摘要
现代制造业为了满足消费者的需要,面临着用有限的生产成本快速地为客户提供多品种、高质量、定制产品的压力；大规模定制迎合当今市场需求,它正以其独特的生产模式引起社会广泛关注。大规模定制的核心思想是以接近大规模生产的速度和成本满足客户对产品的个性化需求,它将传统的面向客户订单的反应式定制转变为面向产品族规划的预定制,以提高企业快速响应客户需求的能力。其实施成败的关键在于能否有效解决同时满足客户个性化的特定需求且保持批量生产的规模效益之间的矛盾。因此,合理的产品族规划成为企业实施大规模定制的基础和保障。
本文的研究目标在于针对参数化产品族规划,提出有效的方法和工具支持科学的产品族优化决策。以期既要展现面向客户尽可能丰富的产品外部差异性以满足客户的需求,又要增加面向企业尽可能多的产品间共性以降低额外生产成本。成功的设计方法应能在满足客户个性化性能需求的前提下获取产品族内的最大共性,实现产品族共性与差异性的最佳平衡。
论文通过对大规模定制的概念、本质属性详细分析,结合产品族的概念、特点与优势,指出以产品族规划为基础组织企业的生产经营,能够集成大规模生产与定制生产的优势,辅助企业有效地实施大规模定制生产。
在参数化产品族优化方面,本文对产品族优化设计的理论与方法进行了较为深入的探讨,具体包括：
(1)在不考虑产品间共性的约束条件下,从多目标的角度,研究了无公用平台下,参数化产品族多目标优化设计方法。建立了无公用平台下,参数化产品族的多目标优化模型,并给出其多目标优化问题模型的求解方法,仿真实验结果表明,所提方法较文献中其他优化方法而言,能得到更佳的无公用平台下参数化产品族整体优化方案。
(2)以无公用平台下参数化产品族多目标优化结果为研究基础,分析了单平台下,参数化产品族的多目标优化问题。对参数化产品族平台变量的优选方法进行了探讨。根据平台变量选取后,是否预先合理设置平台变量取值以降低问题求解的复杂性,分别建立了平台变量取值已知和未知时的参数化产品族多目标优化模型；并给出了相应的求解方法。仿真实验结果表明,所提方法均能得到优于其他文献中所提方法得到的结果。但预先不固定平台变量的取值,所得到的产品族优化设计结果要优于平台变量值预先固定时的产品族优化设计结果,代价是前者算法复杂度更高。
(3)对单平台下参数化产品族设计方法进行了拓展,提出了多平台下的参数化产品族优化设计方法。针对多平台下参数化产品族的特点与及其优化的复杂性,提出了一种单阶段下多平台产品族双层多目标并行协同优化算法,用于求解多平台下参数化产品族多目标优化模型。仿真实验结果表明,所提方法能够允许在平台变量未知的情况下,通过在运行过程中自动改变平台共性并搜索共性与产品差异性之间的最佳平衡点；并通过一次优化过程即可选择最合理的平台变量和差异性变量的最佳配置,以及平台变量和差异性变量取值的最佳设置；从而获得柔性高、整体性能佳的产品族优化设计方案。
综上表明,基于平台的参数化产品族开发设计,能以低成本、高质量的产品快速响应顾客个性化的需求。这对产品定制日益普及的当今企业,进行产品开发优化设计具有一定的借鉴意义。
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.
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