制造单元构建的关键技术研究
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摘要
我国目前存在着大量的中小企业,采用小批量、多品种的生产模式。如何用有限成本提供个性化、高质量的产品是这些制造企业存活的关键。受成组技术思想启发的单元制造系统(Cellular Manufacturing System,CMS)是解决该问题的有效途径之一,而单元构建(Cell Formation,CF)是决定单元制造系统成败的第一步,也是最重要的一步。
针对单元构建中单元分组数的确定、单元构建方案的生成、CF候选方案评价与选择等关键技术问题,本文对其展开研究,具体内容如下:
针对现有方法单元分组数不确定的问题,提出了一种单元构建过程中单元分组数的确定方法。首先分析了权重指数、聚类中心和度量方式等不同对聚类效果、聚类中心和隶属度的影响,根据问题的规模合理选择权重指数和聚类中心及度量方式的确定方法;其次采用了模糊c均值(FCM)算法计算在指定单元分组数范围内零件间的隶属度和聚类中心,在此基础上计算评价聚类性能的四个指标值;以综合性能指标最优确定最佳的单元分组数,从而获得最佳的单元分组解。
针对单元构建问题具有组合优化、NP完全问题的特点,提出了一种基于偏好的单元构建多目标优化方法。首先研究了现有单元构建问题的表示模型,探讨了制造资源的利用与经济效益间的关系,以单元的相似度最大化、加工费用最小化、加工时间最小化和设备投资最小化为目标,建立了适合零件族和设备组并行生成的单元构建优化数学模型;其次针对单元构建问题的组合特征及其多目标和多约束的特点,研究了多目标优化问题对目标和约束的处理方法,采用层次分析法科学地确定各分目标的权重,将所需满足的约束看作一个新目标,采用进化算法进行求解,以每代不满足约束个体所占比例作为该目标的权重,提出了面向制造单元构建的偏好进化算法,同时处理目标和约束,提高了解的质量和计算效率。
针对现有单元构建评价方法仅以静态指标作为评价依据,未综合考虑动态指标和制造企业实际情况的问题,提出了一种基于情境的单元构建方案的评价选择方法。首先分析了在不同企业情境下影响单元构建方案选择的主要因素,确定适当的评价性能指标,以利于符合企业生产资源合理利用的要求;其次利用模糊层次分析法对不同领域专家和评价性能指标进行相应权重的分配,领域专家按各自负责的指标进行评判,以形成模糊性能矩阵;针对领域专家评判时的可信度和潜在风险问题,采用模糊数α截集和β因子的形式表示可信度和潜在风险,采用候选方案与正负理想解相对距离的测度方式进行候选单元构建方案排序的方法,进而得到了符合企业资源合理利用的最佳单元分组方案。
基于上述单元构建基本理论和关键技术,开发了制造单元构建原型系统,验证了文中提出的单元分组数的确定方法、基于偏好单元构建的优化设计方法和支持单元构建候选方案的评价与选择方法在实际工程应用中的适用性。
There are large numbers of small-medium enterprises, which adopt multiple products and small batch production mode, in our country at present. How to provide the individuation and high quality products using limit cost is the key of survive for manufacturing enterprise. Inspired by principles and advantages of the group technology (GT) philosophy, cellular manufacturing system (CMS) designed for lot size production has recently became popular, and with the modest ancillary support can approach the economical benefits of mass production systems. Cell formation (CF) is the first and important stage in designing a CMS in order to form a set of manufacturing cells.
The method of determining the cell number of cell formation, the optimal approach of cell formation for CMS, evaluation and selection of cell formation individuals and development of software platform are deeply discussed in this dissertation. The main work is described as follows:
The approach to determining the optimal cell number of manufacturing cell formation is presented. The difference of weighting exponent, cluster center and metrics how to have an impact upon the clustering results and membership function are studied in the beginning. Afterwards, a method to determine the optimal m value is given. Two-order partial derivative of the objective function for FCM is calculated, and the variational weighting exponent m is obtained that can prevent the parameter from being the unique value and play an important role in the process of fuzzy clustering. Moreover, in order to avoid a single validity index can not assess correctly, partition coefficient (PC), classification entropy (CE), Fukuyama and Sugeno (FS) and Xie and Beni (XB) are considered as multi-performance indexes to evaluate the cluster validity, and then an optimal number c is chosen based on these validity measures.
