A generic tri-model-based approach for product-level digital twin development in a smart manufacturing environment

Smart manufacturing, as an emerging manufacturing paradigm, leverages massive in-context data from manufacturing systems for intelligent decision makings. In such context, Cyber-Physical Systems (CPS) play a key role in digitizing manufacturing systems and integrating multiple systems together for collaborative works. Amongst different levels of smartness and connectedness of CPS, Digital Twin (DT), as an exact digital copy of a physical object or system including its properties and relationship with the environment, has a significant impact on realizing smart manufacturing. A DT constantly synchronizes with its physical system and provides real-time high-fidelity simulations of the system and offers ubiquitous control over the system. Despite its great advantages, few works have been discussed about DT reference models, let alone a generic manner to establish it for smart manufacturing. Aiming to fill the gap, this research introduces a generic CPS system architecture for DT establishment in smart manufacturing with a novel tri-model-based approach (i.e. digital model, computational model and graph-based model) for product-level DT development. The tri-model works concurrently to simulate real-world physical behaviour and characteristics of the digital model. To validate the proposed architecture and approach, a case study of an open source 3D printer DT establishment is further conducted. Conclusions and future works are also highlighted to provide insightful knowledge to both academia and industries at last.     

Integration strategy for distributed intelligent systems

In this article, we describe a new framework for designing real-time intelligent control systems. An integrated intelligent system is a large knowledge integration environment that consists of both symbolic reasoning systems (expert systems) and numerical computation packages. These modular software programs are controlled by a meta-system which manages the selection, operation, and communication of these programs. This new architecture can serve as a universal configuration to develop high-performance intelligent systems for many complicated application domains in the real-time manufacturing process. As an example, an intelligent optimal control is utilized to illustrate the integrated intelligent control system.     

铝电解生产智能优化制造研究综述

铝电解行业具有战略基础地位,面临着诸多挑战性难题,包括原料来源复杂使得工况难以稳定优化运行、多目标协同优化难度大、控制决策智能化水平和数据利用率低以及铝电解企业在内外环境的不确定性影响下难以实时做出正确决策等.为了解决上述问题,本文提出构建一种集铝电解智能分布式感知系统、系列槽智能协同优化控制系统、大型槽智能优化控制系统、智能安全运行监控系统和虚拟制造系统于一体的铝电解智能优化制造系统的方法.同时提出了铝电解制造系统的未来发展目标和愿景功能,并给出了相关研究方向.最后给出了技术发展规划,提出中短期规划和中长期规划"两步走"战略,并对铝电解生产智能优化制造系统发展前景作出展望.     

A CORBA-based agent-driven design for distributed intelligent manufacturing systems

An agent-oriented methodology is presented for representation, acquisition, and processing of manufacturing knowledge along with analysis and modeling of an intelligent manufacturing system (IMS). An intelligent manufacturing system adopts heterarchical and collaborative control as its information system architecture. The behavior of the entire manufacturing system is collaboratively determined by many interacting subsystems that may have their own independent interests, values, and modes of operation. The subsystems are represented as agents. An agent's architecture and task decomposition method are presented. The agent-oriented methodology is used to analyze and model an intelligent machine cell. An intelligent machine center is considered as an autonomous, modular, reconfigurable and fault-tolerant machine tool with self-perception, decision making, and self-process planning, able to cooperate with other machines through communication. The common object request broker architecture (CORBA) distributed software control system was developed as a simple prototype. A case study illustrates an intelligent machine center.     

iCoSim-FMS: An intelligent co-simulator for the adaptive control of complex flexible manufacturing systems

We describe an intelligent co-simulator for real time production control of a complex flexible manufacturing system (CFMS) having machine and tool flexibility. The manufacturing processes associated with the CFMS are complicated with each operation being possibly done by several machining centers. The co-simulator design approach is built upon the theory of dynamic meta-model based supervisory control with the cooperation of its own embedded intelligent blocks. The system is implemented by coupling of the centralized simulation controller (CSC) and real-time simulator for enforcing dynamic strategies of shop floor control. The posteriori adaptive co-simulator is equipped with a concurrent bilateral mechanism for simulation optimization based on appropriate control rules enhancing performance criteria simulation efficiency. A working intelligent adaptive controller prototype (iCoSim-FMS) has been developed to validate the proposed approach and compare its performance with well known FMS heuristic methods.     

