A rough set approach to design concept analysis in a design chain

The inherent dynamic relationships among design tasks performed concurrently at different organizations characterize the complexities of a design chain where designers with diverse expertise need to collaborate across organizational boundaries. To ensure timely completion of inter-related design tasks, metrics to facilitate the early evaluation of design concepts are crucial. The ability to evaluate and select suitable design concepts at an early stage will ensure better solutions and greater savings in time and effort further downstream. This paper proposes a new approach based on the rough set theory to design concept analysis. The approach aims at early detection of design inadequacy. A so-called information system is constructed using the information gleaned from design concepts and design capabilities, and analyzed using the rough set theory to derive a set of design rules for design concept analysis. The approach embodies a technique for handling attributes with unavailable information, which is a frequent occurrence in design. This paper presents details of the proposed approach, the novel technique, and a case study.     

A rough set enhanced fuzzy approach to quality function deployment

Quality function deployment (QFD) provides a systematic methodology to assist companies in developing quality products that are able to satisfy customer needs. The house of quality (HOQ), as the first phase of QFD, plays the most important role in product development. Frequently, fuzzy numbers are used to quantify the vagueness of linguistic terms so as to facilitate subjective assessments in the HOQ. However, the issue concerning how to determine the boundary intervals of fuzzy numbers remains unresolved. This work proposes a novel approach based on rough set theory, and introduces two concepts called rough number and rough boundary interval to address this issue. A comparative case study presented in this work shows that the proposed approach has significant advantages compared to the prevailing fuzzy number based method in processing subjective linguistic assessments in QFD.     

A hybrid approach of rough set theory and genetic algorithm for fault diagnosis

This paper proposes an integrated intelligent system that builds a fault diagnosis inference model based on the advantage of rough set theory and genetic algorithms (GAs). Rough set theory is a novel data mining approach that deals with vagueness and can be used to find hidden patterns in data sets. Based on this approach, minimal condition variable subsets and induction rules are established and illustrated using an application for motherboard electromagnetic interference (EMI) test fault diagnosis. This integrated system successfully integrated the rough set theory for handling uncertainty with a robust search engine, GA. The result shows that the proposed method can reduce the number of conditional attributes used in motherboard EMI fault diagnosis and maintain acceptable classification accuracy. The average diagnostic accuracy of 80% shows that this hybrid model is a promising approach to EMI diagnostic support systems .     

计算机辅助公差设计(CATD)中粗糙集理论及应用

对粗糙集理论和计算机辅助公差设计的一般流程进行了简单描述,粗糙集理论在基于制造成本的计算机辅助公差设计中的应用。利用粗糙集理论在同时满足支持度和可信度的基础上对规则进行筛选约简,从而提高了计算机辅助公差设计决策的准确性和合理性。     

基于粗糙集的产品概念设计知识发现

在概念设计阶段,产品设计主要是依赖于设计者的工程知识及隐含于数据库中的相关知识.为了更好地使用已经存在的数据并减少对设计者经验的依赖性,采用基于粗糙集的知识发现方法及模糊C聚类算法从数据库中抽取规则,降低专家系统知识库的复杂度,缩短产品开发周期.以实例验证了该方法的有效性.     

A grey-based rough decision-making approach to supplier selection

In this paper, we propose a grey-based rough set approach to deal with the supplier selection in supply chain management. The proposed approach takes advantage of mathematical analysis power of grey system theory while at the same time utilizing data mining and knowledge discovery power of rough set theory. It is suitable to the decision-making under more uncertain environments. We also provide a viewpoint on the attribute values in rough set decision table under the condition that all alternatives are described by linguistic variables that can be expressed in grey number. The most suitable supplier can be determined by grey relational analysis based on grey number. A case of supplier selection was used to validate the proposed approach.     

Fault diagnosis of multistage manufacturing systems based on rough set approach

Multistage manufacturing systems (MMS) have been investigated extensively. However, quality and dimensional problems are still one of the most important research topics, especially rapid diagnosis of dimensional failures is of critical concern. Due to the knowledge and experience intension nature of fault diagnosis, the diagnostic results depend on the preference of the decision makers on the hidden relations between possible faults and presented symptoms. In this paper, a rough set-based fault diagnosis method is proposed, and a rapid fault diagnosis system with rough set is developed. The novel approach uses rough sets theory as a knowledge extraction tool to deal with the data that are obtained from both sensors and statistical process control charts and then extracts a set of minimal diagnostic rules encoding the preference pattern of decision making by experts in the field. By means of knowledge acquisition, the machining process failures in MMS can then be identified. A practical system is presented to illustrate the efficiency and effectivity of our method.     

