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Design for Reliability
Published in Michael Pecht, Handbook of Electronic Package Design, 2018
Reliability engineering is the aspect of the product development process concerned with the operational readiness, successful performance over time, maintenance, and service requirements of systems, subsystems, and parts. The reliability of a product can be established only if reliability is designed in (failure-related design), manufacturing processes and testing are in control, and maintenance procedures are properly established and carried out. Improvement in reliability occurs when reliability information, obtained from test and field data, is utilized to adjust design, manufacturing, and maintenance parameters, thereby reducing or eliminating potential failure causes. Test and field data are obtained from inspection, failure analysis, manufacturing, field service, and customers. Figure 11.1 shows the interaction of reliability tasks within the framework of product development.
Research Methods in Human Factors
Published in Robert W. Proctor, Van Zandt Trisha, Human Factors in Simple and Complex Systems, 2018
Robert W. Proctor, Van Zandt Trisha
Two of the most important concepts in human factors and ergonomics research are those of reliability and validity (Kanis, 2014). Reliability refers to the consistency of measurements. Measurements are said to be reliable if we get similar values when we measure the same thing more than once. Experimental results are reliable if we can replicate them under similar conditions. For example, if you give a test to the same group of people at two different times, the test is said to have high “test-retest” reliability if the scores for each person are similar for the two administrations of the test. Another way to think of reliability is that any measure, call it Xobserved, has two parts. One part is “true” (Xtrue) and the other part is random error. The two parts are added together to give the final measure: Xobserved = Xtrue + error. The larger the true part is relative to the error part, the higher the reliability.
Research and developoment
Published in V. David Hopkin, Human Factors in Air Traffic Control, 2017
Reliability refers to consistency and repeatability, whereas validity depends on whether a measure actually measures what it purports to measure. Reliability can often be established by studying the measure itself, whereas validity usually relies on independent external criteria which themselves are reliable and valid, a requirement that is becoming impractical in complex systems such as air traffic control (Wise et al., 1993). Findings from research in laboratories or using simulations may be neither valid nor reliable in real life. A major contribution is to advise on the reliability and validity of human factors evidence, recommendations, findings and conclusions, and particularly on the applicability of other human factors literature to air traffic control. Some types of evidence, for example, on reach and viewing distances, possess high reliability and validity, whereas others, such as the effects of boredom on safety, have unknown validity and reliability.
Reliability Analysis of Microgrids: Evaluation of Centralized and Decentralized Control Approaches
Published in Electric Power Components and Systems, 2023
Selahattin Garip, Melih Bilgen, Necmi Altin, Saban Ozdemir, Ibrahim Sefa
Reliability refers to the ability of a system or product to perform its intended function without failure, interruption, or error over a predetermined duration, or within a specific timeframe and under specified operating conditions. Reliability can be quantified by various metrics, such as mean time between failures (MTBF), failure rate, and availability. MTBF represents the average time between two consecutive failures of a system or product, while failure rate represents the probability of a failure occurring within a given time period. Availability represents the percentage of time that a system or product is operational and ready to perform its intended function. In engineering and industry, reliability is a critical factor in the design, testing, and production of various systems and products, including electrical systems, mechanical systems, software, and complex machinery. High reliability is often a requirement for mission-critical systems, such as those used in aerospace, defense, transportation, and medical applications, where failure can have severe consequences.
Monitoring reliability under competing risks using field data
Published in Journal of Quality Technology, 2023
Francis G. Pascual, Joseph P. Navelski
Developing quality and reliable products is at the core of a manufacturer’s philosophy because it helps meet product demand and reduces maintenance and warranty costs for the manufacturer. Reliability is particularly important because it is one of the factors that drives product quality, and early detection of an unreliable product can help manufactures mitigate demand shrinkage and high replacement costs. Statistical models, used to describe the reliability of a manufacturing process, combined with real-time field or warranty data can effectively predict when a manufacturing process is out of control. Warranty data can take on many forms, but one of the more important factors a manufacturer tends to, and should keep track of, is the mode by which a product has failed. This data structure is rich in information, and allows manufacturers and statisticians to use competing-risk models to identify features in the process that might be contributing to unexpected product failures.
Modeling social influence from a perspective of shift: an elaborated model
Published in Transportmetrica A: Transport Science, 2022
Xiaofeng Pan, Soora Rasouli, Harry Timmermans
Before including decision makers’ personality traits and social relationship with social network members into the analysis, the reliability and validity of all constructed scales should be established. Reliability indicates the extent to which a set of variables is consistent in what they measure, while validity indicates the extent to which a set of variables correctly represent what they are supposed to (Hair et al. 2010). In other words, reliability is concerned with the consistency of the measures, while validity is related to the accuracy of the measures. The details can be found in Pan, Rasouli, and Timmermans (2019). To summarize, indicators with factor loadings higher than 0.6 were adopted and the results of exploratory and confirmatory factor analyses confirmed good reliability and validity of the constructed scales for personality traits and social relationship.