By Michael Tortorella
Makes a speciality of the middle structures engineering initiatives of writing, handling, and monitoring requisites for reliability, maintainability, and supportability which are probably to meet shoppers and result in luck for providers. This ebook is helping structures engineers lead the improvement of platforms and companies whose reliability, maintainability, and supportability meet and exceed the expectancies in their shoppers and advertise luck and revenue for his or her providers. This e-book is prepared into 3 significant elements: reliability, maintainability, and supportability engineering. inside each one half, there's fabric on standards improvement, quantitative modelling, statistical research, and top practices in each one of those parts. Heavy emphasisis put on right use of language. the writer discusses using a variety of sustainability engineering equipment and methods in crafting requisites which are keen on the shoppers' wishes, unambiguous, simply understood by way of the necessities' stakeholders, and verifiable. a part of each one significant department of the ebook is dedicated to statistical analyses had to make sure whilst specifications are being met by means of platforms working in consumer environments. To additional aid structures engineers in writing, examining, and reading sustainability standards, this e-book additionally includes "Language counsel" to aid platforms engineers examine the various languages spoken by means of experts and non-specialists within the sustainability disciplines. It presents workouts in each one bankruptcy, permitting the reader to aim out many of the rules and strategies provided within the bankruptcy; promises end-of-chapter summaries of the present reliability, maintainability, and supportability engineering top practices for structures engineers. Reliability, Maintainability, and Supportability is a reference for platforms engineers and graduate scholars hoping to benefit the right way to successfully make certain and enhance acceptable necessities in order that designers could fulfil the reason of the client.
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Extra info for Reliability, Maintainability, and Supportability: Best Practices for Systems Engineers
The systems engineer is a supplier to the rest of the design and d evelopment team. The product supplied by the systems engineer is the set of requirements for the system (or service). The design and development team, an internal customer, needs clear direction from systems engineering, and the techniques we discuss in this book promote that clarity. A good customer–supplier relationship here includes process management for the requirements development process incorporating a robust feedback mechanism for improvement not only of individual requirements but also of the process by which they are generated.
While alignment with customer needs and desires is absolutely of paramount importance for systems engineers, for good requirements are impossible without it, the details of these techniques are outside the scope of this book even though they are useful in helping to determine not only attribute but also sustainability requirements. Customers and users are interested in the frequency and duration of incidents of violations of attribute requirements, and their needs and desires for the frequency and duration of such incidents of violation are properly the subject of appropriate requirements themselves (these will be the reliability, maintainability, and supportability requirements).
Good requirements are complete (cover all properties and behaviors needed and desired by the customer). The best way to promote unambiguous requirements is to state them in quantitative terms. Most requirements in the sustainability disciplines involve some quantitative variable. For example, we may wish to limit the amount of time it takes to complete a specified repair. To enforce such a limit, this duration will be the subject of a requirement. 1 Consequently, it is customary to conceptualize the quantitative variables appearing in requirements as random variables in the sense used in probability theory.