基于粗糙集的多偏好信息表达形式的群决策方法

为解决现实决策过程中存在的决策者信息偏好表达形式多样化和存在部分已知决策这两大问题,构建了一个解决多属性决策问题的基于优势粗糙集的群体决策模型。该模型针对群决策分析,提出了一种集成七种常用形式的偏好信息的方法。针对数据特点,应用改进的Sem Naive Scaler算法对模型中的粗糙集信息表加以离散化。最后,将通过优势粗糙集理论得到的规则应用于整个信息表得出各方案的排序。     

基于粗糙集的改进重要度绩效分析法

为处理属性绩效值和总体顾客满意度间的非线性关系,以及属性绩效值和属性重要度间的依赖关系,提出基于粗糙集的改进重要度绩效分析法.通过挖掘绩效值和总体顾客满意度间的数据关系,获得潜在的属性重要度.由于粗糙集无法处理连续属性,结合模糊c均值聚类算法对数据进行离散化处理.该方法克服了传统重要度绩效分析法难以准确描述绩效值、重要度和总体顾客满意度间的关系,且重要度的确定主观性强的缺陷.以水平定向钻机的维修服务为例,验证了所提方法的可行性与有效性.     

A mathematical approach to analysis and optimal design of a fixture locating scheme

In manufacturing engineering, localization accuracy is a key concern in the design of a fixture to specify a locating scheme and tolerance allocation. This paper presents a general analysis methodology that is able to characterize the effects of localization source errors based on the position and orientation of the workpiece. From this methodology, a fixture model is formulated by taking into account the overall errors among the system consisting of the workpiece and the fixture in the design of the fixture locating scheme. With this model, the locating principle and a criterion of the robust optimal design are then proposed to improve the localization quality of the fixture. Some examples are provided and allow for a detailed discussion about how to carry out the optimal design of the locating scheme. A comparative study is also made between the optimal solution and the empirical one. Finally, an experiment is made to validate the fixture locating scheme for a cylindrical workpiece. We conclude that this robust design method effectively achieves stable machining precision in workpieces.     

An integrated approach to the design and management of a supply chain system

In the modern competitive business environment, the design and management of supply chains is one of the most important and critical problems facing managers of multinational companies operating worldwide. There are three levels of decisions in a supply chain: strategic, tactical, and operational levels. The literature generally treats these decisions separately. This study defines a conceptual framework for the development of new modeling approaches for the Production Distribution Logistic System Design (PDSD) problem. In particular, the authors introduce the initial basis for the development of an innovative decision support systems platform capable of integrating the design, management, control, and optimization activities for a supply chain system.     

应用聚类和粗糙集的FPGA底层数据挖掘方法

提出了一种从XDL文件中提取现场可编程门阵列(FPGA)底层逻辑和布线资源的方法。预处理阶段通过正则表达式将原有底层逻辑文件转换为待分析的有层次属性的关系型数据库。数据挖掘阶段则根据各个层次数据内部的特性不同,采用不同的算法进行聚类来得到初步知识。通过粗糙集分析初步知识间的关系和约简属性,得出初步知识间的联系同时进一步提取出决策规则和产生式规则的知识。最后,通过规则验证器和泛化器对提取出的规则进行验证和泛化。实验结果表明,对于大型的FPGA器件,wire的逻辑最高压缩比可以达到2.88×10-4。该方法相对于底层器件有较好的通用性和交互性,适用于对不同器件族FPGA底层信息的知识提取,对深入研究FPGA的拓扑架构,提高对FPGA进行动态重配置的可控性和实现更灵活的重配置很有意义。     

定制产品需求知识重构及粗糙集分析方法

对定制产品需求知识进行多粒度分解与重构建模,然后将粗糙集理论引入需求知识处理分析过程,提出基于粗糙集理论的需求知识分析与约简方法,对需求知识的重要度进行权衡评价,从而指导产品的定制设计过程。结合项目实施,将以上方法在空分装备产品的需求知识构建与分析中进行应用,证明了所提方法的适应性和有效性。     

