Under the condition of failure data with poor information

the maximum entropy model for evaluation of mechanical product reliability was put forward. According to the empirical value formula of reliability

the reliability empirical value vector of failure data was obtained

and discrete failure frequency vector of lifetime data could be inferred by the empirical value vector (i.e. statistical histogram was obtained); based on the interval-mapping Newton iteration method

the maximum entropy probability density function was established

the failure probability distribution function could be gained by integration

and then the estimated true value function of reliability was acquired. Studies on simulation cases and experimental cases have proved the method proposed is not only able to evaluate the reliability with a known distribution but effective and feasible in the reliability assessment under the condition of failure data without any priori information about the possibility distribution. At the given lifetime

the difference between the values of reliability obtained via the maximum entropy method and the known distributions is very small

which only reaches 3.40%.