A multi-objective optimization method based on preference of cell formation is proposed. Firstly, the representation models of cell formation problem in existence are investigated; further, the relation between the utilization of manufacturing resource and benefit is discussed. In this study, the established mathematic optimized model considers the total similarity, total processing cost, total processing time and total investment. Secondly, due to the combinatorial nature of cell formation problem and the characteristics of multi-objective and multi-constrain, a novel method of evolutionary algorithm with preference is proposed. The analytic hierarchy process (AHP) is adopted to determine scientifically the weights of the sub-objective functions. The satisfaction of constraints is considered as a new objective, the ratio of the population which doesn't satisfy all constraints is assigned as the weight of new objective. In addition, the self-adaptation of weights is applied in order to converge more easily towards the feasible domain. Therefore, both features multi-criteria and constrains are dealt with simultaneously. Finally, an example is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method in designing the manufacturing cells.
A decision support system based on scenario for multi-attribute selection of cell formation schemes is developed. The system combines fuzzy set theory and group decision with the AHP to decrease the influence of decision makers' subjective preferences and control the uncertain and imprecise variations during evaluation process. The importance weights of different criteria and the ratings of various alternatives under different criteria are evaluated in linguistic terms represented by fuzzy numbers. The intangible criteria and criteria weights are determined by group decision which can integrate all decision makers' subjective opinions based on different scenarios. Besides, fuzzy value of each of the alternatives is computed by making use of standard fuzzy arithmetic. The degree of confidence and risk index are also joined, so that decision makers can adjust them to match real context. Finally, a case of individual selection about cell formation is given, and the simulation results demonstrate the proposed approach is both effective and robust. The system helps user select preferred individual from candidates.
On the basis of theoretic research above, the prototype system of manufacturing cell formation is developed. The successful implementation in enterprise testifies the feasibility of several theories and methods presented in this dissertation.
针对单元构建中单元分组数的确定、单元构建方案的生成、CF候选方案评价与选择等关键技术问题,本文对其展开研究,具体内容如下:
针对现有方法单元分组数不确定的问题,提出了一种单元构建过程中单元分组数的确定方法。首先分析了权重指数、聚类中心和度量方式等不同对聚类效果、聚类中心和隶属度的影响,根据问题的规模合理选择权重指数和聚类中心及度量方式的确定方法;其次采用了模糊c均值(FCM)算法计算在指定单元分组数范围内零件间的隶属度和聚类中心,在此基础上计算评价聚类性能的四个指标值;以综合性能指标最优确定最佳的单元分组数,从而获得最佳的单元分组解。
针对单元构建问题具有组合优化、NP完全问题的特点,提出了一种基于偏好的单元构建多目标优化方法。首先研究了现有单元构建问题的表示模型,探讨了制造资源的利用与经济效益间的关系,以单元的相似度最大化、加工费用最小化、加工时间最小化和设备投资最小化为目标,建立了适合零件族和设备组并行生成的单元构建优化数学模型;其次针对单元构建问题的组合特征及其多目标和多约束的特点,研究了多目标优化问题对目标和约束的处理方法,采用层次分析法科学地确定各分目标的权重,将所需满足的约束看作一个新目标,采用进化算法进行求解,以每代不满足约束个体所占比例作为该目标的权重,提出了面向制造单元构建的偏好进化算法,同时处理目标和约束,提高了解的质量和计算效率。
针对现有单元构建评价方法仅以静态指标作为评价依据,未综合考虑动态指标和制造企业实际情况的问题,提出了一种基于情境的单元构建方案的评价选择方法。首先分析了在不同企业情境下影响单元构建方案选择的主要因素,确定适当的评价性能指标,以利于符合企业生产资源合理利用的要求;其次利用模糊层次分析法对不同领域专家和评价性能指标进行相应权重的分配,领域专家按各自负责的指标进行评判,以形成模糊性能矩阵;针对领域专家评判时的可信度和潜在风险问题,采用模糊数α截集和β因子的形式表示可信度和潜在风险,采用候选方案与正负理想解相对距离的测度方式进行候选单元构建方案排序的方法,进而得到了符合企业资源合理利用的最佳单元分组方案。
基于上述单元构建基本理论和关键技术,开发了制造单元构建原型系统,验证了文中提出的单元分组数的确定方法、基于偏好单元构建的优化设计方法和支持单元构建候选方案的评价与选择方法在实际工程应用中的适用性。
There are large numbers of small-medium enterprises, which adopt multiple products and small batch production mode, in our country at present. How to provide the individuation and high quality products using limit cost is the key of survive for manufacturing enterprise. Inspired by principles and advantages of the group technology (GT) philosophy, cellular manufacturing system (CMS) designed for lot size production has recently became popular, and with the modest ancillary support can approach the economical benefits of mass production systems. Cell formation (CF) is the first and important stage in designing a CMS in order to form a set of manufacturing cells.
