Study On Key Technologies Of Mass Customizatin

With wide application of modern information technique, drastic globalcompetition among manufacturing enterprises and diversification of customers'requirement, manufacturing enterprises are up against more demand: more variety ofproduction, shorter time of delivery, lower production cost and better productionquality. All the experiences show that mass customization is the best mode ofsurviving and developing for manufacturing enterprises, because of which masscustomization has grown at a very rapid rate.Study on mass customization, concerning its research status and the development,is systematically taken in this thesis.First of all, partner selection for enterprise alliance, which is the key part of masscustomization, is studied in this thesis. If competitive and consistent partners areselected, which relates with the success and failure of dynamic alliance. At the sametime, partner selection for enterprise alliance of mass customization is direct affected.Study of partner selection is inherent requirement and supplies basis for dynamicalliance. By analyzing study status of it, multi-objective function model for partnerselection, considering T, Q, R, C, B factors, is built up, based on dynamic anduncertain market situation and general partner selection principle. A multi-objectivefunction model for partner selection is built up and then solved by genetic algorithm(GA) and simulated annealing (SA) algorithm. An example simulation result showsthe effectiveness of the model and algorithm as to partner selection.Secondly, cost forecasting in mass customization is studied. Prompt forecastingof product cost is one of critical technologies of rapid response in mass customizationproduct and is that of mass customization product. From those points, a costforecasting model is brought forward and then solved by GA and SA optimized neuralnetwork. An instance operating result reveals the accuracy and validity of the modeland the algorithm.Lastly, multi-objective optimization of product family in mass customization isstudied. Multi-objective optimization of product family is also one of pivotaltechnologies of mass customization product. With the coming of information era,global competition and expanding of customers'requirement, especially in masscustomization, the requirements of short time of delivery, low cost, good quality andpersonality of production should be enhanced constantly. Based on those points, amulti-objective optimization model of product family is proposed and then solved by genetic algorithm (GA) and simulated annealing (SA) algorithm. An illustrationoperating result displaies the availability of the model and the algorithm.