A knowledge-driven functional change propagation path and workload prediction method

Abstract

The present invention proposes a knowledge-driven function change propagation path and workload prediction method. For all potential affected functions, compare the similarity of the change knowledge of the changed functions and the knowledge of the affected functions one by one; secondly, build the change propagation tree from the functional decomposition model and the change propagation tree from the functional interface model respectively, and calculate the change propagation The additional complexity and workload caused by the possibility and change propagation; finally, according to the additional complexity and workload, a specific design plan is formulated to effectively manage the product development progress. Combined with the BZT complexity evaluation method, the invention helps engineers to improve the existing research and development plan, ensures the research and development progress, and improves the problems of huge workload, strong input subjectivity and low versatility of the engineering change propagation prediction method based on product components.

Description

technical field [0001] The invention relates to the technical field of change propagation prediction, in particular to a knowledge-driven function change propagation path and workload prediction method. Background technique [0002] The difficulty of effectively predicting and managing the complexity of the design phase is one of the main reasons for the increase in product development cycles. The research and development of large-scale products such as automobiles, airplanes and satellites is a complex system engineering that requires multiple iteration stages, of which the design stage is crucial, and its quality not only directly determines the development time, but also affects subsequent manufacturing, use and maintenance. cycle and cost. According to the system engineering method, in the early stage of the design phase, complex products can be decomposed into function trees with different abstraction level functions from top to bottom. function integration. However,...

AI Technical Summary

Problems solved by technology

[0009] Aiming at the technical problems of strong workload subjectivity and weak versatility in existing change propagation prediction methods, this invention proposes a knowledge-driven function change propagation path and workload prediction method. From the perspective of function and knowledge, Establish a function change propagation prediction model; then determine the change propagation path and calculate the propagation possibility; on this basis, combined with the BZT complexity evaluation method, calculate the additional workload caused by the function change propagation, so as to help engineers improve the existing R&D plan , to ensure the development progress

The present invention can improve the problems of the existing engineering change propagation prediction method based on product components, such as huge workload, strong input subjectivity and low versatility

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