北京和利时信息技术有限公司－流程行业生产管理系统HiMES2．0

和利时流程行业生产管理系统HiMES2．0以精益生产为核心管理思想,以ISA95标准为指导,集中体现了和利时公司在过程控制系统领域的技术优势和在流程企业管理方面的丰富经验。系统以实时信息为基础,提供包括工厂建模、实时监控、生产计划、生产调度、工艺管理、生产物流、生产统计、质量管理、设备管理、成本管理、能源管理、安全环保等流程企业应用模块。软件产品完全基于SOA架构,提供了包括企业应用建模平台、工作流平台、运行平台、实时信息平台、企业应用集成平台在内的系列平台产品。     

钢铁企业质量管理系统研究与开发

针对钢铁冶金行业质量管理的特征,就钢铁企业质量管理体系的构成进行了探讨,特别针对质量管理系统中的核心技术冶金规范管理与产品规范管理在信息系统中如何实现进行了分析,并通过对其作用的描述,说明了该体系在钢铁企业质量管理系统中具有应用的潜力。钢铁企业质量管理系统,全面制定了企业所有生产区域的质量标准和工艺规范．体现了质量一贯制的管理思想。该系统加速了产品设计过程,缩短了产品交货周期,实现产线优化、质量效益最大化。     

石化行业智能工厂信息模型研究与设计

智能制造的核心是构建基于模型的企业。信息模型是对物理对象的数字化,可反映实际物理对象和数据的关系,能够解决信息空间与物理空间之间异构数据及异构网络互联互通、异构集成、互操作的问题,为实现各个环节的深度融合打通交互通道提供重要保障。石化行业智能工厂信息模型是石化智能工厂及其中各元素的描述信息与实时状态的数字化表述,是石化智能工厂建模、工厂设计应用的基础,也可以作为石化智能工厂更进一步数据交换标准的基础。此外,石化行业智能工厂信息模型支撑石化行业信息物理系统(CyberPhysical Systems,CPS)信息虚体的搭建。本文结合石化行业特点,建立了石化行业智能工厂信息模型,定义了石化行业智能工厂信息模型组成、属性,以及模型要素之间的关系,并介绍了工厂信息模型在石化行业中的实现及应用情况。     

基于NX/Open的企业零部件库参数化建模方法①

企业产品三维模型数据库的构建,是实现大规模定制设计和快速响应设计的基础。为了满足快速构建企业产品资源库的需求,提出了一种基于三维设计平台的企业零部件库参数化建模方法。该方法以三维设计软件UG NX为开发平台,基于NX/Open开发产品三维零部件库。基于层次性参数化建模方法,提出利用主模型技术和自顶向下的方法实现产品的参数化建模及变型设计,实现了零部件和装配体的参数化建模。结合数控机床快速响应设计系统中刀具库设计开发的实例,给出企业零部件库的建库流程,表明基于主模型的层次性参数化建库方法是企业产品资源库建立     

智能产品模型的建模原理与实现

智能产品模型的建模原理与实现中国机械工业电脑应用技术开发公司张岗智能产品建模的目的就在于：借助于产品模型的“智能性”来缩短设计周期、保证设计质量；通过“模型构件标准化”和“减少使用新零部件”来控制设计结果，保证缩短生产周期、降低成本和提高质量，使企业...     

基于本体的产品知识表达

产品开发过程分工的加强、市场和全球化竞争的激烈都要求工厂能够更迅速地生产更廉价和质量更高的产品，而这需要一个更有效并且强有力的产品知识管理系统，以支持产品知识的表达、重用、共享和交流等．研究了产品知识表达的模型，即S—B—F，结合本体描述语言构建了流本体和功能本体，设计出基于本体的产品知识表达，并进一步提出了可行的应用模型。     

打铁更需自身硬

作为我国国民经济的支柱产业,钢铁工业在我国国民经济发展中起着举足轻重的作用,它的发展水平,甚至已经成为衡量国民经济发展实力的标志。 全球化经济大潮给冶金行业带来前所未有的冲击,而加入WTO又意味着冶金行业必须直面来自国际市场的质量竞争、价格竞争、服务竞争、谋略竞争和深层次企业核心竞争。如何利用信息技术增强企业的国际竞争力,如何在更广泛的领域和更高的层次上进行更为规范的竞争,已经成为冶金行业面临的最迫切的问题。     

冷轧产品质量设计模型及实现

通过对宝钢股份不锈钢事业部整体产销系统中的冷轧产品质量设计模型的介绍,阐明了质量设计的原则和思想。叙述了合同、产品规范、冶金规范与质量设计的功能关系,实现冷轧产品从冶炼到成品全过程的各工序的一贯质量设计。     

