When these are lumped together, there is a “randomizing” effect, which makes the failures appear to lack any time dependency. Simple parallel system – the system reliability is increased to 99% due to the redundancy. β = Weibull shape parameter from plot. This is the point in time at which 10% of a population of bearings should be expected to fail (90% survival rate). measure of central tendency, measures of dispersion and variability, confidence intervals, etc.). It should be noted that when the β equals 1.0, the Weibull distribution takes the form of the exponential distribution on which it is based. Capability – A measure of the ability of an item to achieve mission objectives given the conditions during the mission. This article will provide an introduction to the most basic reliability engineering methods that are applicable to the plant engineer that is interested in production reliability assurance. Reliability engineering deals with the longevity and dependability of parts, products and systems. Most industrial machines spend most of their lives in the constant failure rate, so it is widely applicable. Where: Increasingly, managers and engineers who are responsible for manufacturing and other industrial pursuits are incorporating a reliability focus into their strategic and tactical plans and initiatives. Once the system works through its run-in period, which can take minutes, hours, days, weeks, months or years, depending upon the system type, the system enters a different risk pattern. e = Base of the natural logarithms (2.718281828) k = The maximum allowable number of failures If your interest in reliability engineering methods is high, I encourage you to pursue professional certification by the American Society for Quality as a reliability engineer (CRE). Where: Failure mode – The consequence of the mechanism through which the failure occurs, i.e. Figure 6. BASIC QUALITY CONCEPTS . Where: This equation is somewhat more complicated. Where: Reliability Engineering in the development process is the discipline of quantifying a product’s reliability requirements, while ensuring that practices are in place to design in reliability, and verifying that reliability requirements are met through design analysis and testing. There are some shortcut methods for calculating parallel system reliability when all subsystems have the same estimated reliability. Figure 4. An important concept to plant reliability engineers is the concept of r/n systems. The specific knowledge required to be successful involves many fields of science and engineering with emphasis on those topics related to your system or product. This may translate to higher prices but also higher value for the consumer. Both are published by the ASQ Press. n = The total number of units in the system The computations are the same. Politechniki 1, 00-661 Warsaw, Poland January 2018 Corresponding author: S. A. Livingston, E-mail: slivingston@ets.org. Reliability Engineering Basic Concepts and Applications in ICT. Mission reliability – The ability of an item to perform its required functions for the duration of specified mission profile. More and more, these methods are being employed to assure the production reliability of manufacturing plants and equipment – often as an enabler to lean manufacturing. Figure 8. The quantitative aspects of reliability engineering may, on the surface, seem complicated and daunting. The Much-maligned ‘Bathtub’ Curve. θ = Estimated MTBF/MTTF A basic background in Probability and basic calculus will come handy, but if that’s not the case, then ignoring is always an option. Reliability Engineering presents an integrated approach to the design, engineering, and management of reliability activities throughout the life cycle of a product, including concept, research and development, design, manufacturing, assembly, sales, and service. Surprisingly, despite the versatility of the Gaussian distribution in modeling probabilities for phenomenon ranging from standardized test scores to the birth weights of babies, it is not the dominant distribution employed in reliability engineering. The block diagram for a simple two component parallel system is shown in Figure 10. More often, systems contain parallel and serial subcomponents as depicted in Figure 11. The second line exhibits a beta shape of 3.0, suggesting that the risk of failure increases as a function of time. It is by no means a comprehensive survey of reliability engineering methods, nor is it in any way new or unconventional. Figure 12. Another very basic concept is the mean time between/to failure (MTBF/MTTF). While the origins of its demand are ancient, reliability engineering as a technical discipline truly flourished along with the growth of commercial aviation following World War II. If Subsystem A is not operating, the system is down regardless of the condition of Subsystem B (Figure 9). (2018). The simple parallel system in our example with two components in parallel, each having a reliability of 0.90, has a total system reliability of 1 – (0.1 X 0.1) = 0.99. In our pulverizer example, assuming a subcomponent reliability of 0.90, the equation works out as a summation of the following: But once you understand the mechanics of the formulas, the math is really quite simple. Suggested citation: Livingston, S. A. e = Base of the natural logarithms (2.718281828) However, as the population declines as a result of failure, the actual number of mathematically estimated failures decreases as a function of the declining population. Reliability as a function of time is discussed, along with systems modeling, predicting and estimating reliability, and quality assurance. Reliability Engineering Basic Concepts and Applications in ICT. It should be made clear that this paper is a brief introduction to reliability methods. Failure rate – The total number of failures within an item population, divided by the total number of life units expended by that population, during a particular measurement interval under stated conditions. λ = Failure rate (1/MTBF, or 1/MTTF), In our electric motor example, the actual likelihood of failure at three years is calculated as follows: Most important, spend time learning how to apply reliability engineering methods to plant reliability problems. Reliability engineering is an engineering discipline for applying scientific know-how to a component, product, plant, or process in order to ensure that it performs its intended function, without failure, for the required time duration