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Research On Assessment Model For Intelligent Manufacturing Development Of Regional Industrial Enterprises And Its Application

Posted on:2019-02-15Degree:MasterType:Thesis
Country:ChinaCandidate:Y M WangFull Text:PDF
GTID:2439330545476379Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the increasingly fierce international competition in the manufacturing industry,China issued "China made 2025,in 2015,which regards intelligent manufacturing as the pillar and core for revitalization of the real economy and the emerging industries,as well as the basis and key to enhance the competitiveness and sustainable development ability.At present,our country has a more mature assessment model in the field of information,integration of information and intelligence,and other fields.It can be used to evaluate the development level and publish the evaluation report to the public.However,due to the short time of intelligent manufacturing,the research on intelligent manufacturing evaluation in China just begins.Some institutions put forward a model to evaluate the maturity of enterprise intelligent manufacturing capability.Some scholars build a system to evaluate the development level of single enterprise intelligent manufacturing.Some literature research analyses intelligent manufacturing capability of single province on the basis of intelligent manufacturing evaluation index.The existing evaluation methods of intelligent manufacturing are at the absolute level of intelligent manufacturing.Although the absolute level can be used to compare the differences in different regions or enterprises,it can not objectively reflect the degree of development.The relative level can break the limit of 100 points and objectively reflect the development and change.This paper summarizes the research achievements on the assessment of intelligent manufacturing,and systematically studies the basic theory of intelligent manufacturing and analyzes the factors affecting the evaluation of intelligent manufacturing.Above that,this paper adopts the relative level to do evaluation.The evaluation model of intelligent manufacturing development level for regional industrial enterprises is proposed for the first time.The research contents of this paper include:(1)put forward the assessment model of regional intelligent manufacturing development level,take the level of national intelligent manufacturing development in 2016 as the benchmark of each year,calculate the regional intelligence manufacturing development index relative to the base year,and make clear the idea and principle of evaluating the index.(2)put forward the three level index system,considering the restrictive influence of the ecological environment,the enterprise construction and the benefit to the intelligent manufacturing development of the regional industrial enterprises.By using the principal component analysis method and combining the sampling data of 140 enterprises in Xiamen in 2016,many indexes are classified and reduced to avoid the cross weight of the indexes,optimize the evaluation index system.(3)using the combination of qualitative and quantitative in system evaluation,we adopt analytic hierarchy process and network analytic hierarchy process to calculate index weights respectively,establish two index systems based on PCA-AHP and PCA-ANP,and compare them.The results show that AHP is biased towards the problem of hierarchical structure,while ANP is aimed at the internal.The network hierarchy with interdependent elements is more effective.The evaluation index system based on PCA-ANP is more practical.(4)using the sample survey data of 140 enterprises in 2016 in Xiamen,this paper carries out a case study on the proposed evaluation model,validates the applicability and feasibility of the evaluation model based on PCA-ANP,and analyses the present situation of intelligent manufacturing development of industrial enterprises in Xiamen according to the results obtained,and puts forward relevant suggestions for development.
Keywords/Search Tags:intelligent manufacturing, evaluation model, system evaluation
PDF Full Text Request
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