Research On Intelligent Monitoring And Manageing Method Of Furniture Production Costs

Manufacturing industries take reasonable use of all kinds of resource costs and convert them into products.Among all the industries,the production lines of furniture industry have the prevalent problems that having lots of contradictions in control of operation cost because of lagging behind information,unstable production quality,low rate of equipment utilization,complexity of management and poor improvement effect.The effective monitoring of the operation cost of the production line is an important guarantee to ensure the efficient operation of the enterprises in the industry and maintain their competitiveness.Nowadays,China's manufacturing industry is facing the overall upgrading and the,re is an urgent need for domestic furniture manufacturers to carry out major reforms to meet the needs of new forms,as well as the increasing operation cost of resources,energy and manpower.Therefore,the intelligent monitoring and control of the operating cost of the furniture production line can help enterprises to solve such problems effectively.This research focuses on the framework of intelligent monitoring method of furniture production lines' operating costs,the principle of intelligent data acquisition of operation cost and production state,the modeling of the data,the multi-objective optimization of operation cost,the output of the implementations and the feedback of improvement eff.ect.Firstly,to solve the problem of characteristics analysis of intelligent monitoring and management of furniture production cost,the composition of cost and the characteristics of the related data were identified and analyzed.Relevant statistical analysis,data mining and other methods were used to analyze the modeling of various cost related factors.Based on the results of the modeling,the requirements and characteristics of the operation cost abnormity treatment and optimization,methods are analyzed.To solve the problem of data acquisition of cost and influencing factors,an intelligent data acquisition system,which is related to the factors related to the operating cost of the furniture production line and the real time state information of production,was put forward.The concept of data acquisition matrix and the related definitions were established.All the costs and various influencing factors were covered in the process.The discrete data matrix,the continuous data matrix and the target data matrix are further defined.The principles and functions were fully explained from the perspectives of single and multidimensional influence factors.The data acquisition matrixs fully considered the characteristics of the discrete and continuous production processes of furniture production,which were used to collect,organize and store all kinds of cost related data and support the follow-up analysis call.In the specific die casting production line case,the above method had realized the development of the data intelligent collection system,and accumulated a lot of real data,which laid the foundation for the operation cost of the subsequent production line and the mathematical modeling of the influencing factors,such as the abnormal optimization,and proved the effectiveness of the method and the related theory.To solve the mathematical modeling problem of the operating cost of furniture production lines and their influencing factors,a set of modeling methods for the operation cost of the furniture production line was put forward.Data clustering and data dimensionality reduction based on principal component analysis were applied to realize the preprocessing of data.Based on the deterministic mathematical modeling method based on linear and nonlinear regression analysis and the uncertain mathematical modeling method based on BP neural network,the calculation model of operating cost of furniture production lines and their influencing factors under the constraints of various data characteristics and mathematical principles were established.The related model verification methods were also put forward.A concrete case study was given to elaborate the mathematical modeling method of operation cost of furniture production line proposed.The results showed that the modeling method had high calculation precision,which laid the foundation for the future work of on-line calculation of factors,state monitoring,abnormal optimization and feedback evaluation.To solve the problem of abnormal control of operation cost,the evaluation system of intelligent optimization algorithm was proposed.The specific contents include the identification of abnormal operation cost,the classification of optimization methods,and the evaluation system of optimization algorithm.The evaluation objects include the efficiency and stability of the intelligent algorithm,and the integrity of the Pareto solution set.It provided specific intelligent solutions for specific cost exceptions.Through the monitoring results of the actual case,the average operating cost of the production line decreased gradually and returned to the normal level in the subsequent periods of the following periods of the production line.It was proved that the method proposed in this paper can effectively use intelligent means to balance and effectively solve the problem of operation cost abnormality.Finally,the research contents and the innovation points of this thesis were summarized,and the future research directions were discussed.