. Some months might have no failures, whereas other months might have several failures, but the fail- ures over time average one per month. We would say that l is one failure per month or about 0.032 failures per day. If the average time for repair is 1 day, then we would say is 1.0 repairs per day. Any given repair might take an hour or a week, but the aver- age is 1 day. In an equilibrium condition (over a long period of time), the probability flow from WORKING to FAILED will equal the probability flow from FAILED to WORKING, and the prob- abilities add up to 1. This gives us Eq. (4.1): (4.1) po + P1 = 1 where Po = probability of being in FAILED state P1 = probability of being in WORKING state Figure 4.5 Three components in a series system. Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright © 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website. The Base Station The Base Station Fixed Working Failed Breaks Figure 4.6 Two-state component reliability diagram. We can solve these equations and see that this component will spend u/(1 + u) of its time in the WORKING state and the other /( + u) of its time in the FAILED state. Our example component will average 96.8 percent of its time WORKING and 3.2 percent of its time FAILED. If this is component A, then adding in the failure times for components B and C can only make it worse. If this were our equipment, then we probably would decide that 3.2 percent is an un- acceptable out-of-service time for a base station. There are two direct ways to improve the service level: Decrease l by making the equipment more reliable or increase by having faster repair service. This may be difficult because more reliable equipment may be several times more expensive, and base stations are generally in remote loca- tions that may be hard for a repair truck to reach quickly. There is another approach. We can improve the reliability of a system by adding spare equipment. No