A five-axis rough machining approach for a centrifugal impeller

A clear trend shows that most products or mechanical components, especially those regarding aerospace applications, are designed to fit the requirements of free form surface features. When a 3-axis computer numerical controlled (CNC) machining centre is used to produce a typical centrifugal impeller, great difficulties, i.e., collisions between the cutting tool and impeller, need to be overcome. In this case, sophisticated five-axis machines have to be utilised. Presently, most commercial computer-aided manufacturing (CAM) systems for five-axis control are lacking generality, and functions for the rough tool-path generation are far less than required. The rough machining is recognised as the most important procedure influencing the machining efficiency and is critical for the success of the following finishing process. However, great difficulties are expected to arise in performing five-axis rough machining. The main objective of the present study is to overcome this problem by combining related machining technology. As a result, CL data based on the geometry model of blade and hub of the impeller are generated. Finally, the CL data is confirmed through software simulation. The results of verification prove the machining methodology and procedure to be successful.     

基于小波包与粗集的往复压缩机故障诊断方法

提出了基于小波包与粗集的往复压缩机故障诊断的新方法。该方法使故障特征提取及规则的提取都由计算机自动完成，经诊断实例表明，使用该方法可对往复压缩机进行有效的故障诊断。     

基于贝叶斯网络和粗糙集的信息融合方法研究及应用

利用贝叶斯网络处理不确定性问题能力强和粗糙集约简能够去除冗余性特征的优势,提出了一种基于贝叶斯网络和粗糙集的信息融合方法。该方法提取齿轮泵振动信号的幅域量纲参数作为来自不同传感器的多源信息,改进了特征属性约简方法,设计了贝叶斯网络分类器,构建了多故障贝叶斯网络对特征进行融合,通过最大后验概率准则识别故障类型。两次融合结果对比分析表明,特征属性约简后诊断正确率明显提高,验证了该方法的有效性和实用性。     

A morphological approach to product design in a concurrent engineering environment

The development of product design in a concurrent engineering environment requires the consideration and inclusion of life cycle factors early in the design process. This paper proposes a product design framework where these factors are considered. The phases of product design in a concurrent engineering environment include: design requirements, design functions, design alternatives, design attributes, and design environments. A five-step algorithm is proposed by which the optimal design alternative, among all the feasible alternatives, is selected. In order to illustrate the proposed framework, the design of a braking system is presented in each phase. A morphological approach to product design is proposed that consists of two related morphologies. Morphology 1 addresses the innovative aspect of product design. Morphology 2 considers the computational and optimisation aspect of product design. In conclusion, an integrated approach which reconciles both morphologies is suggested.     

A variable precision rough set based modeling method for pulsed GTAW

Modeling is an important step both for quality and shaping control of the arc welding process. Current modeling methods have made great advances in the field of arc welding, however they all posses certain limitations. It is due to these limitations that we created the variable precision rough set (VPRS) based modeling method. The VPRS modeling has been shown to be both a more efficient and reliable modeling method for the arc welding process due to its ability to account for the character of the welding media. The method was used to produce a dynamic predictive model for pulsed gas tungsten arc welding (GTAW). Results showed that the VPRS modeling method was able to sufficiently acquire knowledge during welding practices. In addition, comparison of VPRS model with classic rough set model and BP neural network model showed that VPRS model was more stable and could predict the unseen data better than classic RS model. Moreover, the VPRS model owns similar precision with neural network model, but has better understandability.     

A new approach to PLC software design

This paper presents a model-based approach to PLC software development. The essence of this approach is the introduction of a new procedural modeling language called ProcGraph. In contrast to commonly used methods, ProcGraph deals with the procedural aspect of the control system and allows software specification at a higher level of abstraction. The modeling language has been supported with the development of a software tool which facilitates graphical model design and automatic code generation. The specification notation has been tested in the development of software for industrial applications. The supporting tool has been tested in a laboratory environment.     

A neuro-fuzzy based approach to affective design

Satisfying customers’ affective needs is nowadays seen as a key point to designing a successful product. To ensure this, the relations between physical form elements and affective responses regarding the product should be quantified. In this article, a novel systematic approach is proposed to overcome this problem by representing the relation structure with “IF THEN” type fuzzy rules. A neuro-fuzzy method, named as NEuro-Fuzzy CLASSification (NEFCLASS), is used to extract a rule base with the aid of semantic differential scale (SDS), multi-criteria group decision making (MCGDM) and grey relational analysis (GRA). To prove the applicability of the proposed approach, a case study has been conducted on mobile phone design. Results show that the suggested approach is useful to assist designers to create products satisfying affective needs of customers.