Reliability Research Of The R&D Process Of Passive Optical Device

As the time of Great Data has come, faster and more-reliable is more and more critical for the R&D process of the related products. There is a lot of uncertain description on the status of the R&D process, such as “stable running”, “high risk”, “roughly 90% of reliability”, etc. The classical reliability theory based on probabilistic measure space cannot model the uncertain reliability well on actual uncertain issues. The purpose of this research is to study the solution of the informatization and programming of the uncertain reliability in the R&D process of passive optical devices(POD).There are three main parts of the thesis. In the first part, the mathematical fundament of uncertain reliability analysis is discussed, e.g. the uncertain variable, uncertain measure, uncertain programming. The model of process reliability analys is based on uncertain measure theory is presented, including the connection models of series, parallel, mixture and storage. The estimation method of the distribution of uncertain reliability based on Delphi procedure is presented in this part as well. In the second part, the properties of POD R&D process are discussed with the views of the system theory and reliability engineering. Compared with traditional reliability theory, the modeling of uncertain reliability theory is presented in this part. In the third part, it is the engineering application of the uncertain reliability modeling and programming on actual R&D process of POD. Comparing with 3 typical cases of evaluation for R&D process, uncertain reliability programming is verified an effic ient method to solve uncertain R&D engineering issues for cost-reducing. The last section of this part presents suggestions of reliability increasing.The main achievement and value of this research is as follows. 1). Solves the uncertain reliability issues in R&D process with the model of uncertain measure space which is transferred from the traditional model of probabilistic measure space. 2). Sets up the model of uncertain reliability analysis and estimation of uncertain distribution in R&D process. 3). Practices the uncertain reliability theory with engineering applications of uncertain programming.