The importance of the equipment support capability index is the premise and foundation of equipment support construction and is the logical starting point for carrying out related research. Determining the importance of equipment support capability indicators can guide and lead the improvement of support capability and promote the performance of equipment support. Aiming at the problems of high subjectivity and low reliability in the current method for determining the importance of the capability index, this paper proposes a gray relational quality function expansion method based on the GQFD-BP neural network. Through the process of determining the task index and the capability index, constructing an expert preference model, establishing the gray comprehensive correlation matrix, and building a house of quality, the importance of the intelligent equipment support capability index is determined, and a theoretical basis for the construction and application of intelligent equipment support capabilities is provided.
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