计算机系统在自动化仪器仪表中的应用

随着各领域技术的迅速发展和不断进步,计算机技术逐渐渗透到自动化控制技术中,其中,嵌入式计算机系统已经在仪器仪表领域获得了越来越多的应用。如今,自动化仪器仪表已具备＂工业IT＂的特征。本文首先介绍了我国仪器仪表控制系统的发展历程,阐述了嵌入式计算机系统的定义、特征、基本构架以及嵌入式计算机系统中的软件技术,对嵌入式计算机系统在仪器仪表中的应用进行了研究与分析,并展望了高级嵌入式系统对未来新型仪器仪表技术的支持及其前景。     

Expert systems for manufacturing cell simulation and design

Computer Integrated Manufacturing (CIM) is approached by means of the application of Computer Aided Design (CAD), Computer Aided Manufacturing (CAM) and other CA techniques, methods and programs/program systems. These programs are often implemented as knowledge-based, or expert systems and in this way they became typical examples of engineering application of artificial intelligence. The production task of CIM systems is solved by using flexible manufacturing systems (FMSs). FMSs built up from smaller, complex units, i.e. from flexible manufacturing cells (FMCs) have several advantages. The design and the operation of manufacturing systems need new, sophisticated methods to utilize all the embedded benefits of the sophisticated and expensive elements installed for production purposes. New methods like knowledge processing technology, cooperative problem-solving techniques, etc., offer wide possibilities to design more reasonable systems. This paper describes prototype expert systems that make use of different knowledge-based tools and techniques to design (configure, reconfigure) and simulate manufacturing cells, taking into consideration technological plans and other relevant information.     

Development and Applications of Holonic Manufacturing Systems: A Survey

This paper surveys the literature in the holonic manufacturing systems area in an attempt to bring together the key issues in the development and applications of holonic systems. A brief introduction presents the characteristics of today’s manufacturing environment and the requirements for next generation manufacturing systems. Then, starting with considerations about the origins of the holonic concept and its first applications in manufacturing, the paper presents the advances made in applying the holonic concept to manufacturing systems area. Several considerations for the development of holonic manufacturing systems and specific holonic system requirements are discussed. As holonic concept is considered a solution for next generation manufacturing systems, there is a significant number of applications and implementations of the holonic concept in manufacturing systems domain. The most important and relevant approaches developed so far are presented. Finally, a short conclusion and future research directions in the area are provided     

Applications of agent-based systems in intelligent manufacturing: An updated review

Agent technology has been recognized as a promising paradigm for next generation manufacturing systems. Researchers have attempted to apply agent technology to manufacturing enterprise integration, enterprise collaboration (including supply chain management and virtual enterprises), manufacturing process planning and scheduling, shop floor control, and to holonic manufacturing as an implementation methodology. This paper provides an update review on the recent achievements in these areas, and discusses some key issues in implementing agent-based manufacturing systems such as agent encapsulation, agent organization, agent coordination and negotiation, system dynamics, learning, optimization, security and privacy, tools and standards.     

Constraint-Based Design of Embedded Intelligent Systems

Substantial progress has been achieved using the standard Constraint Satisfaction Problem framework. However, there is a major unsolved challenge confronting the constraint research community: the constraint-based design of embedded intelligent systems. This requires a new online model of constraint satisfaction and new computational tools for specifying, modeling, verifying and implementing constraint-based, hybrid, intelligent systems, such as robots. The Constraint Net model of Zhang and Mackworth allows the design of hybrid intelligent systems as situated robots: modeling the robot and the environment symmetrically as dynamic systems. If the robot's perceptual and control systems are designed as constraint-satisfying devices then the total robotic system, consisting of the robot symmetrically coupled to the environment, can be proven correct. Some theoretical and practical advances based on this model are described, including experiments with the constraint-based design of robot soccer players.     

Intelligent association selection of embedded agents in intelligent inhabited environments

Recent advances in technology and manufacturing have resulted in more powerful and smaller processors to be embedded in the various artefacts within smart environments. Most of these artefacts are network enabled and thanks to pervasive networking such artefacts can communicate and collaborate together to support our daily lives. Furthermore, these artefacts can also be equipped with embedded agents to provide intelligent reasoning, planning and learning capabilities. However, the multitude of interconnected devices and artefacts can result in major network and processing delays as well as creating inherent complexities in programming and configuring smart environments to personalise themselves to suit the individual needs. Hence, a major challenge to the design and use of smart environments involves finding the best set of device associations and interconnections that are most suitable to the environment and user needs. In this paper, we will present a novel intelligent method for reducing the number of associations and interconnections between the various devices and artefacts within smart environments to minimise the network and processing overheads while reducing the cognitive load associated with configuring and programming smart environments.     

