Research of Enterprise Resource Management Supporting Networked Manufacturing

1Introduction Withthecomingoftheknowledge driveneconomy,manufacturingisdevelopingintermsofdigitization,flexibility,intelligence,integration,agilityandnetworking[1,2].Networkedmanufacturingmeansthat manufacturingenterpriseslaunchaseriesofactivitiessuchasproductdesign,manufacture,marketing andmanagementinthewayofnetworkedtechnology[3].Byanalyzingthecorrelativeresearchabroadand domestic,wemaysummarizethedevelopmenttrendofnetworkedmanufacturingasfollows[4～6]:(1)Thescopeofanetworkedmanufacturingsy…     

Research on resources optimisation deployment model and algorithm for collaborative manufacturing process

Agility is the competitive advantage in the global manufacturing environment. It is believed that agility can be realised by networked manufacturing resource optimisation deployment. However, this is a challenge to us now. To solve this question, logical manufacturing unit and logical manufacturing process are proposed to decompose and model the networked manufacturing task, and networked manufacturing resources are organised and modelled based on physical manufacturing unit. During the deployment of manufacturing resources to the task, many factors should be taken into consideration. Of these, manufacturing cost, time and quality are the most important factors. In this paper, before these factors are considered, networked manufacturing resources pre-deployment is carried out to find the candidate manufacturing resources on the basis of manufacturing abilities. Then, resources optimisation deployment is modelled as a multi-objectives optimisation. This optimisation problem is solved based on genetic algorithm after transforming the multi-objectives optimisation problem to a single objectives optimisation problem. Although we may not find the optimal solution for the problem by genetic algorithm, the better and feasible solution is produced. Thus, this algorithm is efficient and can be applicable to practical problem. At last, an illustrative example is presented to show the application of the proposed algorithm.     

The Networked Manufacturing Resources Optimizing Configuration System and Its Partners Selection Method

1 IntroductionNetworked manufacturing is the future trend in the manufacturing industry, and it becomes the focusof research today. One of the key problems in networked manufacturing is howto quickly and exactlyconstruct a dynamic and complementary networked manufacturing alliance from the numerous manu-facturers and suppliers based on the manufacturing requirement of the products, so to realize the re-organization, re-configuration and dynamic optimization of the manufacturing resources. Acco…     

应用成组技术实现制造敏捷化、分散化、网络化

本文分析了敏捷化、分散化、网络化制造与应用成组技术之间的关系，提出了应用成组技术实现敏捷化、分散化、网络化制造的方法，探讨了我国制造企业基于成组技术的敏捷生产组织构建方法以及敏捷制造单元的成组与重构技术，为我国中小企业特别是离散型制造企业实现敏捷化、分散化、网络化制造作了有益探索。     

面向网络联盟的全球产品配置管理

阐述了网络化制造模式的特点，在分析网络化制造环境下产品配置的新特点的基础上，提出面向网络联盟的全球产品配置管理思路，支持基于知识的快速创新和“边缘创新”．通过建立全球配置系统结构和对产品配置流程的分析，为相应的软件开发可行性进行了论证。     

An architecture for IoT-enabled intelligent process-aware cloud production platform: a case study in a networked cloud clinical laboratory

Cloud production is an emerging paradigm that supports co-designing and co-producing integrated solutions with customers. The realisation of this paradigm requires integrated platforms that enable parties collaborating within a production ecosystem to inter-operate networked business processes. Previous research has proposed different architectures for cloud production platforms from different perspectives like virtualiseng and servitiseng manufacturing resources, distributed and networked sensing supported by IoT technologies, and service-oriented and process-centred computing to compose and enact networked production services. However, an integrated architecture that brings together insights from service-oriented cloud manufacturing, IoT-enabled intelligence, and networked process-centred service composition and enactment has not been sufficiently addressed in previous research. In order to incorporate insights from the mentioned different perspectives, in this paper architectural analysis, synthesis, and evaluation steps are conducted to propose a conceptual architecture for IoT-enabled intelligent process-aware cloud production platforms. This architecture describes design-time and run-time components of a cloud production platform that can sense and intelligently respond to events within a value network. To evaluate the applicability of the proposed architecture within real-life scenarios, a case study is conducted in a cloud clinical laboratory in Tehran, Iran. Within this case study, a concrete cloud clinical laboratory platform has been instantiated.     

