Reliability tests are commonly used in product design and manufacturing processes to assure the reliability of components, subsystems, and, in some cases, complete systems. Typical responses are time to failure (either in terms of operating time or number of cycle of operation) or strength or other critical material properties. Virtually alllaboratory reliability tests are accelerated (e.g., by testing at an increases cycling rate or at higher-than-usual levels of temperature or voltage) so that information is obtained in a timely manner. The resulting test data are often censored because not all units fail by the end of the test.

"SHRP 2 initiated the L38 project to pilot test products from five of the program’s completed projects. The products support reliability estimation and use based on data analyses, analytical techniques, and decision-making framework. The L38 project has two main objectives: (1) to assist agencies in using travel time reliability as a measure in their business practices and (2) to receive feedback from the project research teams on the applicability and usefulness of the products tested, along with their suggested possible refinements. SHRP 2 selected four teams from California, Minnesota, Florida, and Washington. Project L38C tested elements from Projects L02, L05, L07, and L08. Project L02 identified methods to collect, archive, and integrate required data for reliability estimation and methods for analyzing and visualizing the causes of unreliability based on the collected data. Projects L07 and L08 produced analytical techniques and tools for estimating reliability based on developed models and allowing the estimation of reliability and the impacts on reliability of alternative mitigating strategies. Project L05 provided guidance regarding how to use reliability assessments to support the business processes of transportation agencies. The datasets in this zip file, which is 7.83 MB in size, support of SHRP 2 reliability project L38C, "Pilot testing of SHRP 2 reliability data and analytical products: Florida." The accompanying report can be accessed at the following URL: https://rosap.ntl.bts.gov/view/dot/3609 There are 12 datasets in this zip file, including 2 Microsoft Excel worksheets (XLSX) and 10 Comma Separated Values (CSV) files. The Microsoft Excel worksheets can be opened using the 2010 and 2016 versions of Microsoft Word, the CSV files can be opened using most text editors.

The target numbers for the average duration of power outages for System Average Interruption Duration Index (SAIDI) goals: Prior to 2016: 60.00 minutes; 2016 – 2019: 57.22 minutes; 2020 – 2021: 45.50 minutes; 2022: 57.00 minutes The target numbers for the System Average Interruption Frequency Index (SAIFI) goals or the average number of power outages per customer: Prior to 2018: 0.80; 2018: 0.72; 2019: 0.69 2020 – 2021: 0.57; 2022: 0.72

The target number for the System Average Transmission Line Performance index (SATLPI) or the 12-month rolling average of the number of transmission line faults per 100 miles is 3.0.

The objective of this project was to develop system designs for programs to monitor travel time reliability and to prepare a guidebook that practitioners and others can use to design, build, operate, and maintain such systems. Generally, such travel time reliability monitoring systems will be built on top of existing traffic monitoring systems. The focus of this project was on travel time reliability. The data from the monitoring systems developed in this project – from both public and private sources –included, wherever cost-effective, information on the seven sources of non-recurring congestion. This data was used to construct performance measures or to perform various types of analyses useful for operations management as well as performance measurement, planning, and programming. The datasets in the attached ZIP file support SHRP 2 reliability project L38B, "Pilot testing of SHRP 2 reliability data and analytical products: Minnesota." This report can be accessed via the following URL: https://rosap.ntl.bts.gov/view/dot/3608 This ZIP file package, which is 22.1 MB in size, contains 6 Microsoft Excel spreadsheet files (XLSX). This file package also contains 3 Comma Separated Value files (CSV). The XLSX and CSV files can be opened using Microsoft Excel 2010 and 2016. The CSV files can be opened using most available text editing programs.

The revenue of Reliability with headquarters in the United States amounted to 549.3 million U.S. dollars in 2023. The reported fiscal year ends on December 31.Compared to the earliest depicted value from 2019 this is a total increase by approximately 232.95 million U.S. dollars. The trend from 2019 to 2023 shows, however, that this increase did not happen continuously.

The Washington site used the reliability guide from Project L02, analysis tools for forecasting reliability and estimating impacts from Project L07, Project L08, and Project C11 as well as the guide on reliability performance measures from the Project L05 product. The Washington site focused on the I-5 and I-405 corridors from Lynnwood to Tukwila (approximately 30 miles long for each corridor running through the Puget Sound metropolitan region), and the SR-522 urban arterial near Seattle. The pilot testing demonstrated that the SHRP 2 Reliability data and analytical products clearly addressed the practical challenges that transportation agencies face when monitoring and analyzing travel time reliability. However, most tools require significant improvements at the application level. Project L38D was intended to evaluate a suite of projects to determine their readiness for implementation. Those projects had a logical structure consisting of data collection, analysis, and project prioritization. The datasets in this zip file, which is 90.5 MB in size, are in support of SHRP 2 reliability project L38D, "Pilot testing of SHRP 2 reliability data and analytical products: Washington." The project report can be accessed via the following URL: https://rosap.ntl.bts.gov/view/dot/3610 This zip file contains 20 Comma Separated Values (CSV) files, which can be opened using most text editing programs.

