基于产品族的产品定义中智能技术的应用研究
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摘要
大规模定制是企业在日趋激烈的市场竞争中获胜的有效途径之一。通过这种生产模式,企业可以以较低成本满足多样化的客户需求,提升利润空间。在大规模定制的设计过程中,能否正确进行产品定义是企业能否赢得市场的关键。要实现此阶段的设计任务,关键是要合理、有效地实现需求的分析和转化。围绕这些关键问题,本论文的主要内容如下:
(1)对大规模定制的经济效益,研究现状和趋势进行了回顾,分析和讨论了其中的关键技术,在此基础上提出了全文的研究思路。
(2)对产品定义的研究现状进行了总结,包括客户需求的获取、表达和预处理方法,功能需求的表达和分析方法,以及实现两者转化的方法和技术。
(3)提出了基于两种知识的产品族定义模型,使用基于知识的神经网络(KBANN)从两类知识源中学习,实现客户需求向产品族的映射。KBANN是一种结合了演绎和归纳两种学习方式的智能方法,它可以同时从数据库和规则库中获取知识。在此基础上,使用决策树算法(DT)将网络中隐含的知识转化为易于理解的规则,帮助工程师了解客户对产品族的偏好。
(4)提出了面向产品定义阶段的设计检索模型。此模型同时考虑客户需求和产品功能需求的相似性,使用模糊ARTMAP神经网络(FAM)实现历史设计案例的智能检索。在新的客户需求到来时,此方法可以迅速有效地找到合适数量的相似设计案例,作为设计的起点。
(5)以数据挖掘为工具,挖掘客户需求属性和产品功能需求属性之间复杂的映射关系。对于挖掘得到的关联规则,采用四个指标来衡量其有效性:支持度、置信度、有趣度和可理解度。为实现对复杂、高维的设计空间的搜索,本研究使用基于帕累托的遗传算法来完成多目标关联规则挖掘任务。
本文以客户需求为出发点研究大规模定制中的产品定义,丰富了大规模定制的设计方法,降低了设计所需成本和时间,进而提高了企业的经济效益。
In the current scenario of globalization and strong competitive environment, mass customization (MC) has become an effective method for companies. It can satisfy wide spectrum of customer demands with low cost, which results in high profit. During the design stage of MC, product definition is one of the essential premises for successful product development. It requires design engineers to catch up with the voice of customers and translate it into product specifications effectively. The main concern of this paper is focused upon the following aspects:
(1) Review the background of mass customization, including economic effect, research status and trend. Based on the discussion of the key issues in MC, the research approach is presented.
(2) Review the research activities of product definition, including acquisition, representation and preprocessing of customer needs, representation and analysis of functional requirements, methodology of mapping individual customer requirement into product specifications, etc.
(3) Propose a model of product family identification based on two kinds of knowledge. Using knowledge-based artificial neural network (KBANN), this model can learn from two knowledge resources and realize the mapping relationship between customer needs and product family. KBANN, combining the merits of inductive and deductive methods, can learn knowledge from data base and rule base. On the basis of KBANN, this paper utilize classification and regression tree (CART) to translate the knowledge store in KBANN into comprehensible rules, which can help engineers understand customer preference to different product families.
(4) Propose a fuzzy intelligent design retrieving system for product definition. It employs fuzzy ARTMAP (FAM) neural network as its key technique to retrieve reference designs based on the similarity of customer requirements and functional requirements. FAM learns from historical transaction records. For newly emerging customer requirements, the system is able to effectively retrieve reference designs. Design engineers can then develop new products by evaluation and modification of the existing ones.
(5) Present the framework of product specification identification base on data mining method. It mines the complex relationship between customer need attributes and functional attributes of product. Four objectives, support, confidence, interestingness and comprehensibility, are used for evaluating the extracted rules. To solve such a multi-objective problem, a Pareto-based GA is utilized to perform the rule extraction.
Take customer's demand as the starting point of management, this article investigated the product definition in mass customization. It improves the design methodology of MC, reduces time and cost during the design process, and thus increases the profits of companies.
(1)对大规模定制的经济效益,研究现状和趋势进行了回顾,分析和讨论了其中的关键技术,在此基础上提出了全文的研究思路。
(2)对产品定义的研究现状进行了总结,包括客户需求的获取、表达和预处理方法,功能需求的表达和分析方法,以及实现两者转化的方法和技术。
(3)提出了基于两种知识的产品族定义模型,使用基于知识的神经网络(KBANN)从两类知识源中学习,实现客户需求向产品族的映射。KBANN是一种结合了演绎和归纳两种学习方式的智能方法,它可以同时从数据库和规则库中获取知识。在此基础上,使用决策树算法(DT)将网络中隐含的知识转化为易于理解的规则,帮助工程师了解客户对产品族的偏好。
(4)提出了面向产品定义阶段的设计检索模型。此模型同时考虑客户需求和产品功能需求的相似性,使用模糊ARTMAP神经网络(FAM)实现历史设计案例的智能检索。在新的客户需求到来时,此方法可以迅速有效地找到合适数量的相似设计案例,作为设计的起点。
(5)以数据挖掘为工具,挖掘客户需求属性和产品功能需求属性之间复杂的映射关系。对于挖掘得到的关联规则,采用四个指标来衡量其有效性:支持度、置信度、有趣度和可理解度。为实现对复杂、高维的设计空间的搜索,本研究使用基于帕累托的遗传算法来完成多目标关联规则挖掘任务。
本文以客户需求为出发点研究大规模定制中的产品定义,丰富了大规模定制的设计方法,降低了设计所需成本和时间,进而提高了企业的经济效益。
In the current scenario of globalization and strong competitive environment, mass customization (MC) has become an effective method for companies. It can satisfy wide spectrum of customer demands with low cost, which results in high profit. During the design stage of MC, product definition is one of the essential premises for successful product development. It requires design engineers to catch up with the voice of customers and translate it into product specifications effectively. The main concern of this paper is focused upon the following aspects:
(1) Review the background of mass customization, including economic effect, research status and trend. Based on the discussion of the key issues in MC, the research approach is presented.
(2) Review the research activities of product definition, including acquisition, representation and preprocessing of customer needs, representation and analysis of functional requirements, methodology of mapping individual customer requirement into product specifications, etc.
(3) Propose a model of product family identification based on two kinds of knowledge. Using knowledge-based artificial neural network (KBANN), this model can learn from two knowledge resources and realize the mapping relationship between customer needs and product family. KBANN, combining the merits of inductive and deductive methods, can learn knowledge from data base and rule base. On the basis of KBANN, this paper utilize classification and regression tree (CART) to translate the knowledge store in KBANN into comprehensible rules, which can help engineers understand customer preference to different product families.
(4) Propose a fuzzy intelligent design retrieving system for product definition. It employs fuzzy ARTMAP (FAM) neural network as its key technique to retrieve reference designs based on the similarity of customer requirements and functional requirements. FAM learns from historical transaction records. For newly emerging customer requirements, the system is able to effectively retrieve reference designs. Design engineers can then develop new products by evaluation and modification of the existing ones.
(5) Present the framework of product specification identification base on data mining method. It mines the complex relationship between customer need attributes and functional attributes of product. Four objectives, support, confidence, interestingness and comprehensibility, are used for evaluating the extracted rules. To solve such a multi-objective problem, a Pareto-based GA is utilized to perform the rule extraction.
Take customer's demand as the starting point of management, this article investigated the product definition in mass customization. It improves the design methodology of MC, reduces time and cost during the design process, and thus increases the profits of companies.
引文
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