面向云制造服务的制造资源优化配置研究

为了降低云端制造服务成本,解决云制造环境下无需求偏好的制造资源优化配置的难题,充分考虑制造资源需求企业和云平台运营方的利益以及双方在制造资源配置服务过程中涉及到的服务质量（quality of sevice,QoS）因素和柔性因素,构建了云环境下代表制造资源需求企业和云平台运营方利益的多目标优化资源配置模型,并基于改进NSGA-Ⅱ算法对模型算例进行了求解,计算结果表明了该模型和算法的可行性、有效性和稳定性。     

基于ASP的网络化制造平台研究

为了解决中小企业群的信息化建设问题,研究了基于ASP(Application Service Provider,应用服务供应商)模式的网络化制造平台的关键技术及其实现方案。通过分析中小企业群的构成模式,提出了分别以专业、产品和业务组合为核心的三种基于ASP的网络化制造平台的体系结构,研究了以增值服务链为核心的资源共享,以及面向产品生命周期的业务协同。在综合分析J2EE和．NET技术架构的基础上,提出了基于Web Service网络化制造平台集成方案。     

基于互联网的纺织行业资源库系统的建立方法

基于互联网的纺织行业资源库对于纺织企业信息化、知识化、国际化、管理现代化等具有重要的作用．本文从资源的分散度和资源的网络化难度两个角度对纺织行业资源库进行了粗分类;研究了基于互联网的纺织行业资源库的环境特点,其对资源库的建立方法有重要影响;分析了基于互联网的纺织行业资源库的自组织建立方法;最后研究了基于互联网的纺织行业资源库的正反馈发展机制,包括形成条件和启动方法等．     

Cloud manufacturing resources fuzzy classification based on genetic simulated annealing algorithm

To solve the problem of fuzzy classification of manufacturing resources in a cloud manufacturing environment, a hybrid algorithm based on genetic algorithm (GA), simulated annealing (SA) and fuzzy C-means clustering algorithm (FCM) is proposed. In this hybrid algorithm, classification is based on the processing feature and attributes of the manufacturing resource; the inner and outer layers of the nested loops are solving it, GA obtains the best classification number in the outer layer; the fitness function is constructed by fuzzy clustering algorithm (FCM), carrying out the selection, crossover and mutation operation and SA cooling operation. The final classification results are obtained in the inner layer. Using the hybrid algorithm to solve 45 kinds of manufacturing resources, the optimal classification number is 9 and the corresponding classification results are obtained, proving that the algorithm is effective.     

导向辊生产设备制造资源集合匹配方法

目的 为解决云制造环境下导向辊生产工序外协时设备制造资源搜索效率低的问题,本文提出一种导向辊生产设备云制造资源集合与生产工序云制造需求匹配的方法,用于降低导向辊制造资源的寻优范围。方法 首先建立导向辊生产设备制造资源的可拓物元模型,通过可拓聚类算法实现导向辊生产设备制造资源的聚类,接着利用集合中制造资源的可用加工方法属性与制造需求的加工方法属性进行配对,通过配对结果完成导向辊生产设备制造资源集合与生产工序制造需求的匹配。结果 使用该匹配方法后,成功将10个导向辊制造资源样本聚类为7种制造资源集合KN1—KN7,并将其与导向辊的7种生产工序制造需求实现匹配。结论 实验结果表明,该方法能够实现导向辊生产设备云制造资源集合与生产工序需求的匹配,提高了后续导向辊生产工序外协资源的寻优效率。     

基于本体论的工艺信息描述方法研究

依据本体论的概念论述了零件信息和制造资源信息的描述方法，给出了它们本体的定义方式。描述了零件本体和特征本体的属性，分析了各本体间和本体属性间的关系。以开发的CAPP系统为例，阐述了此描述方法在实际应用中体现出的特点。     

异地协同设计制造关键技术及系统实现

 在分析制造业面临的新挑战以及网络化制造特点的基础上，提出了基于Web的异地协同设计制造系统的体系结构并开发了一个实际系统eCWS(e—cooperative work system )．详细介绍了该系统的功能和关键技术的实现，包括协同系统管理、协同工作管理、协同应用、约束管理和冲突消解、协同工具、安全控制、分布式产品数据管理等技术． 最后介绍了应用实例．     

网络化制造系统中产品信息集成平台的研究

为了使网络制造中各企业间的协作更有效,需要建立有效的信息集成与共享环境以及协同作业运行机制,即建立一个基于Web的产品信息集成平台(PIIE),为各企业的产品信息集成与共享及产品的协同开发提供一个环境.本文探讨了PIIE系统的体系架构,分析了产品开发的协同作业机理,并就建立PIIE系统涉及的关键技术进行了阐述.     

