基于数据驱动的生产质量决策支持系统模型的研究

基于生产过程实时监控系统获取的大量质量监测数据，提出了以数据仓库为核心，数据挖掘为驱动的企业生产质量决策支持系统模式，以粗糙集理论为主体技术进行数据挖掘，针对实际生产过程的特性，将经典粗糙集不可分辨关系进行扩展，引入相近和相似关系，可以有效处理实际生产过程中数据的背景噪音和数据不完备的状况，采用遗传算法解决粗糙集理论中知识简约的NP完全问题，挖掘出的各个生产过程的相互联风规则，通过人机一体优化策略，使决策者获得真正需要的知识。     

面向大规模定制的网络化群体智能决策支持系统

分析了大规模定制模式下决策问题的协同性、科学性和快速响应需求,提出了面向大规模定制的群体智能决策支持系统,用以支持多决策者之间通过虚拟组织的形式开展迅速、科学、有效的群体决策。该系统采用B／S构架,由数据源、集成数据平台、应用服务层、网络通讯平台和用户接口5层结构组成。在数据库／数据仓库、模型库、方法库和知识库的基础上,开发了案例库系统、方法引导器、模型选择器和数据挖掘工具等人工智能部件,增强了系统的实用性和易用性。给出了使用该系统进行客户定制订单群决策的应用实例。     

A decision support system for rapid one-of-a-kind product development

A decision support system (DSS) is a specific class of computerized information systems that support decision-making activities. Such a system has become paramount in supporting manufacturing activities with the development of World Wide Web (WWW) technology in recent years. The research and development of a knowledge-based DSS dedicated to rapid one-of-a-kind products (OKPs), however, has, to the author’s knowledge, rarely been directly studied. This work presents a knowledge-based DSS for supporting decision-making activities in developing OKPs using broad knowledge base content. The underlying architecture of the proposed system is a system that manages and optimizes the data, information and knowledge in the product development process. A knowledge structure model is proposed in this paper, and a comprehensive set of expert knowledge and analytical/numerical methods are integrated into the system to automate intelligent decision-making. Case studies have shown that the knowledge-based DSS is able to help OKP companies develop new products more quickly by sharing optimization tools, information and knowledge to reduce possible errors and rework.     

A decision logic schema of process planning using backward chaining reasoning

Decision logic of process planning is one of the most difficult issues in the research on computer-aided process planning (CAPP), and also a bottleneck hampering the process of pragmatization and commercialization of CAPP. A proper methodology for decision logic of process planning is essential for describing or specifying the various decisions associated with combinations of conditions in process planning. This paper presents a decision logic schema of process planning using backward chaining reasoning in mathematical logic to address process reasoning formalization in automated process planning, which is based on a meta-modeling paradigm of the manufacturing resources [19]. The meta-modeling paradigm combines mapping theory with the first- & second-order logic in mathematical logic to address modeling the manufacturing resources and to provide a methodology for the extraction of specific process knowledge. The meta-modeling paradigm lays the foundation for the proposed decision logic schema with specific process knowledge while the decision logic schema is the extension and application of the results from the meta-modeling paradigm. The decision logic schema provides a systematic methodology for the decision-making process and inference mechanism in process planning from the global viewpoint, which can be applied to eliminate the variability from the planners’ judgement and experience. Finally, an application example is used to illustrate the decision logic schema.     

Fuzzy multiple criteria decision model for the evaluation of AMS

The economic justification of advanced manufacturing systems is very important today, but it is difficult to obtain sound answers using ordinary financial techniques, such as discounted cash flow (DCF) measures. These techniques over-simplify investment decisions, because they are unable to account for the strategic issues and for the uncertainty of financial flows present in AMS investments. In this paper, a fuzzy multiple criteria decision model is presented. A fuzzy set theory approach is suggested because it is able to tackle both the linguistic assessments necessary for strategic issues, and the uncertainty of financial flows. The proposed method calculates a fuzzy integrated index that brings together both the qualitative and quantitative, but uncertain, issues. Ranking the investment alternatives based on this index, the analyst can determine which option is more suited to the company's objectives.     

A Synergistic Framework for Evaluating Business Process Improvements

The evaluation, selection, or justification of business process improvements, or business process reengineering efforts, is similar to many strategic initiatives and their justification methodologies. This similarity arises from the fact that there are multiple factors that need to be considered, many of which have long-term and broad implications for an organization. There are many intangible measures and qualitative concerns when evaluating business process improvements. These improvements necessarily have to link to the strategic objectives of the organization. The proposed methodological framework will involve the synthesis of the analytical network process and data envelopment analysis. These two techniques, when used together, can provide subjective and objective evaluations for managerial decision makers. An illustrative example provides some insights into the application of this methodology. Additional issues and research questions are also identified.     