Integration of neurocomputing and system simulation for modeling continuous improvement systems in manufacturing

The use of a neural network embedded in a larger general-purpose simulation system (GPSS) simulation used to model continuous improvement systems (CIS) policies in a factory setting is described. The neural network is used to accelerate the identification of an effective CIS policy by providing a more realistic simulation framework. The interface between general simulation theory and neural network simulation is examined. Neural networks, when embedded in larger general-purpose simulations, are found to offer the potential for improving on the capabilities of those simulations, in particular manufacturing simulations for continuous improvement of production processes.     

离散事件系统理论研究和应用进展（Ⅰ）

介绍离散事件动态系统（ＤＥＤＳ）理论各主要方面近几年的新进展以及它们在各方面的应用情况。特别着重强调了一些新方向和新问题，如混杂系统、动态对策等，以及它们在机械，电子等制造过程以及通讯和计算机系统中的应用。最后从基础性研究的角度对ＤＥＤＳ研究的未来发展方向提出了一些想法和建议。本文为综述的第一部分。     

离散事件系统理论研究和应用进展（Ⅱ）

介绍离散事件动态系统（DEDS）理论各主要方面近几年的新进展以及它们在各方面的应用情况。特别着重强调了一些新方向和新问题，如混杂系统、动态对策等，以有它们在机械、电子等制造过程以及通讯和计算机系统中的应用。最后还从基础性研究的角度对DEDS研究的未来发展方向提出了一些想法和建议。这是综述的第二部分。     

RMS design methodology for automotive framing systems BIW

Today, markets increasingly require more customized products, with shorter life cycles. In response, manufacturing systems have evolved from mass production techniques, through flexible automation and mass customization, to produce at mass production costs. Manufacturing facilities must incorporate more flexibility and intelligence, evolving toward reconfigurable manufacturing systems (RMS). RMS are amid to posses such flexibility and responsiveness and said to be the next generation of world class systems. RMS are designed for rapid change in structure and for a quickly adjustable production capacity. This paper proposes a new methodology (high level process) of framework using flexible and reconfigurable manufacturing systems principles for automotive framing systems as well as to provide a guideline to support the structure of different stages of the design methodology. The proposed methodology is presented through a case study using data based on actual production systems of three different styles; (process and design data) which supports the hypothesis of the research.     

Standard Linux for embedded real-time robotics and manufacturing control systems

The main goal of the research presented in this paper is to evaluate the possibility of using standard Linux for embedded real-time applications in robotics and manufacturing as a consequence of dramatic improvements in hardware computing power and free software quality in the last few years. After an accurate analysis of the problems related to make Linux, a native Unix-like fair kernel, real-time, laboratory tests showed that a large variety of applications (up to 1 KHz) can be implemented using Linux and commercial-of-the-shelf hardware. Practical examples of the control systems of an unmanned surface vessel used for robotics research and of a marking machine for steelworks are reported and discussed.     

Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook

The recent advances in sensor and communication technologies can provide the foundations for linking the physical manufacturing facility and machine world to the cyber world of Internet applications. The coupled manufacturing cyber-physical system is envisioned to handle the actual operations in the physical world while simultaneously monitor them in the cyber world with the help of advanced data processing and simulation models at both the manufacturing process and system operational levels. Moreover, a sensor-packed manufacturing system in which each process or piece of equipment makes available event and status information, coupled with market research for true advanced Big Data analytics, seem to be the right ingredients for event response selection and operation virtualization. As a drawback, the resulting manufacturing cyber-physical system will be vulnerable to the inevitable cyber-attacks, unfortunately, so common for the software and Internet-based systems. This reality makes cybersecurity penetration within the manufacturing domain a need that goes uncontested across researchers and practitioners. This work provides a review of the current status of virtualization and cloud-based services for manufacturing systems and of the use of Big Data analytics for planning and control of manufacturing operations. Building on already developed cloud business solutions, cloud manufacturing is expected to offer improved enterprise manufacturing and business decision support. Based on the current state-of-the-art cloud manufacturing solutions and Big Data applications, this work also proposes a framework for the development of predictive manufacturing cyber-physical systems that include capabilities for attaching to the Internet of Things, and capabilities for complex event processing and Big Data algorithmic analytics.     

A configurable cryptography subsystem in a middleware framework for embedded systems

Computer and network security is becoming increasingly important as both large systems and, increasingly small, embedded systems are networked. Middleware frameworks aid the system developer who must interconnect individual systems into larger interconnected, distributed systems. However, there exist very few middleware frameworks that have been designed for use with embedded systems, which constitute the vast majority of CPUs produced each year, and none offer the range of security mechanisms required by the wide range of embedded system applications. This paper describes MicroQoSCORBA, a highly configurable middleware framework for embedded systems, and its security subsystem. It first presents an analysis of security requirements for embedded applications and what can and should be done in middleware. It then presents the design of MicroQoSCORBA’s security subsystem and the wide range of mechanisms it supports. Experimental results for these mechanisms are presented for two different embedded systems and one desktop computer that collectively represent a wide range of computational capabilities.     