The method of determining the cell number of cell formation, the optimal approach of cell formation for CMS, evaluation and selection of cell formation individuals and development of software platform are deeply discussed in this dissertation. The main work is described as follows:
The approach to determining the optimal cell number of manufacturing cell formation is presented. The difference of weighting exponent, cluster center and metrics how to have an impact upon the clustering results and membership function are studied in the beginning. Afterwards, a method to determine the optimal m value is given. Two-order partial derivative of the objective function for FCM is calculated, and the variational weighting exponent m is obtained that can prevent the parameter from being the unique value and play an important role in the process of fuzzy clustering. Moreover, in order to avoid a single validity index can not assess correctly, partition coefficient (PC), classification entropy (CE), Fukuyama and Sugeno (FS) and Xie and Beni (XB) are considered as multi-performance indexes to evaluate the cluster validity, and then an optimal number c is chosen based on these validity measures.
A multi-objective optimization method based on preference of cell formation is proposed. Firstly, the representation models of cell formation problem in existence are investigated; further, the relation between the utilization of manufacturing resource and benefit is discussed. In this study, the established mathematic optimized model considers the total similarity, total processing cost, total processing time and total investment. Secondly, due to the combinatorial nature of cell formation problem and the characteristics of multi-objective and multi-constrain, a novel method of evolutionary algorithm with preference is proposed. The analytic hierarchy process (AHP) is adopted to determine scientifically the weights of the sub-objective functions. The satisfaction of constraints is considered as a new objective, the ratio of the population which doesn't satisfy all constraints is assigned as the weight of new objective. In addition, the self-adaptation of weights is applied in order to converge more easily towards the feasible domain. Therefore, both features multi-criteria and constrains are dealt with simultaneously. Finally, an example is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method in designing the manufacturing cells.
A decision support system based on scenario for multi-attribute selection of cell formation schemes is developed. The system combines fuzzy set theory and group decision with the AHP to decrease the influence of decision makers' subjective preferences and control the uncertain and imprecise variations during evaluation process. The importance weights of different criteria and the ratings of various alternatives under different criteria are evaluated in linguistic terms represented by fuzzy numbers. The intangible criteria and criteria weights are determined by group decision which can integrate all decision makers' subjective opinions based on different scenarios. Besides, fuzzy value of each of the alternatives is computed by making use of standard fuzzy arithmetic. The degree of confidence and risk index are also joined, so that decision makers can adjust them to match real context. Finally, a case of individual selection about cell formation is given, and the simulation results demonstrate the proposed approach is both effective and robust. The system helps user select preferred individual from candidates.
On the basis of theoretic research above, the prototype system of manufacturing cell formation is developed. The successful implementation in enterprise testifies the feasibility of several theories and methods presented in this dissertation.
引文
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