为实现不完全维修条件下的数控机床可靠性评估,提出基于对数线性比例强度模型(Log-linear proportional intensity model,LPIM)的多台数控机床可靠性评估方法,建立故障时间的对数线性比例强度函数式.用极大似然估计法和Fisher信息矩阵法给出了模型参数的点估计与区间估计,给出机床可靠性指标的点估计和基于Delta法的区间估计,采用似然比检验方法对时间趋势和修复功效的显著性进行检验.实例分析表明,考虑维修活动影响时,LPIM优于Weibull分布法和非齐次泊松过程模型,能定量反映出维修对机床可靠性的作用,得出的瞬时和累积可靠性特性更符合实际.
An approach of assessing reliability for multiple NC machine tools with general repair based on log-linear proportional intensity model (LPIM) is proposed, and an LPIM function for failure times is built. Point and confidence bounds estimates of model parameters are given by maximum likelihood method and Fisher information matrix method. Point estimates of reliability metrics are also derived with their confidence bounds offered through Delta method. Likelihood ratio tests are adopted to check the time trend and repair effect. A real example analysis demonstrates that, LPIM approach outperforms Weibull distribution method and NHPP model considering the effects of repair activities, capable to capture quantitatively repair effects on machine tools reliability, hence the instantaneous and cumulative reliability properties obtained more practical.