolve the ATE world adopting a modular architecture from inception to deployment. A modular mentality applied to every aspect of a system design, shifts away from a rigid perspective and towards a flexible environment where customer ideas and goals can thrive. From utilizing AGILE strategies in execution of design and documentation, taking “vertical slices” on complex designs, utilizing Model-Based Systems Engineering to derive system requirements, using collaborative, cloud-based tools to maximize productivity and shorten program-execution schedules, developing full kit-based solutions, to the virtualization of the ATE design, test and manufacturing plans; All in support of a product that offers confidence during design and execution, maximizes future upgradeability, obsolescence management and field-sustainment, while minimizing non-recurring costs experienced on a traditional, fixed, waterfall ATE design environment. This paper will describe how Digital Transformation in a modular test system makes this possible and enables customers to achieve and maintain success for years to come.","PeriodicalId":298798,"journal":{"name":"2022 IEEE AUTOTESTCON","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116045769","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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