Reliability analysis is an engineering discipline that applies various mathematical techniques to the measurement and prediction of the reliability of components and systems. The components under study may be mechanical, electronic, software, or other types. Measurements include failure rates, cumulative failures, and component lifetimes (time until failure). A variety of techniques are employed, drawn mainly from probability, statistics, and the theory of stochastic processes. Risk analysis includes methods for the assessment, characterization, and management of risk. "Risk" is generally taken to be the product of the probability of an event and the loss caused by the event (in financial or other measurable terms). Risks are often associated with failures of systems (including natural ecosystems), and thus the quantitative treatment of risk has much in common with reliability analysis. In this paper, we use fuzzy parameters in reliability analysis and show the importance of fuzziness in reliability and risk management. Using fuzzy exposure and resistance concepts, we compare the alternative locations for a nuclear power plant.