Agent-based intelligent system development for decision support in chemical process industry

This paper presents an agent-based intelligent system to support coordinate manufacturing execution and decision-making in chemical process industry. A multi-agent system (MAS) framework is developed to provide a flexible infrastructure for the integration of chemical process information and process models. The system comprise of a process knowledge base and a group of functional agents. Agents in the system can communicate and cooperate with each other to exchange and share information, and to achieve timely decisions in dealing with various scenarios in process operations and manufacturing management. Process simulation, artificial intelligent technique, rule-based decision supports are integrated in this system for process analysis, process monitoring, process performance prediction and operation suggestion. The implementation of this agent-based system was illustrated with two case studies, including one application in process monitoring and process performance prediction for a chemical process and one application in de-bottlenecking of a site utility system.     

Design of expert systems for integrated production automation

An approach to the design of expert systems for integrated production automation is presented. The major components in an integrated manufacturing system consist of corporate planning, marketing planning, research and development, engineering design, production planning, manufacturing, warehousing, and product distribution. These components are linked by management information flow, technology information flow, as well as materials flow. An intelligent computer is used to integrate information flow and to control materials flow. This paper discusses characteristics of the future factory, elements of knowledge based systems, and the design of computer based expert systems for production planning, for engineering design, and for integrated manufacturing.     

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.     

An Intelligent Online Monitoring and Diagnostic System for Manufacturing Automation

Condition monitoring and fault diagnosis in modern manufacturing automation is of great practical significance. It improves quality and productivity, and prevents damage to machinery. In general, this practice consists of two parts: 1)extracting appropriate features from sensor signals and 2)recognizing possible faulty patterns from the features. Through introducing the concept of marginal energy in signal processing, a new feature representation is developed in this paper. In order to cope with the complex manufacturing operations, three approaches are proposed to develop a feasible system for online applications. This paper develops intelligent learning algorithms using hidden Markov models and the newly developed support vector techniques to model manufacturing operations. The algorithms have been coded in modular architecture and hierarchical architecture for the recognition of multiple faulty conditions. We define a novel similarity measure criterion for the comparison of signal patterns which will be incorporated into a novel condition monitoring system. The sensor-based intelligent system has been implemented in stamping operations as an example. We demonstrate that the proposed method is substantially more effective than the previous approaches. Its unique features benefit various real-world manufacturing automation engineering, and it has great potential for shop floor applications.     

数字孪生与生产线仿真技术研究

随着新一代信息技术与制造技术的深度融合,仿真技术正向着信息系统与物理系统深度融合和高效协同的方向发展,应运而生的数字孪生技术成为近年来的新兴研究热点.为探索采用新一代信息技术促进离散制造行业数字化转型升级,从仿真技术的发展脉络和应用场景入手,引入基于数字孪生技术开展生产线仿真分析的研究,介绍了数字孪生技术的概念和内涵,...     

复杂工业过程智能优化决策系统的现状与展望

流程工业是制造业的重要组成部分,是我国国民经济和社会发展的重要支柱产业.新一代信息技术和人工智能技术为流程工业的发展带来新的挑战和机遇.只有与流程工业的特点与目标密切结合,充分利用大数据,将人工智能、移动互联网、云计算、建模、控制与优化等信息技术与工业生产过程的物理资源紧密融合与协同,实现流程工业智能优化制造,才可能实现流程工业的跨越式发展.本文聚焦流程工业的复杂生产过程,从其智能优化决策系统的角度,描述了复杂工业过程优化决策系统的问题、回顾总结了复杂工业过程全流程优化决策系统的现状,分析了智能优化决策系统的必要性,提出了智能优化决策系统的发展目标及愿景,并对智能优化决策系统的下一步重点研究方向进行了展望.     

全局性视角下SMIS鲁棒性分析及控制策略研究

当前我国制造业正在转型关键期,智能制造信息系统SMIS的鲁棒性是发展智能制造的瓶颈问题。基于此,本文就SMIS系统的鲁棒性分析和控制策略展开论述,以期找到合适的解决方法,为智能制造系统转型升级提供一点有意义的参考。     

A collaborative architecture of the industrial internet platform for manufacturing systems

One of the most significant advances in the development of intelligent manufacturing is represented by the industrial Internet, which is combining the physical and cyber components in manufacturing systems together. Aiming to manage the interaction between the physical and cyber components, this paper proposes a collaborative architecture for industrial Internet platform (IIP) called industrial operation system (Ind-OS), which contains the industrial driver, digital thread and micro-services to provide a better cooperative enterprise information system (EIS) environment for manufacturing systems. The industrial driver in the edge layer is presented for each resource unit for communication, computation, control, identification, insight and interoperation, realizing a ``plug and play" fashion in IIP. The digital thread is designed to link all resource units and meta-data, which consists of a digital resource chain and an integrated information chain. In the application layer, all the businesses in EIS are decoupled into different micro-services, and a “Jigsaw Apps” is recombined to support the operation of manufacturing systems. A case study illustrates the effectiveness of the proposed Ind-OS, and the impacts caused by the Ind-OS are discussed.     