Applications of artificial intelligence in intelligent manufacturing: a review

Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of ‘Internet plus AI’, which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent manufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the application of AI in intelligent manufacturing in China are presented.     

Intelligent product and mechatronic software components enabling mass customisation in advanced production systems

Up to the present time, the control software design of production systems has been developed to produce a certain number of goods, in a centralised manner and through a case-by-case, timely and costly process. Therefore, the current control design approaches hinder factories in their pursuit to acquire the essential capabilities needed in order to survive in this customer-driven and highly competitive market. Some of these vital production competencies include mass customisation, fault tolerance reconfigurability, handling complexity, scalability and agility. The intention of this research is to propose a uniform architecture for control software design of collaborative manufacturing systems. It introduces software components named as modular, intelligent, and real-time agents (MIRAs) that represent both intelligent products as clients (C-MIRA) and machines or robots as operators (O-MIRAs) in a production system. C-MIRAs are in constant interaction with customers and operators through human machine interfaces, and are responsible for transforming products from concepts up to full realisation of them with the least possible human intervention. This architecture is built upon the IEC 61499 standard which is recognised for facilitating the distributed control design of automation systems; however, it also takes into account the intelligent product concept and envisages the machines’ control to be composed of a set of modular software components with standardised interfaces. This approach makes the software components intuitive and easy to install, to create the desired behaviour for collaborative manufacturing systems and ultimately paves the way towards mass customisation. A simplified food production case study, whose control is synthesised using the proposed approach, is chosen as an illustrative example for the proposed methodology.     

INTEGRATED INTELLIGENT ENVIRONMENT FOR GEAR MANUFACTURING SYSTEM

Abstract

This article investigates the integration of computer-aided design, manufacturing, and testing for gears using a distributed intelligence system. The integration architecture, principles, and implementation for computer integrated manufacturing systems (CIMS) are presented. An integrated intelligent system is developed, which has a parallel hierarchical structure in general and a meta-system as its kernel to manage and control the selection, communication, coordination, and operation of the subsystem. The functions and configuration of the meta-system are discussed in detail. A gear integrated manufacturing system (GIMS) is implemented to demonstrate the feasibility and capability of the integrated intelligent system.     

基于区块链的边缘计算IIoT架构研究

在智能制造系统中,工业物联网通过先进的管理技术将制造设备互连,实现了信息的实时传输、设备的范在化感知和数据的快速分析处理。但是由于制造设备的异构性、物联网网关（IoT网关）数据分析能力的有限性、制造设备的存储力低下,设备和数据的低安全性等缺陷严重阻碍了智能制造的发展。BEIIoT架构从制造企业的实际生产过程与应用角度出发,将区块链技术与边缘计算相结合,通过对服务器进行P2P组网以实现对设备去中心化管理;通过对边缘设备进行服务化封装,增强设备的安全性与实时分析能力,降低设备的异构性;使用DAG双链式数据存储结构,提高数据的冗余度与安全性,实现生产线数据的异步并发备份存储。BEIIoT架构为智能制造的实施提供了体系支持。     

Performance comparison and analysis of reactive and planning-based control architectures for manufacturing

Although numerous distributed architectures ranging from hierarchical to non-hierarchical (or heterarchical) have been proposed for the control of manufacturing systems, very little research has focused on quantitative comparisons of these architectures. In this paper, an objective comparison of two architectures, each required to control the same manufacturing cell, is presented. The objective of this work is to gain insight into the behaviour of alternative control architectures that will ultimately be used to determine the best control architecture for a given manufacturing system. In particular, this research focuses on the role of planning horizon in control architecture design to determine whether intelligent control agents should plan ahead or simply react to change in their environment.     