基于PDM的工艺知识库管理方法研究

为了完成基于产品数据管理的计算机辅助工艺设计系统中工艺知识库管理系统的开发,提出了一种基于产品数据管理的工艺知识库管理方法。工艺知识包括工艺资源信息、工艺实例和工艺决策知识三类,据此构建了基于产品数据管理的工艺知识库管理系统的体系结构,提出了基于物料清单的工艺实例表示方法和检索方法、基于数据库中view技术的工艺资源信息的检索方法和基于工艺决策知识三视图模型的工艺决策知识库的维护策略。最后,介绍了样机系统的应用。     

The optimization of attribute selection in decision tree-based production control systems

This study develops a learning-based production control system (PCS) to support a manufacturing system to make on-line decisions that are robust in the face of various production requirements. Selecting essential system attributes (or features) based on various production requirements to construct PCS knowledge bases is a critical issue because of the existence of a large amount of shop floor information in a manufacturing system. However, a classical decision tree (DT) learning approach to construct dynamic dispatching knowledge bases does not consider the optimal subset of system attributes in the problem domain. To resolve this problem, this study develops a hybrid genetic algorithm/decision tree (GA/DT) approach for DT-based PCS. The hybrid GA/DT approach is used to simultaneously evolve an optimal subset of system attributes and determine learning parameters of the DT from a large set of candidate manufacturing system attributes according to various performance measures. For a given feature subset and learning parameters of a DT decoded by a GA, a DT was applied to evaluate the fitness in the GA process and to generate the PCS knowledge base. The results demonstrate that the proposed GA/DT-based PCS has, according to various performance criteria, a better long term system performance than those obtained with classical DT-based PCS and the heuristic individual dispatching rules, according to various performance criteria.     

An analytic network process-based multicriteria decision making model for a reverse supply chain

Reverse logistics has emerged as an important dimension for organizations to build their strategic advantage. Part of this effort relies on potentially outsourcing these activities. With this competitive issue in mind, this paper presents a multistep process to select a third-party reverse logistic provider (3PRLP). Criteria for evaluation are drawn from the literature and practical input from experts and decision makers within a case company. The process requires that an initial screening of criteria is completed through the analytical hierarchy process. The second stage of the process, 3PRLP selection, is completed using the analytic network process. An illustrative example is provided to demonstrate the solutions obtained by the proposed process within an automobile case company. A sensitivity analysis is also provided for a robustness check. The results obtained from the proposed model provide some interesting managerial implications to the case company and others wishing to apply the process.     

An Efficient Expert System for Machine Fault Diagnosis

An efficient expert system for machine fault diagnosis is developed. A new search method is proposed in this system to improve the efficiency of the diagnostic process. First of all, a diagnostic tree (a decision tree) is built by domain experts according to the functions of the devices in the machine. Then, the diagnostic priorities of nodes (devices) in the tree are determined based on a fuzzy group multiple attribute decision making method. A meta knowledge base for fault diagnosis is generated automatically based on the determined priorities to guide the diagnostic process. After that, a domain knowledge base that hypothesises possible faults for each device in the tree is generated by domain experts and/or manuals. At last, the inference process starts based on the meta knowledge base and hypothesises which device is the possible cause of failure. To validate the system performance, an illustrative example (VCR troubleshooting) is presented for demonstration purposes.     

Knowledge management to support product development in cold roll-forming environment

Knowledge and information management has focused on how available knowledge is exploited to enhance organisational performance especially in marketing, costing, design, and manufacturing activities; however, there is limited information on how knowledge acquired during product development can be utilised to provide decision support throughout the product life cycle. Existing knowledge management systems do not seem to provide information on well-known manufacturing constraints and product attributes identified during product development. Secondly, such systems do not provide the means to identify, capture, formalise, present and utilise tacit knowledge which have a major impact on overall product development process. Consequently, knowledge and experiences gained from existing projects are sometimes poorly documented and therefore are not available for reuse in future projects. An organised transfer of knowledge from previous projects will no doubt enhance the quality, efficiency, cost, and time to market of new products and processes. The study carried out here has developed a knowledge management framework to support product development in a cold roll-forming manufacturing environment. Process modelling supported by Integrated Definition for Function Modeling methodology was applied to guide the identification of information and knowledge required to support product development and also for effective decision making in routine cold roll forming.     

