Aircraft Material Maintainers Assessment Research Based On RIMER Theory

When aircraft flight's amount increasing and flight punctuality requirements continue to increase at the same time, competitive pressures currently faced by domestic and foreign airlines are heavier,reserving appropriate continuing airworthiness air materiel become an important strategic objective for the airline company. So regularly or irregularly to evaluate aircraft material providers to ensure that the providers can provide sustained and stable aircraft material. This paper studies the evaluation of the aircraft material providers, and belief rule-base inference methodology using the evidential reasoning approach. An aircraft material providers evaluation method is proposed basing on the belief rule base.The main property parameters of the belief rule base is trained by particle swarm optimization algorithm,which is applied to the belief rule base parameters training and improve the ability for airline companies to assess effectively aircraft material providers. This paper mainly completed the following work:1)This paper describes the background and significance of aircraft material supplier assessment, RIMER method is used as the theoretical basis for aircraft material supplier evaluation, and the theoretical principles and implementation process is descripted.The air material providers belief rule base is established, the qualitative and quantitative analysis method of organic combination of system modeling, the establishment of aviation maintenance business evaluation and decision making model.2)Integrated analysis aircraft material provider evaluation of new features. Build analysis aircraft material provider on the basis of the evaluation criteria and principles.From the basic situation of the maintenance supplier, cost, quality, cycle and service five aspects of to evaluate and make decisions.Ensuring objectivity and comprehensiveness of the assessment process to provide a reliable aircraft material provider evaluation.3)In the belief rule base parameter in training, PSO algorithm premature convergence of traditional local optimal solutions,proposed gradually decreasing inertia weight in PSO algorithm. By aircraft material provider evaluation test in the instance of the validity of the algorithm, the improved PSO algorithm converge faster, more accurate; belief rule output parameters after training with expert scores have significantly improved. Experimental results show that the improved PSO algorithm can be used for belief rule base parameter training.