深度学习在软件定义网络研究中的应用综述

数据转发与控制分离的软件定义网络（Software Defined Networking,简称SDN）是对传统网络架构的彻底颠覆,为网络各方面的研究引入新的机遇和挑战.随着传统网络研究方法在SDN中遭遇瓶颈,基于深度学习的方法被引入到SDN的研究中,在实现实时智能的网络管控上成果颇丰,推动了SDN研究的深入发展.调查了深度学习开发平台,训练数据集,智能SDN架构等深度学习引入SDN的促进因素;对智能路由,入侵检测,流量感知和其他应用等SDN研究领域中的深度学习应用进行系统的介绍,深入分析了现有深度学习应用的特点和不足;最后展望了SDN未来的研究方向与趋势.     

An agent-oriented approach to resolve scheduling optimization in intelligent manufacturing

Agent technology is considered as a promising approach for developing optimizing process plans in intelligent manufacturing. As a bridge between computer aided design (CAD) and computer aided manufacturing (CAM), the computer aided scheduling optimization (CASO) plays an important role in the computer integrated manufacturing (CIM) environment. In order to develop a multi-agent-based scheduling system for intelligent manufacturing, it is necessary to build various functional agents for all the resources and an agent manager to improve the scheduling agility. Identifying the shortcomings of traditional scheduling algorithm in intelligent manufacturing, the architecture of intelligent manufacturing system based on multi-agent is put forward, among which agent represents the basic processing entity. Multi-agent-based scheduling is a new intelligent scheduling method based on the theories of multi-agent system (MAS) and distributed artificial intelligence (DAI). It views intelligent manufacturing as composed of a set of intelligent agents, who are responsible for one or more activities and interacting with other related agents in planning and executing their responsibilities. In this paper, the proposed architecture consists of various autonomous agents that are capable of communicating with each other and making decisions based on their knowledge. The architecture of intelligent manufacturing, the scheduling optimization algorithm, the negotiation processes and protocols among the agents are described in detail. A prototype system is built and validated in an illustrative example, which demonstrates the feasibility of the proposed approach. The experiments prove that the implementation of multi-agent technology in intelligent manufacturing system makes the operations much more flexible, economical and energy efficient.     

Application of the analytical hierarchy process for real-time scheduling and part routing in advanced manufacturing systems

This paper presents a framework that employs the analytical hierarchy process (AHP) in advanced manufacturing systems for real-time scheduling and part routing. The proposed multicriteria decision-making framework brings a new perspective to real-time scheduling and part routing decisions, by implementing pairwise comparison of possible future states of a manufacturing system. The framework includes an extended finite state machine and a scheduler model to facilitate dynamic, short-term decision making. The scheduler model, which is developed on the basis of control theory, uses AHP to assess possible future states in a limited look-ahead horizon by comparing the performance measures of each state. The multicriteria decision-making framework developed in this study is implemented in a simulation environment to validate it for real-time manufacturing system control and investigate its performance under a range of look-ahead horizons. Simulation results indicate that the proposed framework performs better for a mid-range horizon for most of the commonly used performance measures.     

Integration and control of intelligence in distributed manufacturing

The area of intelligent systems has generated a considerable amount of interest—occasionally verging on controversy—within both the research community and the industrial sector. This paper aims to present a unified framework for integrating the methods and techniques related to intelligent systems in the context of design and control of modern manufacturing systems. Particular emphasis is placed on the methodologies relevant to distributed processing over the Internet. Following presentation of a spectrum of intelligent techniques, a framework for integrated analysis of these techniques at different levels in the context of intelligent manufacturing systems is discussed. Integration of methods of artificial intelligence is investigated primarily along two dimensions: the manufacturing product life-cycle dimension, and the organizational complexity dimension. It is shown that at different stages of the product life-cycle, different intelligent and knowledge-oriented techniques are used, mainly because of the varied levels of complexity associated with those stages. Distribution of the system architecture or system control is the most important factor in terms of demanding the use of the most up-to-date distributed intelligence technologies. A tool set for web-enabled design of distributed intelligent systems is presented. Finally, the issue of intelligence control is addressed. It is argued that the dominant criterion according to which the level of intelligence is selected in technological tasks is the required precision of the resulting operation, related to the degree of generalization required by the particular task. The control of knowledge in higher-level tasks has to be executed with a strong involvement of the human component in the feedback loop. In order to facilitate the human intervention, there is a need for readily available, user-transparent computing and telecommunications infrastructure. In its final part, the paper discusses currently emerging ubiquitous systems, which combine this type of infrastructure with new intelligent control systems based on a multi-sensory perception of the state of the controlled process and its environment to give us tools to manage information in a way that would be most natural and easy for the human operator.     

