Research On The Evaluation System Of Smart Heating System

With the development of the times,big data,cloud computing,AI and other high and new technologies continue to integrate into traditional industries,it has been an inevitable trend for heating systems to undergo intelligent transformation.As China is in the key period of creating smart cities,building new infrastructure and advocating ecological and environmental protection,heating enterprises should seize the opportunity to advance intellectual heating process energetically,raise construction level unceasingly,realize enterprise and society common development.In order to help enterprises locate their own intellectual heating construction level and find out the weak areas,this paper,based on the connotation and target characteristics of smart heating,establishes a set of scientific and feasible indicator evaluation system of smart heating system through the process of literature review,questionnaire interview,online survey and software analysis,etc.The main contents of this article are as follows:Firstly,after comprehensive understanding of the current situation of the meaning,development process,technology and target of intelligent heating,and referring to the mature standards of traditional heating evaluation,intelligent grid,intelligence manufacturing ability,artificial intelligence,etc.,we choose data connectivity,intelligent decision-making and efficient self-control 3 primary indicators and 14 secondary indicators.In order to test the rationality of indicators and the feasibility of the evaluation system,a questionnaire was designed and distributed according to the characteristics and evaluation principle,and data results were calculated and analyzed by using SPSS 25.0and AMOS 25.0 software.It was obtained that the evaluation indicator system meets the theoretical requirements,can reflect the corresponding relationship between the different levels,and can better summarize the influencing factors of the smart heating system in terms of smart development.Secondly,after comparing the applicability and evaluation process of different assignment methods,the improved structural entropy weighting method is selected to assign weights to the indicators,which has better applicability for the characteristics of small sample information and complex indicator types of smart heating,and the improved structural entropy weighting method can correct the weights of the first-level indicators to make the results more accurate and reliable.After that,this paper adopts the grey relational degree analysis method combining qualitative and quantitative evaluation as the comprehensive evaluation method.In order to achieve an accurate description of the smart heating level of the enterprise,five development levels are defined with reference to the level definition in the smart manufacturing maturity model,and each level corresponds to a certain range of scores,with the higher the score the higher the level.At the same time,the calculation method and scoring criteria of each indicator are given with the meaning of indicators and related literature,and the qualitative indicators are taken according to the degree of realization,and the quantitative indicators are taken according to the principle of linear difference.Finally,based on the research on online smart heating construction in several cities,this paper selects six heating enterprises as evaluation objects,summarizes the scores of each indicator according to the construction information provided by them,calculates the smart heating construction ranking of each participating enterprise by combining the indicator weights and comprehensive evaluation methods obtained in the previous paper,and analyzes and compares the development status of enterprises at different levels,and put forward suggestions for the implementation of enterprise wisdom transformation.