Methods And Applications For Multi-objective Intelligent Optimization On Scale-based Product Family Under Mass Customization

Inorder to fulfill the requirements of the customers, modern manufacturing feels the pressure of offering the various styles, high quality and customized products by utilizing the limited production cost. Mass cutomization caters for trend of needs in market. Now many enterprises in society are paying attention to it widely because of its advantage. The key thought of Mass customization is to offer customers individualized products at the nearly same effieiency and cost of mass production. Mass customization shifts the traditional customization model that passively responds to customer orders into the pre-customization model that plans initiatively product family inorder to improve the ability of enierprises to respond to customer requirements quiekly. The key is to solve the conflict between scale economies with batch production while meeting customers’individual requirements. Therefore, a reasonable product family planning is the foundation and guarantee of mass customization.The dissertation is to research and develop suitable methods and algorithms to support scientific scale-based product family optimization decision, including optimization of both exterior product functional diversification to satisfy customer’s individual requirement and interior design diversification to decrease production cost for enterprises. A successful product family design mothod should achieve an optimal tradeoff among a set of conflicting objectives, which involves maximizing commonality across the family of products without comporising the capability to satisfy customer’s performance requirements.According to the analysis for the concept and essential characteristics of mass customization in detail, in combination with the definition, characteristics and advantages of product family, The dissertation can indicate that the production and operations based on product family planning can effectively combine the benefits from mass production and one-of-a-kind production in order to enterprise effectively implement the strategy of mass customization in the customer.oriented market environment.In respect of scale-based product family optimization, the theories and methods related to product family optimization design were deeply researched in the paper, including: (1) Without regard for commonality between products, a multi-objective optimization design method for scale-based product family was proposed from multi-objective angles. The multi-bjective optimization model for scale-based product family without product platform was built and correspondent solving method was given. Comparison of the simulation experiment results with existing benchmark designs suggests that the proposed algorithms perform better than conventional optimization techniques, while providing designers with more information to support decision making during scale-based product family optimization design.(2) Based on the results of scale-based product family optimization design without consideration about commonality between products, the dissertation then analyzed the multi-objective optimization problem for single platform based product family. A method of optimal selection for platform variables among product family design variables was given. According to the complexity of scale-based product family optimization design based on selected platform variables, two multi-objective optimization models were respectively built based on platform variables values setting or no setting in advance and corresponding solving methods were proposed. The efficiency and effectiveness of the proposed method were illustrated by the optimization design of the Scale-based universal motor families and the comparison against the designs obtained from related literatures. At the same time, the simulation experiments also show that the results obtained from platform variables values without setting in advance during the process of corresponding algorithm running were better than that of platform variables values setting in advance. However, the former has a higher computational complexity.(3) This dissertation presents a new optimization design method for multi-platform based product family optimization problem in order to advance further the previous presented method for single platform based product family optimization problem. According to the characteristic and complexity of scale-based product family based on multi.platform, a two-level multi-objective concurrent collaborative optimization algorithm was presented to solve multi-platform based product family model during a single optimization process. The simulation experiment shows that the presented method in the case of unknown platform variables can simultaneously determine the optimal settings for the product platform and corresponding product family, by automatically varying the amount of platform commonality within the Scale-based product family.Viewed in toto, these results indicates that the development and design of scale-based product family on common product platform could reduce cost, raise quality of product and respond rapidly the individual needs of customers. It is definite sense for product development and design in enterprise because the way of customized product has gradually been popular in today.