信息物理融合系统

信息物理融合系统 (Cyber-physical system, CPS)是计算、通信和物理过程高度集成的系统,通过在物理设备中嵌入感知、通信和计算能力,实 现对外部环境的分布式感知、可靠数据传输、智能信息处理,并通过反馈机制实现对物理过程的实时控制. 分析了CPS的基本概念和特征,对CPS的体系架构、中间件系统、实时性、安全和隐私等关键技术的现有研究 成果进行综述,并提出了相应的研究思路;然后介绍了一些现有的CPS原型系统和实例,体现出CPS的优越性; 最后对CPS和传感器网络(Wireless sensor network, WSN)、物联网(The internet of things, IOT)、网络控制系统(Networked control systems, NCSs)进行了对比分析,总结了CPS现有研究中存在的问题,并展望了CPS的发展方向.     

Advancements of the KUCIM automated flexible manufacturing workstation

Incremental automation, i.e. adding capabilities over time, is an alternative for small mannfacturers to large scale automation projects as a method of achieving automated manufacturing. As an example of incremental automation, the University of Kansas Computer Integrated Manufacturing (KUCIM) workstation has developed over time into an unmanned flexible machining workstation. Presently, the workstation contains a Hurco three-axis milling machine, an American Robot six-axis robot, a Sun 4/260, a versatile fixturing system, an IBM PC-AT compatible computer, and an interface between the milling machine and PC. The control architecture is based on the National Institute for Standards and Technology (NIST) Automated Manufacturing Research Facility (AMRF) manufacturing control hierarchy. The workstation controller employs three software modules: the Supervisor, the Robot Foreman, and the Fixture/Machine Tool Foreman. At the equipment level, two modules are used: the Robot Command Interpreter and the Fixture/Machine Tool Command Interpreter. The three functions that the KUCIM workstation performs to produce parts are: processing an input file, performing tool zeroing and performing machining cycles.     

基于智慧车间的生产执行系统的研究及应用

为了解决中小型塑料制造企业管理系统在信息采集方式、计划实时性、灵活性等方面的不足,将射频识别Radio Frequency Identification(RFID)技术引入塑料生产车间,构建塑料制造装配车间的物料智能配送体系,形成面向离散制造业的智慧装配车间。对生产执行系统Manufacturing Execution System(MES)的架构、RFID智慧生产车间应用流程、应用可靠性等关键技术进行了研究,并对车间生产组织、制造事件和动态多变市场的响应能力进行了优化。所述内容对提升塑料制造企业核心竞争力具有重要的理论与实际意义。     

Concept design of future intelligent Earth observing satellites

This paper presents a concept design of an envisioned future intelligent Earth observing satellite (FIEOS) system. The proposed system is a space-based architecture for the dynamic and comprehensive on-board integration of Earth observing sensors, data processors and communication systems. The architecture and implementation strategies suggest a seamless integration of diverse components into a smart, adaptable and robust Earth observation satellite system. It is intended to enable simultaneous, global measurements and timely analyses of the Earth's environment for a variety of users. In particular, common users would directly access data in a manner similar to selecting a TV channel. We also discuss key technology problems, current technology development, amongst other things. It is concluded that (1) the proposed intelligent Earth observing satellite system is technically feasible; and (2) information technology and real-time information systems, for example multi-layer satellite networks connected with an organic system and on-board data processor capabilities, are crucial for implementation of the intelligent system. This revolutionary concept should dramatically impact on how Earth observing systems develop and conduct missions in the future.     

MetaMorph II: an agent-based architecture for distributed intelligent design and manufacturing

Agent technology derived from Distributed Artificial Intelligence is increasingly being considered for next generation computer-integrated manufacturing systems, to satisfy new requirements for increased integrability, configurability, adaptability, extendibility, agility, and reliability. This paper reviews our previous research on the application of the agent-based technology to intelligent design and manufacturing and describes the current research project MetaMorph II (an agent-based architecture for distributed intelligent design and manufacturing).