AutoCAD 2000图形数据库中的零件总体信息的提取方法

文章详细论述了用ObjectARX2000开发工具,自动提取AutoCAD2000图形数据库中的零件总体信息,并自动添加到MicrosoftSQLServer数据库中的方法。利用这种方法,可以获取AutoCAD2000图纸中零件的总体信息及工艺信息等,对CAPP系统的开发及实现CAD与CAPP之间的信息共享都具有重要意义。     

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.     

The complementary roles of expert systems and database management systems in a design for manufacture environment

Effective product design that satisfies functional requirements and can be manufactured easily requires vast amounts of knowledge on the part of the design engineer. This paper focuses on the complementary roles of expert systems and database management systems as they relate to the Intelligent Design System (IDS) in a Design for Manufacture (DFM) environment. Each technology complements the other in its strengths and abilities. The database management system provides during the design process. The expert system provides a reasoning mechanism for identifying manufacturing violations and generating meaningful recommendations. These components work cooperatively with a CAD interface to form a unified, intelligent design environment.An information flow analysis of the Intelligent Design System resulted in the development of three distinct classifications of information within the database: CAD data, a design catalog, and a knowledge base. The CAD data tables employ an, object oriented approach to store specific information about the physical contains cost, weight, and strength characteristics of the standard parts and fasteners used within the system. The knowledge base contains rules and heuristics concerning design and manufacturing methodologies.The placement of the expert system rules in the database represents an innovation. As a result, the expansion and updating of the materials, fasteners, standard parts, or manufacturing processes used by the Intelligent Design System is facilitated without increased due to the efficient management of the knowledge base by the database management system. This allows the designer to modify the knowledge and help the system to learn without the need for a knowledge engineer.     

Engineering framework for agent-based manufacturing control

MAS (multi-agent systems) and HMS (holonic manufacturing systems) are enabling the vision of the Plug & Play Factory and paving the way for future autonomous production systems. This paper reviews the state of the art in implementations of agent-based manufacturing systems, and identifies the lack of engineering tools as a technological gap for widespread industrial adoption of the paradigm. The lack of tools limits the implementation of agent-based manufacturing systems within reach of only a handful of domain experts. One of the current challenges for the design and implementation of intelligent agents is the simulation and visualization of the agent societies. This issue is significant as soon as the software agent is embedded into a mechatronic device or machine resulting in a physical intelligent agent with 3D-mechanical restrictions. These mechanical restrictions must be considered in the negotiations between agents in order to coordinate the execution of physical operations. This paper presents an engineering framework that contributes towards overcoming the identified technology gap. The framework consists of a comprehensive set of software tools that facilitate the creation, simulation and visualization of agent societies. The 3D framework is innovative in fully emulating the deployed agents, recreating multi-agent negotiations and societies that coordinate and execute control of assembly operations. The documented research describes the methodology for the 3D representation of individual physical agents, the related identified objects present in the interaction protocols, and the assembly features and clustering algorithms.     

A knowledge-based system for information management in an automated and integrated manufacturing system

In recent years there has been considerable interest in flexible automation of manufacturing processes in an effort to improve the productivity of manufacturing industry. Central to an integrated, flexible and intelligent manufacturing system is the information management function. The sharing of data is the basis of flexible and intelligent decision-making, the means of integrating the system components, the mode of synchronizing their processes and the method of maintaining the consistency of their states.

It appears that the data management and manipulation function in manufacturing systems is increasingly becoming a bottleneck for further performance improvement of manufacturing systems. New information management systems need to be developed that meet the needs of modern manufacturing systems in terms of efficiency, flexibility, reliability and intelligence. A new model for an integrated manufacturing information system is presented. A double structure of two parallel but independent system is proposed for manufacturing control and manufacturing information management. The objective is to improve service efficiency. representational adequacy, consistency of information and reliability in the information system.     

