In this paper we describe a general approach to optimal imperfect maintenance activities of a repairable equipment with independent components. Most of the existing works on optimal imperfect maintenance activities of a repairable equipment with independent components. In addition, it is assumed that all the components of the equipment share the same model and the same maintenance intervals and that effectiveness of maintenance is known. In this paper we take a different approach. In order to formalize the uncertainty on the occurrence of failures and on the effect of maintenance activities we consider, for each component, a class of candidate models obtained combining models for failure rate with models for imperfect maintenance and let the data select the best model (that might be different for the different components). All the parameters are assumed to be unknown and are jointly estimated via maximum likelihood. Model selection is performed, separately for each component, using standard selection criteria that take into account the problem of over-parametrization. The selected models are used to derive the cost per unit time and the average reliability of the equipment, the objective functions of a Multi-Objective Optimization Problem with maintenance intervals of each single component as decision variables. The proposed procedure is illustrated using a real data example.

翻译：本文提出了一种针对具有独立组件的可修复设备进行非完美维护活动优化的一般性方法。现有大多数关于可修复设备非完美维护活动优化的研究通常假设设备所有组件共享相同的模型与维护周期，且维护效果已知。本文采取了不同的研究路径。为形式化描述故障发生与维护活动效果的不确定性，我们为每个组件考虑一类候选模型，这些模型通过组合失效率模型与非完美维护模型得到，并让数据选择最优模型（不同组件的最优模型可能不同）。所有参数均假定为未知，并通过最大似然估计法进行联合估计。模型选择针对每个组件分别进行，采用考虑过度参数化问题的标准选择准则。所选模型用于推导设备的单位时间成本与平均可靠性，这两者构成了以各组件维护周期为决策变量的多目标优化问题的目标函数。本文通过实际数据案例对所提流程进行了说明。