Service Optimization of Internet of Manufacturing Things Based on Mixed Information Axioms

As a new intelligent manufacturing model, the Internet of Manufacturing Things (IOMT) based on the Internet of Things technology has a large amount of random, fuzzy, and uncertain information, which makes the optimization of manufacturing services face challenges. On the basis of fully considering the uncertain factors in the process of manufacturing service, a quality of service (QoS) optimization method based on mixed information axioms is proposed to solve the optimization problem of manufacturing service in the IOMT environment. The mixed uncertainty model is expounded with random variables to express the range of system and fuzzy variables to describe the design range. In order to select the best resource or sort, the fuzzy mathematics and the axiomatic theory of axiomatic design theory are combined to evaluate the coexistence of ambiguity and randomness of the QoS. Finally, the process of treatment and optimization in practical application by taking the example of a hydraulic pump product seeking service through the civil aircraft IOMT service platform is described. This example is given out to demonstrate the effectiveness of the proposed method by comparing with the traditional information axiom method, and this method extends the application scope of traditional information axioms.