Health states assessment and prediction of manufacturing system based on brittleness

Abstract

Abstract Accurate recognition of system health states is the key to ensure the safe operation of the system. In view of the shortcomings of the existing methods, a new method of manufacturing system health states assessment and prediction based on brittleness is proposed. Firstly, according to the real-time effective performance parameters, the brittle risk entropy model of equipment is constructed, and the brittleness of corresponding equipment on each station is calculated; Secondly, based on the structural characteristics of manufacturing system, the calculation model of system brittleness is constructed by analysing from equipment to system step by step, and the mapping relationship between system brittleness and health states is established to complete the assessment of system health states; Thirdly, based on the historical data samples, the quintic polynomial regression model of system brittleness and time is constructed to predict the future health states of system and the time nodes that need to be maintained. Finally, an assembly manufacturing system is taken as an example to verify the correctness and effectiveness of the proposed method.