O-K Learning Super-Network Evolution Model And Its Performance Influencing Mechanism Of Complex Product System

Complex Product Systems(CoPS)play a role of the basis for economic development,improving the efficiency of knowledge learning and achieving technological upgrading could be a vital approach to develop the CoPS quickly.With the rapid development of modern communication technology,the CoPS9 chain of international industrial value is reconstructing continuously,causing the growing trend of knowledge activity network.Hence,the construction of CoPS O-K learning network model and the study of its dynamic evolution is the theoretical requirement of systematic knowledge management as well as the practical requirement of knowledge innovation and industrial upgrading.However,there is still a lack of systematic and in-depth research on the construction method,dynamic mechanism,knowledge learning network model generation mechanism and network structure characteristics of CoPS,which hinders a in-depth study of knowledge learning performance mechanism,as well as how to apply theory into promote knowledge innovation and industrial upgrading in CoPS.The main contents of this paper include:Firstly,an O-K knowledge super learning-network static model of CoPS was proposed,considering knowledge learning modes of multi-organizational in CoPS.In the meantime,taking the uniqueness of learning activities and the evolution of GUSA model into consideration,the learning motivation mechanism of O-K learning super-network was extracted.Secondly,the project team member selection algorithm based on O-K learning super-network was analyzed.This paper takes judgment language uncertainties of the multidimensional organization nodes in the super-network into consideration.After careful evaluation of individual advantage weight in the competition evaluation,the Individualization-intuitionistic fuzzy interval weighted geometric operator(I-IIFWG)was proposed,providing the application method based on the operator.In this paper,an example is introduced to show the team-member preference mechanism.Thirdly,the knowledge learning process and evolution mechanism of O-K learning super-network were analyzed.Based on the theory of system dynamics,this paper analyzes the content of knowledge gathering,knowledge transfers and knowledge diffusion in a knowledge learning cycle,and puts forward the dynamic construction algorithm and generating mechanism of O-K learning super network.Finally,two characteristic indexes to analyze the dynamic operation characteristics of O-K learning super-network were concluded.Finally,this part aimed to learn super-network knowledge evolution model with the characteristics of the project team as the starting point.Based on the simulation experient,to explore the characteristics of the project team and the mechanism of multi-organization cooperative network structure on learning performance.Through the case study,this paper gives the enlightenment of knowledge management practice and gives relevant suggestions.