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It is difficult to describe the complex relationship between spare parts consumption and influencing factors accurately in the prediction process. The resons are listed as the randomness, diversity, time-varying and insufficient information of spare parts demand. The theories has been developed rapidly when dealing with uncertainty based on the Intelligent computing and tools. It was summarized about relevant literature on handling the uncertainty of spare parts demand prediction, according to the four categories of uncertainty, namely, randomness, fuzziness, incompleteness and compound uncertainty. It was summarized about the limitations and development direction of relevant research. The research results can be used to serve as references for equipment spare parts management. [ABSTRACT FROM AUTHOR]

Warship formation spare part support plan plays an important role in forming the warship formation readiness. The spare part support plan which is in accordance with the engineering practice is established by using inventory optimization management strategy. The support plan can be used to reduce the spare parts support funds while satisfying the minimum requirement of warship formation availability. A warship formation inventory optimization model which was based on spare part`s multi-echelon demand rate is built by taking the very low utilization rate of spare parts in the waters off Somalia as studying background, and the system support funds as the optimizing goal which is constrained by the minimum requirement of warship formation availability, and the calculation steps and the solution method are given. the decision and recommendations of warship formation spare part configuration is proposed by using the contrastive research on the different warship formation spare part support plans. [ABSTRACT FROM AUTHOR]

A sound warship spare parts allotment optimization project is the result of cost efficient tradeoff between multi-constraints and optimal objective. In the conventional Warship spare parts allotment optimization models, the operational availability and the mean waiting time for spares and expect back order are always the target, but these parameters are rarely used by the domestic use department and model development unit to confirm the warship spare parts allotment project. In order to solve all the problems which are mentioned above, firstly, objective function and constraint conditions are analyzed; Secondly, an optimized model of the probability spare guarantee is built, Lagrange and marginal algorithm are applied to build the warship spare parts allotment optimization model and process optimization; Once more, the resource factors are being confirmed and dynamically updated; Finally, in the given example, by analyzing the results of the case, the feasibility of the proposed method is verified. [ABSTRACT FROM AUTHOR]

Study on the multi-state reliability modeling, analysis and assessment, which plays an important role in controlling time-varying process reasonably and programming supportability activity effectively for the big complex equipment system. In this paper, a universal method adopted to analyze and assess the accumulative characteristic of reliability is given with respect to the multi-state complex equipment systems under time-varying demand condition. Meanwhile, the logic reward matrix system is established and the accumulative logic reward is calculated during work period. Research shows that method adopted in this paper has better robustness, which can meet different constraint condition and assessment request. And that also has better adaptability and routinization, which can be used to assess any multi-state systems with high state dimension uniting with the universal generating function (UGF) technology and can easily be realized by the computer programming considering the matrix vector model. Moreover, the result can be applied to analyze and assess multi-state system reliability in other fields, such as energy industry, information industry and machinery industry, and has important directive to equipment support system construction. [ABSTRACT FROM AUTHOR]