Enhancing image processing architecture using deep learning for embedded vision systems

In recent years, the success and capabilities of embedded vision have showed up in embedded applications. The embedding of vision into electronic devices such as embedded medical applications is being driven by the availability of high-performance processors, integrating with deep learning algorithms, as well as advances in image processing technology. But, including image processing in embedded vision systems need huge amount of computational capabilities even to process a single image to detect an object and it's extremely challenging to implement in embedded systems. Implementing deep learning algorithms and testing it on a task specific data set could provide enhanced results. In this paper, an approach for enhancing image processing architecture using deep learning for embedded vision systems is proposed and analyzed. Implementing deep learning algorithms and testing it on embedded vision yielded effective results.     

基于虚拟化打印机的数据采集设计

为配合现代制造执行系统(MES)对数据管理要求、提高生产效率,提出"虚拟化打印机"概念,即以嵌入式系统代替实体打印机,基于这样的虚拟化打印机系统实现打印口数据的采集与保存。设计结合现有技术,通过C51单片机系统实现打印口-串口虚拟化打印机,实现打印图表文字的数据采集与电子存储;并在此基础上,提出基于嵌入式系统的打印口-网络虚拟化打印机,将数据通过以太网直接传输至数据中心,方案摒弃现场工控机,以降低成本提高效率。本设计已付诸应用,帮助某汽车制造工厂获取测试仪的测试数据及图表,实时同步数据中心或企业ERP系统。     

Computer-aided manufacturing systems: Work-psychological aspects and empirical findings from case studies

In this paper, findings from a research project on work-psychological concepts for the design of computer-aided integrated manufacturing systems are presented. The work-psychological point of view is that concepts which focus not only on technical aspects, but also on the design of work organization and the use and development of skills and qualifications not only contribute to humane work conditions but are also associated with economics efficiency. Results gained from 60 small and medium size Swiss companies in the capital-goods industry show that very few companies have holistic manufacturing structures in terms of decentralization, functional integration, work group autonomy and complete and challenging tasks. Furthermore, skills and qualifications are not made use of to their fullest extent in most companies. Although technical support in terms of implementation of computer-aided manufacturing systems and technical integration is noticeably high, economic efficiency could not be exclusively attributed to the implementation of technical systems. The attainment of efficiency goals associated with the implementation of technical systems turned out to be higher in companies pursuing a holistic approach to the design of computer-aided manufacturing systems encompassing technical aspects, organizational design and use and development of skills and qualifications.

Relevance to industry

In many companies, the implementation and utilization of computer-aided manufacturing systems is considered an appropriate means for meeting increased market demand. Yet, a growing body of empirical findings indicates that computer-aided manufacturing systems per se will not guarantee that companies perform successfully. Data gained from case studies indicate that a comprehensive approach directed at the joint consideration and optimization of technical systems, organizational design and qualifications will contribute to a successful implementation of computer-aided manufacturing systems in terms of humane working conditions and economic efficiency. The data can be used for the work-psychologically founded design of computer-aided integrated manufacturing systems.     

Agent-based distributed manufacturing control: A state-of-the-art survey

Manufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and re-usability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future.     

Complex networks in advanced manufacturing systems

In recent years, with the rapid development of manufacturing, information, and management technology, advanced manufacturing systems (AMSs) have become increasingly more and more complex, which hinders the wider applications of many key theories and technologies in AMSs. Fortunately, in the last two decades, some dramatic advances have been made in the field of statistical physics theories, along with the extensive applications of complex network. It has provided an alternative approach to analyze AMSs. Many recent studies have focused on the theory of complex networks to describe and solve complicated manufacturing problems. Based on a great number of relevant publications, this paper presents an up-to-date literature review with the identified outstanding research issues, future trends and directions. Three critical issues are summarized after this investigation: (a) the focused areas of AMSs that have deployed the theory of complex networks, (b) the addressed issues and the corresponding approaches, and (c) the limitations and directions of the existing works.     

A distributed development environment for embedded software

The HAGAR project is building a high-performance disk controller. It is an embedded system for which many hundreds of thousands of lines of embedded software will have to be developed concurrently with the development of the hardware. We found existing methods for embedded software development, such as simulation and remote cross development, to be inadequate for us. To meet our special needs, we developed a distributed development environment that combines and extends the capabilities of existing methods while fixing their drawbacks. Our environment is based on a processor-pool architecture, in which multiple hardware sets are pooled and managed systematically. It supports embedded software development for many programmers at different sites. It allows for the emulation of non-existing hardware adaptor cards and for the integration of embedded software testing with hardware simulation. The environment provides a single system image, hiding many hardware and configuration details from its users. From the perspective of the programmers, our environment makes developing embedded software for special hardware systems as easy as developing application programs for a UNIX workstation.