Research On Customized Demand Prediction Technology For Construction Machinery Based On Data Mining

In the era of Industry 4.0,more and more manufacturing enterprises are integrating knowledge,information,and digital technology into their production processes to improve their competitiveness.With the development of society,customers’ concepts are also changing.Traditional mass production methods are no longer able to meet customers’ customized needs.Customized product design and production driven by big data will become the key for enterprises to seize the terminal market in the future.This article combines data mining technology to establish a customized demand prediction model for construction machinery.Taking concrete spreaders as an example,demand collection is conducted for existing customers;Requirement induction;Demand analysis,customized demand forecasting for target customers;Customized fabric distribution machine design;Evaluation of customized fabric distribution machines.Firstly,the steps of conventional mechanical design were analyzed,and combined with the key tasks of customized engineering machinery design,a customized demand prediction model for engineering machinery based on customer needs was established.The specific process of customized demand prediction for concrete placing machines was determined by combining the model.Secondly,use web crawler and questionnaires to collect internal and external demand data of enterprises,and build a mass customer demand index system through sorting,transformation and induction of demand data.Based on the indicator system,a questionnaire survey was conducted to establish a preference matrix for existing customer needs,and the collection and induction of existing customer needs for the fabric machine were completed.Then,K-means clustering and R-type clustering algorithms were used to analyze the laws in the demand matrix of existing customer fabric machines.The obtained laws were combined with BP neural network to complete the prediction of customized demand for target customers.Using the Analytic Hierarchy Process(AHP)combined with the K coefficient of the KANO model,the customized weight of the demand was calculated,and the customized demand plan for the target customer was ultimately determined.The analysis of the existing customer demand for the fabric machine and the prediction of the customized demand of the target customer were completed.Finally,based on the customized demand plan of the target customer,the functional design and optimization of the customized fabric machine were completed using QFD and TRIZ theories,and a customized parameter setting system with user expert interaction was established.Confirmed customized technical parameters;Collect feedback on virtual prototype evaluation that meets the parameters for the target customer group;The customer satisfaction score was calculated using fuzzy evaluation method and TOPSIS theory.Completed the requirement implementation and evaluation of customized fabric distribution machines.This article demonstrates the practical significance of the established customized demand prediction model for construction machinery through the case study of fabric distribution machines.The products produced under the guidance of the model can meet the customized needs of customers,and the model is suitable for the customized production of construction machinery enterprises...