满足装配建模的标准件库的设计与实现

在装配建模过程中 ,三维标准零件是构成产品模型整体的一个不可缺少的部分 ,本文深入分析了面向装配的标准件库的信息结构 ,提出和实现了满足装配建模的一种标准件建库方法和建库工具 ,系统具有友好的用户界面和方便的标准件装配操作。     

基于知识管理的 BIM 模型建筑设计合规性自动检查系统研究

建筑设计合规性自动检查对保证建筑信息模型(BIM)符合设计规范要求,增加规范 检查自动化程度具有重要意义。结合合规性检查理论与专家系统方法,提出了以BIM 模型为检 查对象的合规性自动检查系统框架,以规则知识与推理机制分开的方式实现合规性检查过程。 以《住宅设计规范》为例,对规范中的条文进行知识分析,总结出规范知识表达式,构建规则 库和规则库访问机制;建立了逻辑策略下推理机制,将规则库中的规则信息与BIM 信息进行推 理,输出检查结果;最后构建了合规性检查系统验证平台,通过BIM 模型实例完成模型数据提 取及规则推理的过程,实现了合规性检查的功能,验证了合规性检查方法框架。该方法在一定 程度上能够指导后续的合规性检查相关研究,有效提高BIM 模型的建筑设计合规性检查效率, 保证检查质量,促进建筑工程领域信息化的发展。     

Reconfigurable and transportable container-integrated production system

In this paper, the concept and the prototype realization of a novel reconfigurable small-footprint manufacturing system in a transportable container is presented. The containerized format enables transportation of the system to provide on-site manufacturing, enabling the benefits of localized service delivery without duplication of equipment at multiple locations.Three industrial product use cases with varying manufacturing and performance requirements were analysed. All of the use cases demanded highly customized products with high quality in low production volumes. Based on their requirements, a general system specification was derived and used to develop a concept for the container-integrated factory.A reconfigurable, modular manufacturing system is integral to the overall container concept. Production equipment was integrated in the form of interchangeable process modules, which can be quickly connected by standard utility supply and control interfaces. A modular and self-configuring control system provides assisted production workflow programming, while a modular process chain combining Additive Manufacturing, CNC milling, precision assembly and cleaning processes has been developed.A prototype of the container-integrated factory with reconfigurable process modules and control system has been established, with full functionality and feasibility of the system demonstrated.     

Concurrent-development process model

The lessons learned in managing a model that lets a user develop multiple functions concurrently over the entire development process, from requirements specification to system test are reviewed. The structure and dynamic behavior of a concurrent development process are discussed. The process management, project management, product management, organization management, and software-engineering environment elements of the concurrent development model are all described, although the focus is on process management. The concurrent development process is compared to sequential development, lean production, software factory, and capability maturity model processes     

A Framework for Improving the Requirements Engineering Process Management

This paper presents a system dynamics model for improving the requirements engineering process management. The paper argues that improving RE process management improves the quality of the specification produced. It uses a simulation modelling approach to capture the complex and dynamic nature of quality and also the cost of resources and time needed to complete the process. Current claims by various researchers and empirical evidence has led to our proposition that “the earlier in the requirements engineering phase that system dynamics simulation modelling is used, the more effective the RE process management is and the better its product quality will be.” In developing such a model, the paper fills an important gap in the RE process management literature and has potential to provide requirement engineers, managers and software development organisations with a model-based process framework to aid quality assessment and improvement. The paper concludes by suggesting that the framework makes a useful contribution both in providing the foundations for theory building in RE process management and quality improvement by aiding shared understanding through learning and training situations. This revised version was published online in August 2006 with corrections to the Cover Date.     

Requirements Engineering-Based Conceptual Modelling

The software production process involves a set of phases where a clear relationship and smooth transitions between them should be introduced. In this paper, a requirements engineering-based conceptual modelling approach is introduced as a way to improve the quality of the software production process. The aim of this approach is to provide a set of techniques and methods to capture software requirements and to provide a way to move from requirements to a conceptual schema in a traceable way. The approach combines a framework for requirements engineering (TRADE) and a graphical object-oriented method for conceptual modelling and code generation (OO-Method). The intended improvement of the software production process is accomplished by providing a precise methodological guidance to go from the user requirements (represented through the use of the appropriate TRADE techniques) to the conceptual schema that properly represents them (according to the conceptual constructs provided by the OO-Method). Additionally, as the OO-Method provides full model-based code generation features, this combination minimises the time dedicated to obtaining the final software product.     

