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          <name>Title</name>
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              <text>Reliability, maintainability and sensitivity analysis of physical processing unit of sewage treatment plant</text>
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          <name>Subject</name>
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              <text>Availability; Dependability ratio; Maintainability; Physical processing unit; Reliability</text>
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              <text>India is facing radical change in perspective of inadequate water resources which can reduce by using treated water. In this direction, sewage treatment plants play a key role. Sewage treatment plant comprises three units namely physical processing, chemical processing and biological process. The physical process is the most important part and it has five component arranged in series configuration. It becomes necessary to perform this process with high efficiency and reliability, availability, maintainability, and dependability (RAMD) is the methodology to analyze the performance. The failure and repair rates of the subsystems has been considered exponentially distributed. ChapmanKolmogorov differential equations are derived using Markovian birthdeath process and several measures like mean time between failures, mean time to repair and dependability ratio are derived. The sensitivity analysis of reliability of the plant has also been performed. RAMD investigation shows that: availability of system is 0.952177, reliability of the system after 20days is 0.2018 and after 60days 0.00823, maintainability of the plant is 0.999948, dependability ratio is 0.9541 and raw sewage sump is the most sensitive subsystem of the plant with reliability 0.382893. This work is projected to support as an informative exertion in steering a RAMD analysis of physical processing unit and vary few work is available in literature related to the performance features of physical processing units of the sewage treatment plants. The main findings may be very useful for sewage treatment plants designers.  2019, Springer Nature Switzerland AG.</text>
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          <name>Creator</name>
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              <text>Goyal D.; Kumar A.; Saini M.; Joshi H.</text>
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              <text>SN Applied Sciences, Vol-1, No. 11</text>
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              <text>Springer Nature</text>
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              <text>2019-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/s42452-019-1544-7" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s42452-019-1544-7&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082644905&amp;amp;doi=10.1007%2Fs42452-019-1544-7&amp;amp;partnerID=40&amp;amp;md5=27b8fd41ecd11618d4c8e45bb4676a4f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082644905&amp;amp;doi=10.1007%2fs42452-019-1544-7&amp;amp;partnerID=40&amp;amp;md5=27b8fd41ecd11618d4c8e45bb4676a4f&lt;/a&gt;</text>
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              <text>All Open Access; Bronze Open Access</text>
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              <text>ISSN: 25233971</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Goyal D., Department of Mathematics and Statistics, School of Basic Science, Manipal University, Jaipur, Jaipur, 303007, India; Kumar A., Department of Mathematics and Statistics, School of Basic Science, Manipal University, Jaipur, Jaipur, 303007, India; Saini M., Department of Mathematics and Statistics, School of Basic Science, Manipal University, Jaipur, Jaipur, 303007, India; Joshi H., Department of Statistics, CHRIST University, Bangalore, India</text>
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