基于粗糙集知识获取的转子轴承系统故障诊断知识库构造研究

利用粗糙集理论从信息系统中知识获取与知识发现的功能，对转子轴承系统状态监测与故障诊断系统中知识库构造进行了研究。通过对粗糙集理论用于智能决策过程和诊断监测数据特性的分析，获得了数据表中连续属性值离散化映射、条件属性集与决策属性集记录的完备性是诊断知识获取与知识发现前提条件的结论。建立了基于粗糙集方法从数据库中知识获取和知识发现的诊断知识库模型，设置的连续属性值离散化步骤具有实现知识库决簏规则扩展的特点。     

决策支持系统的模型库和方法库的探索

简要介绍了决策支持系统（DSS）的产生和发展,论述了决策支持系统的系统结构和3个技术层次,辨析了DSS与管理信息系统（MIS）的区别和联系,重点研究了基于DSS的模型库和方法库的设计与实现。阐述了模型库系统的3个组成部分和方法库系统的体系结构,并对模型库与方法库之间的关系调用问题进行了详细分析。提出了模型库系统调用方法库中方法的实现方案。本文介绍的内容,对DSS应用具有一定的参考价值。     

Object-based knowledge bases in automatic manufacturing environments

A manufacturing system is a very complex network of physical activities, decision making and information flows. Hence the complexity of the design and the integration of such a system increases with increases in the degree of automation. In this paper the authors propose to use the framework of an object-oriented knowledge base as the basis to, organise the knowledge in an automatic manufacturing environment. Such systems can provide significant advantages in terms of knowledge management, integrity control, object abstraction, design abstraction, and very high level programming. The power of this framework is illustrated in detail in the context of process planning, which is one of the major components of an automatic manufacturing environment. This research is supported by the National Science Foundation under grant number CDR-85-00022.     

碟簧产品经营决策辅助系统的研究

本语文根据碟簧产品的经营特点,探讨了对集产品方案设计、工艺规划、成本估算及经营效益分析等于一体的产品经营决策辅助系统的开发建立,以用于辅助支持企业在产品经营决策阶段就能设计规划出产品的最优经营过程,并及时作出有效、可靠的产品经营决策。     

An Improved Rough Set Approach to Design of Gating Scheme for Injection Moulding

The gate is one of the most important functional structures in an injection mould, as it has a direct influence on the quality of the injection products. The design of a gating scheme includes the selection of the types of gate and calculation of the sizes and determination of the location, which depends heavily on prior experience and knowledge and involves a trial-and-error process. Due to the vagueness and uncertainty in the design of a gating scheme, classical rough set theory is not effective. In this paper, a fuzzy rough set model is proposed, which is not based on equivalent relationships but on fuzzy similarity relationships. An inductive learning algorithm based on the fuzzy rough set model (FRILA) is then presented. Compared to decision tree algorithms, the proposed algorithm can generate fewer classification rules; moreover, the generated rules are more concise. Finally, an intelligent prototype system for the design of a gating scheme based on an induced fuzzy knowledge base is developed. An illustrative example proves the effectiveness of the proposed method.     

飞机结构件数控加工工艺知识组织与管理

介绍飞机结构件数控加工工艺决策专家系统中，工艺决策知识的组织与管理的思想和方法，并讨论了知识库的一致性维护问题。     

Developing a knowledge-based injection mould cost estimation system by decision tables

This paper presents a knowledge-based costing system (DTMOLD-1) for an electrical appliance manufacturer to assist mould cost estimation at the early design stage. The system is developed in the form of decision tables. Through the use of decision tables, numerous interrelated variables and technical data in the injection mould cost estimation process are organised and presented. When the features of a plastic part are input, the DTMOLD-1 will generate an estimated cost of the injection mould required to produce the part. The rationale behind the system as well as the methodologies used in the developmental process are discussed.     

CAPP专家系统中工艺决策的实现

结合杭州叉车总厂ＨＣ－ＣＡＰＰ工程应用项目,构造了一种基于知识推理的创成式ＣＡＰＰ专家系统模型。原型系统中,工艺设计、机床选择、刀具选择、夹具等知识库的管理独立于推理机,不仅为知识库管理、推理机改进、零件特征排序、知识库系统移植等提供方便,而且系统采用ＲＤＢ（关系型数据库管理）技术、ＯＤＢＣ（开放式数据库互连）技术,为ＣＡＰＰ、ＣＡＤ、ＮＣＰ（数控编程）子系统内部不同模式数据交换提供接口。     

多转子系统弯、扭耦合作用时临界转速的研究

导出了轴的弯、扭耦合传递矩阵和轴间的弯、扭耦合矩阵。在文［１］的基础上编制了多转子弯、扭耦合临界转速的通用程序。采用等效刚度、等效阻尼方法编制了多转子弯、扭耦合稳态不平衡响应的通用程序；研究了扭振、畸形结构、油膜刚度、油膜阻尼等因素对临界转速的影响；并对某型发动机转子进行了计算和分析