Specifying software quality with the extended ISO model

Specifying the quality of software products is a valuable addition to functional specification, clarifying product properties such as learnability and availability. Specifying such properties is considered difficult due to the different parties involved and the implicit nature of the requirements. The QUINT project gathered experience with product specification by means of the Extended ISO model: an extension to the ISO 9126 model of software quality. By defining indicators and specifying how they should be measured, quality specifications can make requirements explicit. Recommendations and pitfalls for composing a specification are grouped by the context in which quality specifications can be used.     

A knowledge-based tool for designing cyber physical production systems

Changing production systems and product requirements can trace their origin in volatile customer behaviour and evolving product requirements. This dynamic nature of customer requirements has been described as a constantly moving target, thus presenting a significant challenge for several aspects of product development. To deal with this constant and sometimes unpredictable product evolution, cyber physical production systems (CPPS) that employ condition monitoring, self-awareness and reconfigurability principles, have to be designed and implemented. This research contributes a CPPS design approach that proactively provides the required CPPS design knowledge. This approach aims to minimise or avoids future consequences and disruptions on the CPPS. This knowledge needs to be provided at the right time whilst not being intrusive to the production system designer’s cognitive activity. To effectively deal with the complexity of the cyber physical production system design activity with a manual method would lead to a time consuming, and complex support tool which is hard to implement, and difficult to use. The CPPS design approach has therefore been implemented in a prototype digital factory tool. This paper describes in detail the system requirements and system architecture for this tool. In order to establish the effectiveness of the proposed approach for designing cyber physical production systems, the prototype digital factory tool has been evaluated with a case study and a number of semi-structured interviews with both industrial and scientific stakeholders. The encouraging results obtained from this research evaluation have shown that such an approach for supporting the CPPS design activity makes stakeholders aware of their decision consequences and is useful in practice. This result can lead the way for the development and integration of such knowledge-based decision-making approaches within state-of-the-art digital factory and Computer Aided Engineering Design (CAED) tools.     

Intelligent products: The grace experience

Product intelligence is a new industrial manufacturing control paradigm aligned with the context of cyber-physical systems and addressing the current requirements of flexibility, reconfigurability and responsiveness. This paradigm introduces benefits in terms of improvement of the entire product׳s life-cycle, and particularly the product quality and customization, aiming the customer satisfaction. This paper presents an implementation of a system of intelligent products, developed under the scope of the GRACE project, where an agent-based solution was deployed in a factory plant producing laundry washing machines. The achieved results show an increase of the production and energy efficiency, an increase of the product quality and customization, as well as a reduction of the scrap costs.     

A dispatching rule for photolithography scheduling with an on-line rework strategy

Generally speaking, wafer fabrication factories define the photolithography area as the dispatching center of the entire factory. To establish a set of operative dispatching rules in the photolithography area while taking into consideration the rework of defective products would assist in coordinating and balancing the workload of the entire production line. Furthermore, it would help to enhance both the productivity and efficiency of the wafer fabrication, reduce the on-line WIP stock, shorten the production cycle time, and satisfy the requirements of customers regarding production due time and product quality. This research uses on-line rework as the basis for bringing the factor of reworking of a batch process into the dispatching rule for measurement. It then develops the dispatching rule (Rw-DR) which includes the rework strategy. In addition, this research focuses on the batch with high finished proportion in the photolithography area for finding a way to complete the manufacturing procedure faster, lighten the machine workload of the waiting line, and at the same time increase the output quantity.     

An approach to monitoring quality in manufacturing using supervised machine learning on product state data

Increasing market demand towards higher product and process quality and efficiency forces companies to think of new and innovative ways to optimize their production. In the area of high-tech manufacturing products, even slight variations of the product state during production can lead to costly and time-consuming rework or even scrapage. Describing an individual product’s state along the entire manufacturing programme, including all relevant information involved for utilization, e.g., in-process adjustments of process parameters, can be one way to meet the quality requirements and stay competitive. Ideally, the gathered information can be directly analyzed and in case of an identified critical trend or event, adequate action, such as an alarm, can be triggered. Traditional methods based on modelling of cause-effect relations reaches its limits due to the fast increasing complexity and high-dimensionality of modern manufacturing programmes. There is a need for new approaches that are able to cope with this complexity and high-dimensionality which, at the same time, are able to generate applicable results with reasonable effort. Within this paper, the possibility to generate such a system by applying a combination of Cluster Analysis and Supervised Machine Learning on product state data along the manufacturing programme will be presented. After elaborating on the different key aspects of the approach, the applicability on the identified problem in industrial environment will be discussed briefly.