不完备模糊信息系统

以不完备模糊信息系统为研究对象，建立了其中的模糊相容关系及模糊粗糙上、下近似集。在此基础上，探讨了论域上的模糊覆盖问题并提出了覆盖的3种运算形式；定义了2种新的模糊粗糙熵以讨论不完备模糊信息系统中的不确定性因素，证明了不确定因素的变化与度量强度之间的重要关系；建立了一种度量部分模糊知识依赖的新方法，获得了一些新的定理结果证明。     

模糊逻辑系统在船舶风险评估中的应用

为了合理进行船舶风险评估，提出了一种基于模糊逻辑系统的船舶风险评估方法．根据模糊逻辑系统的基本原理，建立了船舶风险评估的模糊逻辑模型；按照国家标准、规范，并结合经验建立了风险指标的模糊集合、风险矩阵厦模糊规则，然后进行了模糊推理，得到了系统的风险等级，并制定了预防风险的措施．以某艇消防系统的风险评估为例，证明了其能够合理地评估出系统的风险，可为决策提供参考，     

综合及其他

科技部指出要以信息化引导制造业今年3月,科技部在全国各省（区、市）中分批遴选制造业信息化工程示范省（区、市）工程启动。它标志着用信息化带动工业制造业发展,在国家制造业信息化工程建设的基础上,开始向地方延伸,进入一个新阶段。在经济全球化和全球信息化以及我国加入世贸组织的新形势下,中央提出了“以信息化带动工业化,发挥后发优势,实现社会生产力的跨越式发展”的战略。“制造业信息化关键技术研究及应用示范工程”（简称“制造业信息化工程”）是科技部面向国民经济建设主战场,围绕制造业和经济发展的需求,整合科技资源、加快信息技术向传统产业渗透,落实“以信息化带动工业化” 战略的重要举措。就像科技部部长徐冠华指出的,我国尚处在     

一种基于粗糙集的模糊信息融合方法及应用

将粗糙集理论和模糊逻辑技术结合起来，提出了一种基于粗糙集数据处理的模糊信息融合方法。运用粗糙集的基本理论和简约计算方法，从大量原始数据中发现精简的、概略化的规则，结合模糊逻辑推理建立一致粗糙模糊模型，并提出了对模型进行扩充与完备化的概念。脉动真空灭菌温度控制过程的仿真试验研究结果表明了所提方法的有效性和可行性。     

军校教员业绩的模糊综合评估方法研究

根据模糊综合评估理论，建立了军校教员业绩的模糊综合评估模型，对军校教员业绩的模糊综合测评方法进行了研究。并给出了一种新的确定评估指标权重的方法，使得模糊综合测评更加公正，全面，合理，准确，最后给出了测评实例，取得了比较好的效果。     

质量改进与顾客互动机制转换子模型的建立

基于模糊理论和矩阵转换思想,分别建立了在顾客需求及需求权重明确和不明确两种条件下如何将顾客需求转换为工程特征的转换子模型,以及将工程特征转换为顾客需求的转换子模型。     

区域制造业信息化工程项目管理体系研究及应用

作为制造业信息化工程的一个重要组成部分,区域制造业信息化工程包含了很多项目.为了有效地管理好这些项目,将项目管理理论运用到对区域制造业信息化项目的管理中,提出了区域制造业信息化工程项日管理体系.该体系包括单项目管理、项目群管理以及项目组合管理3个层次,研究各层次的管理内容.介绍了研究成果在重庆市"十五"制造业信息化工程中的应用情况.     

基于信息化制造系统的实践考核硬件系统研究

介绍了我国制造业信息化的发展状况以及我国制造业信息化过程中的主要问题，针对现有情况，试图找到一种高度信息化的制造生产模式。根据想要达到的生产模式的需求，选择了EPLAN作为研究的软件平台。利用这要的模式，进行了初步的探索，对实际应用中简单的电气设计及装备进行了实验，并得到了良好的结果。     

模糊命题逻辑系统中的代换定理

在舍弃了经典逻辑系统中公理L1)的基础上建立了一类模糊命题逻辑的准形式演绎系统LGR^*。并在此基础上研究了模糊逻辑系统中的代换定理，为进一步研究模糊命题逻辑系统的完备性奠定了一定的基础。     

正则半群上模糊同余的模糊核

模糊核迹方法是研究正则半群上模糊同余的重要手段，模糊核作为一个方法的组成部分成为重要的讨论对象。目的在于研究正则半群的模糊子集满足什么条件构成模糊同余的模糊核：引入一般半群上的模糊等价关系浸满一个模糊子集的概念，证明了正则半群上每个模糊同余浸满它的模糊核，给出了正则半群的模糊子集是某个模糊同余的模糊核的充要条件。     

Tolerance synthesis using second-order fuzzy comprehensive evaluation and genetic algorithm

In modern manufacturing engineering, tolerance synthesis is important because it directly effects product quality and manufacturing cost. This paper introduces a new method for tolerance synthesis of machining parts. The new method consists of three steps. First, machining parts are evaluated using the second-order fuzzy comprehensive evaluation (FCE). Then, a mathematical model for tolerance allocation is formed based on the machinability of the parts. Finally, the model is solved using the genetic algorithm (GA). The feasibility of the method is validated using a practical gearbox design example.     

A manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation for aircraft structural parts

Manufacturing of aircraft structural parts has the characteristics of multiple varieties, complex structures and small batches, which make the manufacturing resource allocation highly difficult. This paper proposes a manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation, considering multiple manufacturing resources including process planners, machine tools and cutting tools, as well as manufacturing process schemes of aircraft structural parts. Knowledge in terms of experts’ experience and historical data is used for fuzzy comprehensive evaluation. A manufacturing resource allocation model is proposed based on the analysis of manufacturing processes of aircraft structural parts. The capability of planners, the complexity of structural parts, the reliability of machine tools, the reliability of cutting tools and the correlations between manufacturing resources and structural parts are evaluated using the fuzzy comprehensive evaluation method. Multiple manufacturing resources are allocated based on the fuzzy comprehensive evaluation results. A prototype system has been implemented and a case study is used to validate the proposed approach.     

Fuzzy geometric programming approach to a fuzzy machining economics model

Machining economics is an important function of the process planning activity for manufacturing products with high quality and low cost. The machining economics model usually contains a highly non-linear objective function and equations that could be formulated as a geometric programming problem. The paper develops a solution method for deriving the fuzzy objective value of the fuzzy machining economics problem when some of the parameters in the problem are fuzzy numbers. A pair of geometric programs is formulated to calculate the lower and upper bounds of the unit production cost at possibility level α. With the ability to calculate the fuzzy objective value developed, it might help lead to a more realistic modelling effort. The developed methodology can also be applied to other engineering design problems with fuzzy numbers.     

供应商选择模糊决策方法

制造资源的全球化以及各种先进制造模式的应用使得供应商选择问题变得越来越复杂，加之供应商选择问题中包含大量的不确定因素和模糊因素。在分析供应商评价指标体系所应遵循的原则的基础上，建立了一套供应商评价一般指标体系，然后，将模糊集合论的思想和方法引入其中，提出供应商模糊综合决策方法并给出实例予以验证。     

An exact method for solving logical loops in reliability analysis

This paper presents an exact method for solving logical loops in reliability analysis. The systems that include logical loops are usually described by simultaneous Boolean equations. First, present a basic rule of solving simultaneous Boolean equations. Next, show the analysis procedures for three-component system with external supports. Third, more detailed discussions are given for the establishment of logical loop relation. Finally, take up two typical structures which include more than one logical loop. Their analysis results and corresponding GO-FLOW charts are given. The proposed analytical method is applicable to loop structures that can be described by simultaneous Boolean equations, and it is very useful in evaluating the reliability of complex engineering systems.     

Fuzzy multiple objective decision making approach to prioritize design requirements in quality function deployment

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to increase customer satisfaction by integrating marketing, design engineering, manufacturing, and other related functions of an organization. QFD focuses on delivering value by taking into account customer needs and then deploying this information throughout the development process. Although QFD aims to maximize customer satisfaction, technology and cost considerations limit the number and the extent of the possible design requirements that can be incorporated into a product. This paper presents a fuzzy multiple objective programming approach that incorporates imprecise and subjective information inherent in the QFD planning process to determine the level of fulfilment of design requirements. Linguistic variables are employed to represent the imprecise design information and the importance degree of each design objective. The fuzzy Delphi method is utilized to achieve the consensus of customers in determining the importance of customer needs. A pencil design example illustrates the application of the multiple objective decision analysis.     

A numerical algorithm of fuzzy reliability

In this paper, a computational model of fuzzy reliability focusing on solving the engineering problems with random general stress–fuzzy general strength is presented. The mathematical basis of this computational model is that the fuzzy probability can be computed with the computational method of conventional probability by use of a mathematical transition. Based on this computational model, a numerical algorithm is given which can be applied to compute the fuzzy reliability of mechanical components, sensors, electronic units, etc. This establishes a basis for the reliability analysis of systems consisting of components with fuzzy reliability. As an example, a case study about the fuzzy reliability analysis of a kind of sensor used in railway systems is provided to verify the logic of this algorithm. The computation results show that this algorithm fits the engineering experience.     

Evaluating flexible manufacturing systems using a combined multiple attribute decision making method

This paper presents a logical procedure to evaluate alternative flexible manufacturing systems for a given industrial application. The procedure is based on a combined multiple attribute decision making method using TOPSIS and AHP methods together. A ‘flexible manufacturing system suitability index’ is proposed that evaluates and ranks flexible manufacturing systems for the given industrial application. The methodology is illustrated by means of an example.     

A subjective and objective integrated multiple attribute decision making method for material selection

The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method.     

A genetic programming based fuzzy regression approach to modelling manufacturing processes

Fuzzy regression has demonstrated its ability to model manufacturing processes in which the processes have fuzziness and the number of experimental data sets for modelling them is limited. However, previous studies only yield fuzzy linear regression based process models in which variables or higher order terms are not addressed. In fact, it is widely recognised that behaviours of manufacturing processes do often carry interactions among variables or higher order terms. In this paper, a genetic programming based fuzzy regression GP-FR, is proposed for modelling manufacturing processes. The proposed method uses the general outcome of GP to construct models the structure of which is based on a tree representation, which could carry interaction and higher order terms. Then, a fuzzy linear regression algorithm is used to estimate the contributions and the fuzziness of each branch of the tree, so as to determine the fuzzy parameters of the genetic programming based fuzzy regression model. To evaluate the effectiveness of the proposed method for process modelling, it was applied to the modelling of a solder paste dispensing process. Results were compared with those based on statistical regression and fuzzy linear regression. It was found that the proposed method can achieve better goodness-of-fitness than the other two methods. Also the prediction accuracy of the model developed based on GP-FR is better than those based on the other two methods.