中文摘要：

针对按订单制造企业模块化产品族渐进演变过程中的绩效优化与控制问题,应用神经网络和配置设计优化技术实现产品族动态实施阶段的绩效最大化目标。分析产品族演进的渐变和突变过程,阐明产品族渐变过程中动态市场需求的确定性与不确定性;构建产品族动态实施阶段的绩效优化与控制研究框架,综合考虑零部件通用性的学习效应和规模效应,分析面向随机订单的产品变型配置设计对产品族成本、收益和总绩效的影响;以产品族绩效最优为目标,满足客户定制需求、产品结构和成本要求等约束条件构建配置设计模型,通过遗传算法进行求解;通过电动剪刀产品族实例验证模型的有效性,并对关键变量或参数进行敏感性分析后得到结论：通过面向随机订单的配置设计优化能够实现产品族动态实施过程某一时期内的绩效最大化目标,同时必须综合考虑影响绩效的各方面因素以确定随机订单的配置方案。

英文摘要：

To deal with the issue of performance optimization and control in the gradual evolution process of modular product family for make-to-order enterprises,the neural network and configuration optimization techniques were utilized to realize performance maximization.Both abrupt change and gradual evolution in product family evolution process were elaborated,meanwhile certainty and uncertainty of dynamic market requirement in gradual evolution process were analyzed.Performance optimization and control framework for dynamic implementation phase of product family was established,and the influence of product configuration design for random orders on product family cost,revenue and total performance was analyzed by comprehensive consideration of learning effect and scale effect from component commonality.The configuration design model was put forward with the goal of performance optimization and the constraints of customized requirements,product structure and cost requirement,and was solved by genetic algorithm.A case study of electric scissors product family was carried out to verify the effectiveness of proposed method,and the sensitivity of critical variables or parameters in the model was analyzed.The conclusion showed that the maximum performance in certain period of product family dynamic implementation process was realized with random orders oriented configuration design optimization,and the configuration scheme of random orders with consideration of performance factors should be confirmed.