As of 2024, the Latin America was the region with the largest share of organizations with fully operationalized reliability measures worldwide. About 15 percent of the respondents in this industry reported to have fully operationalized at least 50 percent of the listed measures to mitigate reliability risks across the development, deployment, and use of artificial intelligence (AI) — from these, about six percent claim to have fully operationalized all the listed measures. Nevertheless, Europe was the one with the highest overall adoption of AI-related reliability measures by the surveyed organizations, having an average of 2.27 adopted measures.

In some reliability studies, the natural response is measured degradation (either performance degradation or physical/chemical degradation), as opposed to the traditional failure-time reliability data. Examples include light output from LEDs and lasers. crack length, and the amount of wear. Laboratory degradation tests are typically accelerated by increasing a variable like temperature to increase the degradation rate. Before statistical methods had been developed for repeated measured degradation data, it was common practice to wait for enough units to actually fail and then use statistical methods for failure-time data (Device-A in Chapter 18 of SMRD2 is such an example). There are, however, important advantages for direct modeling and analysis of repeated measures degradation data. In particular, it is possible to make reliability inferences with few or no observed failures and the degradation data contain useful information for checking important model assumptions.

The dataset contains raw data from the pilot study samples used for the validity and reliability testing of the Environmental Enrichment Scale Questionnaire (EESQ) and its translated Malay version (EESQ-M).

California Local Reliability Areas.

There is no description for this dataset.

Latin American organizations have by far the lowest concerns regarding reliability risks with AI in 2024. This was in stark contrast to the rest of the world, where 55 percent of respondents said reliability was relevant to their organization.

The total equity of Reliability with headquarters in the United States amounted to -303.3 million U.S. dollars in 2023. The reported fiscal year ends on December 31.Compared to the earliest depicted value from 2019 this is a total decrease by approximately 640.54 million U.S. dollars. The trend from 2019 to 2023 shows, furthermore, that this decrease happened continuously.

The objective of this project was to develop technical relationships between reliability improvement strategies and reliability performance metrics. This project defined reliability, explained the importance of travel time distributions for measuring reliability, and recommended specific reliability performance measures. The research reexamined the contribution of the various causes of nonrecurring congestion on urban freeway sections, however, some attention was also given to rural highways and urban arterials). Numerous actions that can potentially reduce nonrecurring congestion were identified with an indication of their relative importance. Models for predicting nonrecurring congestion were developed using three methods, all based on empirical procedures: The first involved before and after studies; the second was termed a 'data poor' approach and resulted in a parsimonious and easy-to-apply set of models; the third was entitled a 'data rich model' and used cross-section inputs including data on selected factors known to directly affect nonrecurring congestion. An important conclusion of the study is that actions to improve operations, reduce demand, and increase capacity all can improve travel time reliability. The 3 attached zip files contains comma separated value (.csv) files of data to support SHRP 2 report S2-L03-RR-1, Analytical procedures for determining the impacts of reliability mitigation strategies.Zip size is 1.83 MB. Files were accessed in Microsoft Excel 2016. Data will be preserved as is. To view publication see: https://rosap.ntl.bts.gov/view/dot/3605

The GRC uses a combined gearbox testing, modeling, and analysis approach disseminating data and results to the industry and facilitating improvement of gearbox reliability. This test data describes the tests of GRC gearbox 3 in the National Wind Technology Center dynamometer and documents any modifications to the original test plan. It serves as a guide to interpret the publicly released data sets with brief analyses to illustrate the data. TDMS viewer and Solidworks software required to view data files. The National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) was established by the U.S. Department of Energy in 2006; its key goal is to understand the root causes of premature gearbox failures and improve their reliability.

Reliability of information.

The Highway Capacity Manual (HCM) historically has been among the most important reference guides used by transportation professionals seeking a systematic basis for evaluating the capacity, level of service, and performance measures for elements of the surface transportation system, particularly highways but also other modes. The objective of this project was to determine how data and information on the impacts of differing causes of nonrecurrent congestion (incidents, weather, work zones, special events, etc.) in the context of highway capacity can be incorporated into the performance measure estimation procedures contained in the HCM. The methodologies contained in the HCM for predicting delay, speed, queuing, and other performance measures for alternative highway designs are not currently sensitive to traffic management techniques and other operation/design measures for reducing nonrecurrent congestion. A further objective was to develop methodologies to predict travel time reliability on selected types of facilities and within corridors. This project developed new analytical procedures and prepared chapters about freeway facilities and urban streets for potential incorporation of travel-time reliability into the HCM. The methods are embodied in two computational engines, and a final report documents the research. This zip file contains comma separated value (.csv) files of data to support SHRP 2 report S2-L08-RW-1, Incorporating travel time reliability into the Highway Capacity Manual. Zip size is 1.83 MB. Files were accessed in Microsoft Excel 2016. Data will be preserved as is. To view publication see: https://rosap.ntl.bts.gov/view/dot/3606

rosbag2_2022_12_13-14_34_28

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