Manufacturing in the Digital Age: Exploiting Information Technologies for Product Realization

Information technology (IT) is both the key enabler for future manufacturing enterprises and a transformer of organizations and markets. By reducing barriers to collaboration, compressing lead time, eliminating physical movement, and enriching decision-making, IT helps manufacturers achieve their goal of meeting customer needs better, quicker, and cheaper. By providing global reach and easy connectivity, information technology has fostered cooperation while increasing market competition, and heightened customer expectations. Advances in computer and communication technologies combined with rapid changes in organizations have created new opportunities for exploiting information technologies in the entire product realization process. This paper explores these opportunities, and identifies promising directions for both basic and applied research. We first review important trends in organizations, markets, and information technologies—from increasing customer involvement and opportunistic organizational alliances to global reach and connectivity, enterprise integration, and virtualization. Adopting a process viewpoint of the product realization cycle, we translate these trends into high-impact IT applications in design and operations that offer rich potential for applied research and development. Underlying these applications are four broad classes of intelligent information processes—intelligent search, diagnosis and prognosis, collaboration, coordination, and negotiation, and understanding and learning. And, software agents provide an ideal platform to implement these processes. We briefly review developments in these basic research fields, and identify necessary scientific advances that are most important from the manufacturing perspective. Our goal is to synthesize streams of thought from many related disciplines in engineering, science, and management, and develop a framework for examining how information technologies can facilitate and influence manufacturing.     

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.     

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.     

Expert systems: An application in flexible manufacturing

Flexible manufacturing systems (FMS) are needed to provide manufacturing operations with the capability to adjust, in real time, to changes in the manufacturing environment. Realization of the goals of flexible manufacturing is governed by the ability of the FMS to maintain adequate information on the factory to assist in generating scenarios from product planning to operations and performance. This leads to a view where the factory is represented as an integrated information system. To facilitate the analysis of information requirements and the design of information systems for flexible manufacturing, an expert support system (ESS) which can be used to model and study the various structures is described. This ESS uses the information cell model to build these information structures. Petri net representations of these structures and their interactions are then constructed. The ESS may now be used to exercise these models and study their performance using time and cost measures.     

智能制造下产品数字孪生体全生命周期研究

针对信息物理融合系统在智能制造领域中的应用新范式,提出了产品数字孪生体全生命周期的理论框架.数字孪生的出现为信息物理融合理念的实现提供可行的思路和途径.从数字孪生概念的发展背景出发,分别从物理对象和物理对象的发展过程分析数字孪生和数字孪生体的定义,在此基础上进一步分析了数字孪生体全生命周期的内涵和特征.数字孪生体全生命...     

Digital twin-based smart assembly process design and application framework for complex products and its case study

With rapid advances in new generation information technologies, digital twin (DT), and cyber-physical system, smart assembly has become a core focus for intelligent manufacturing in the fourth industrial evolution. Deep integration between information and physical worlds is a key phase to develop smart assembly process design that bridge the gap between product assembly design and manufacturing. This paper presents a digital twin reference model for smart assembly process design, and proposes an application framework for DT-based smart assembly with three layers. Product assembly station components are detailed in the physical space layer; two main modules, communication connection and data processing, are introduced in the interaction layer; and we discuss working mechanisms of assembly process planning, simulation, predication, and control management in the virtual space layer in detail. A case study shows the proposed approach application for an experimental simplified satellite assembly case using the DT-based assembly application system (DT-AAS) to verify the proposed application framework and method effectiveness.     

Life-cycle data management of engineered-to-order components using radio frequency identification

Management of engineered-to-order (ETO) components and their related information is a challenging task due to the complexity of information and its flow. Different information items are generated, accessed and exchanged between different organizations and they must continually flow through design, production, construction, and operations and maintenance. Current manual and labor-intensive methods are inefficient; as a result, information is frequently incomplete, inaccurate or unavailable during the life-cycle of a facility. This paper provides a vision of intelligent components, which know their identities, locations and history, and communicate this information to their environments. It proposes streamlining information flow through supply chains by utilizing radio frequency identification (RFID) technology. To explore the technical feasibility of intelligent components, component-related information flow patterns in ETO supply chains were identified and analyzed. Requirements analysis and corresponding technology deployment and testing were performed for three types of ETO components through different life-cycle phases. These experiments demonstrated that it is technically feasible to have intelligent components in construction supply chains by using RFID technology; that status information can be collected automatically; and that maintenance information can be stored and retrieved during the service life of a facility.