Continuous Process Operating Performance Assessment And Its Application Using Rough Set Theory

With the rapid development of the society,due to the resource supply pressure,environmental protection cost and pursuit of industrial production profit,it becomes an urgent problem on how to control the continuous processes effectively and to improve production process profit.As a new research field,process operating performance assessment can judge the optimality degree of the process operating performance in real time.Besides,it gives guidance for identifying the cause of non-optimal process operating performance.This is conducive to the operators and managers to adjust the operation of the continuous processes to achieve the best economic performance.This thesis aims to study the assessment method of continuous process operating performance.An actual continuous process usually consists of multiple sub-processes.The variables within a sub-process are closely related,while the variables between the sub-processes are relatively weakly related.Besides,continuous processes have high complexity,miscellaneous influence factors and numerous uncertain information,which limit the application of the conventional assessment approaches.Taken the above characteristics and problems into consideration,a novel assessment method of process operating performance based on hierarchical multi-block structure is put forward in this thesis.A complex continuous process is vertically layered according to the direction of management,namely process layer,procedure layer and global layer.And then the process is horizontally blocked according to the production characteristics.The global assessment model is established according to the relationship between the global layer index and procedure layer indices.The procedure layer assessment model is respectively established according to the correlations between the procedure layer index and corresponding process layer indices.The process layer assessment model is respectively established according to the correlations between process index and corresponding process variables.Based on the hierarchical multi-block structure,rough set theory is used to deal with the uncertain information,implement the online assessment of process operating performance,and perform the non-optimal cause identification.Finally,the proposed method is applied to a gold hydrometallurgy process,and the simulation analysis is carried out to verify its effectiveness.The main researches of this thesis are summarized as follows:(1)The continuous process characteristics,gold hydrometallurgy process properties,and process operating performance assessment approaches are introduced in this thesis.(2)The types of uncertain information are described in this thesis.Rough set theory is reviewed,including the data processing,the establishment of decision tables,attribute reduction,attribute value reduction,and rule extraction.(3)According to the characteristics of the actual continuous processes,a novel hierarchical assessment structure is put forward.Sub-models are built on the basis of the hierarchical structure to assess the operating performance online with the uncertain information.If the performance grade is non-optimal,then the cause identification is carried out.Rough set theory properties,experts' knowledge,and operation feasibility are considered to build a dissimilarity formula to identify the non-optimal cause and guide the subsequent production.(4)At last,the gold hydrometallurgy process which is the typical continuous process is briefly introduced in the thesis.The hierarchical assessment method and the non-optimal cause identification method are applied to the gold hydrometallurgy process.In combination with the actual production,four typical cases are designed to verify the effectiveness of the proposed method.