Network-integrated manufacturing system

In this study, systematic integration for networked manufacturing, including information integration, process integration, knowledge integration and organisation integration, is presented. Then, a model of network-integrated manufacturing system (NIMS) is proposed. A wheel of network-integrated manufacturing system (NIMS) details the concept, which includes five integrated rings: the rings of core objects, participants, support centres, functional subsystems and infrastructure. A NIMS model of a Chinese ceramic company (CP-NIMS) is presented to illustrate how the model can be applied to ceramic product design, customisation, production, and delivery.     

A dynamic curation method for manufacturing-related knowledge

A method for the dynamic curation of manufacturing-related knowledge is proposed, based on the impact of successive paradigm introduction on the network structure within manufacturing companies. This draws together manufacturing system structure in terms of interacting component network types, the nature and consequences of knowledge silos and the underpinning dichotomous influence of language. The need and opportunities for an objective- rather than subjective paradigm-based view of manufacturing are identified, leading to a curation process in which paradigms and other knowledge specialisms are different viewpoints based on particular models of manufacturing processes and resources. The consequences of this are explored in terms of knowledge silo reduction, improved communication within component social- and information networks, increased operational resilience and better informed decision-making for future business.     

Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described.     

TOPSIS在制造企业ASP平台选型中的应用

根据制造企业选择ASP服务提供商的业务流程,采用TOPSIS方法构造评价函数,建立了ASP平台软件系统评价指标体系;采用Delphi法确定评价指标的权重系数,求解评价函数最优解作为评价目标的最优解,最后举例进行了验证.结果表明,采用TOPSIS和Delphi相结合的方法对制造企业ASP平台软件系统进行选型,可以有效地减少ASP平台选型的主观盲目性,提高平台选型的科学性.     

制造系统全过程可诊断性测度的研究

制造过程中存在着４Ｒ效应,即鸟尾效应,斜升效应,随机效应和松弛效应的影响,这些效应使系统的运行性能在寿命周期同俣现复杂的状况,从系统角度研究了制造系统整个寿命周期内的可诊断性问题,定义了制造系统可诊断性,按照制造过程,分析讨论了系统过程前可诊断性,过程中可诊断性以及过程后诊断性,对每个阶段的性能测度进行了研究,并提出一种评价和控制系统全过程可诊断性的指标体系,研究表明,这个测度系统也是系统产品质量缺陷和设备运行故障的有效评价指标。     

SWMRD: a Semantic Web-based manufacturing resource discovery system for cross-enterprise collaboration

As supply chains are becoming ever more global and agile in the modern manufacturing era, enterprises are increasingly dependent upon the efficient and effective discovery of shared manufacturing resources provided by their partners, wherever they are. Enterprises are thus faced with increasing challenges caused by the technical difficulties and ontological issues in manufacturing interoperability and integration over heterogeneous computing platforms. This paper presents a prototype intelligent system SWMRD (Semantic Web-based manufacturing resource discovery) for distributed manufacturing collaboration across ubiquitous virtual enterprises. Ontology-based annotation to the distributed manufacturing resources via a new, multidisciplinary manufacturing ontology is proposed on the semantic web to convert resources into machine understandable knowledge, which is a prelude to the meaningful resource discovery for cross-enterprise multidisciplinary collaboration. An ontology-based multi-level knowledge retrieval model is devised to extend the traditional information retrieval approaches based on keyword search, with integrated capabilities of graph search, semantic search, fuzzy search and automated reasoning to realise the intelligent discovery of manufacturing resources, e.g. to facilitate more flexible, meaningful, accurate and automated resource discovery. A case study for intelligent discovery of manufacturing resources is used to demonstrate the practicality of the developed system.