in a specified environment. In the series system, the ability to employ Subsystem B depends upon the operating state of Subsystem A. Type of course: Lecture Level of course: Bachelor . Basic Concepts of Reliability Reliability is a broad concept. The origins of contemporary reliability engineering can be traced to World War II. Figure 10. Not dependent. (t) Parallel Systems More poignantly, it is about controlling risk. Bernowski, K (1997) “Safety in the Skies,” Quality Progress, January. (2) The probability that an item can perform its intended function for a specified interval under stated conditions. θ = Mean time between/to failure Failure, random – Failure whose occurrence is predictable only in the probabilistic or statistical sense. A great industrial example is coal pulverizers in an electric power generating plant. For redundant items, this is the definition of mission reliability. It became rapidly apparent to managers of aviation industry companies that crashes are bad for business. Basic Reliability is an invaluable resource for anyone who wants to work in Reliability Engineering or has a project that has to be completed with the principles of Reliability.Author Nicholas Summerville brings over 15 years of Reliability, Quality, and Safety Engineering to light in this easy to understand book. Site Reliability Engineering — In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of … Rs = System reliability given the actual number of failures (r) is less than or equal the maximum allowable (k) However, engineers must be particularly clever in their application of the methods. Despite its limitations in modeling the failure rates of typical industrial machines, the bathtub curve is a useful tool for explaining the basic concepts of reliability engineering. p = The probability of survival, or the subcomponent reliability for a given time (t). Your email address will not be published. In our previously discussed example of electric motors, we previously assumed the exponential distribution. For instance, a unit has four pulverizers and the unit requires that three of the four be operable to run at the unit’s full load (see Figure 12). r out of n Systems (r/n Systems) This graphic visually illustrates the concept of increasing risk vs. time (β = 0.5), constant risk vs. time (β = 1.0) and increasing risk vs. time (β = 5). The treatment of failure data is given in the last … e = Base of the natural logarithms (2.718281828) For smaller motors that are considered disposable, we would state the measure of central tendency as MTTF. Most machines spend their lives in the early life, or infant mortality, and/or the constant failure rate regions of the bathtub curve. (t). Corrective maintenance can include any or all of the following steps: localization, isolation, disassembly, interchange, reassembly, alignment and checkout. While it is called a distribution, it is actually a tool that enables the reliability engineer to first characterize the probability density function (failure frequency distribution) of a set of failure data to characterize the failures as early life, constant (exponential) or wear out (Gaussian or log normal) by plotting time to failure data on a special plotting paper with the log of the times/cycles/miles to failure plotted a log scaled X-axis versus the cumulative percent of the population represented by each failure on a log-log scaled Y-axis (Figure 5). θ = Estimated MTBF/MTTF By continuing, you consent to the use of cookies. We’ve come to accept that as the objective life for a bearing when perhaps we should set our sights on the L63.22 point, indicating that our bearings are lasting, on average, to projected MTBF – assuming, of course, that the bearings follow the exponential distribution. The Noria, for instance, is an ancient pump thought to be the world’s first sophisticated machine. These systems require that r units from a total population in n be available for use. Site reliability engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems. It is common for reliability engineers to plot, for example, one curve representing the shape parameter during run in and another curve to represent the constant or gradually increasing failure rate. Where: Used properly, quantitative reliability engineering tools and methods enable the plant reliability engineering to more effectively apply the frameworks provided by RCM, RCA, etc., by eliminating some of the guesswork involved with their application otherwise. It is always the function of time, miles or cycles where 63.21% of the units under evaluation have failed, which is the MTBF/MTTF for the exponential distribution. For the purpose of this brief introduction, we’ll limit our discussion to the exponential distribution and the Weibull distribution, the two most widely applied to reliability engineering. Collectively, they affect both the utility and the life-cycle costs of a product or system. In the industries of investment goods it becomes […] Reliability engineering incorporates a wide variety of analytical techniques designed to help engineers understand the failure modes and patterns of these parts, products and systems. In reality, only a fraction of the bearings actually survive to the L10 point. Any given individual from the population could fail on the first day of operation while another individual could last 30 years. Reliability Engineering – Basic Concepts . Often, design engineers will incorporate redundancy into critical machines. This depends on a number of factors: • design of the system • the parts and components used • and the environment Reliability is the probability that the given system will perform its required function under specified conditions for a specified period of time. Assuming everything is constant, except the β shape parameter, Figure 7 illustrates the difference the β shape parameter has on the estimate of reliability assuming β shape values of 0.5 (early life), 1.0 (constant, or exponential) and 5.0 (wearout) for a range of time estimates. Maintainability – The measure of the ability of an item to be retained or restored to specified condition when maintenance is performed by personnel having specified skill levels, using prescribed procedures and resources, at each prescribed level of maintenance and repair. The operating context and environment of a production process incorporates more variables than the somewhat one-dimensional world of product reliability assurance. 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