QUALITY ASSURANCE INFORMATION SYSTEM FOR AGILE MANUFACTURING

The customer driven dynamic global market and geographical distribution of collaborating partners bring new challenges to the development of quality assurance information system (QAIS) for agile manufacturing. With recent dramatic advances in information technology, firstly the requirements of QAIS are examined in agile manufacturing environment, then a new implementation framework of a distributed QAIS is presented, where a deve loping environment of QAIS is established and some critical techniques are studied. Finally a prototype system based on world wide web (WWW) is accomplished.

An Agent-Oriented Modelling Approach for Agile Manufacturing

The dynamic variations in demand patterns and produ ct mix, driven by unpredictable changes in a global market, are placing manufactur ing systems under significant pressure. In order to remain competitive, manu facturing organisations must satisfy demands timely. This implies that companies must increase product varieties, reduce time-to-market, shorten product-life cycles and at the same time maintain good quality and reduce investment costs. Conventional methodologies for planning and control have been found to be inadeq uate in meeting these challenges. Agile manufacturing is the state-of-the-art concept that provides enterprises with the opportunity to react rapidly and cos t-effectively to changes that occur in their environment. Several paradigms suc h as Holonic Manufacturing Systems (HMS), Bionic Manufacturing Systems (BMS) and Fractal Factory have been developed to enable manufacturing systems achieve agi lity by integrating manufacturing activities into a coordinated framework. Despi te the differences in their origin (HMS from social organisation, BMS from biolo gy and Fractal Factory from Mathematics), these paradigms have overlapping conce pts and one of the most important is hierarchical organisational structure. This paper presents a conceptual hierarchically structured multi-agent architec ture for manufacturing systems’ modelling. Multi-Agent Systems (MAS) provide su itable techniques for implementing the above concepts and as a branch of Distrib uted Artificial Intelligence (DAI), have characteristics that have been explored in various applications. Such characteristics include self-organisation, flexi bility, scalability, and robustness. The proposed architecture provides a suit able decision-making framework where each agent represents a node in the hier archic tree of manufacturing systems such as the company as whole, each plant wi thin the company, each cell or line within the plant, each machine in a cell or line. Each agent has the ability to perceive and evaluate changes that occur in the manufacturing environment, interact with other agents in the system in order to reach an optimal decision, and act based on that decision. In other words, agents respond timely to unexpected changes by continuously co-ordinating t heir activities, and allocating manufacturing resources dynamically based on act ual shop-floor situation. The flexibility of this architecture also lies in its ability to accommodate both homogenous and heterogeneous agents, and its capabi lity for the dynamic addition and removal of agents using a conceptual intellige nt communication mechanism similar to the blackboard messaging system. A Bidding -Based Scheme (BBS) would be used to generate and evaluate alternative scenario at run-time. In addition, this architecture can be extended to meet the requir ements of enterprise integration.

A Heuristic for Resource Reconfiguration of Agile Manufacturing Supply Chain

The agile manufacturing is a new conception for rap id reaction to the consumers. One of its implements is establishing a virtual ente rprise (VE) around the task, where each manufacturing unit, or sub-task, probab ly have at least one resource, or referred to as suppliers. Because each manufac turing unit might be carried out in different geographical places that implies t his probably gives rise to transportation cost, the selection of resources for e ach manufacturing unit must considers not only the manufacturing price of each r esource but also the transfer cost between any two potential resources. This pap er discusses the resource reconfiguration problem with two hypotheses: 1. Permit s one or more resources to attend the same manufacturing unit as long as the tot al cost can reach its least; 2. The freight contains the initial part, that is t he freight concave. Indeed, these hypotheses are much meaningful in the real wor ld. Furthermore, to simplify the solution for this problem, we propose two conce pts: assembly tree (AT) and combinatorial mode base (CMB). Formally an AT is a c omplete production line, which can ensure the parts equilibrium, and its capacit y is subjected to the least capacity of every resources and every path in it. In the end, we propose an implicit enumeration algorithm (IEA) by the use of CMB, including it is a heuristic algorithm for integer programming (HAIP) by the use of AT. The IEA can be outlined that for a determined combinatorial mode, if it h as not enumerated, we use the HAIP to get an near optima and corresponding CMB, marking every combinatorial mode extended from the CMB as enumerated, other cont inue a new iteration. The HAIP can be outlined that for a determined combinatori al mode, there are some determined number of AT, we select an AT with the le ast slope, and select the volume of this AT to its ultimate within its capacity, iterates this doing until the needed volume reached. In the end, we conclude th is paper and prospect the deep research based on GA thought.

Problems of Production Management in Agile Manufacturing Environment and their Countermeasures

Agile manufacturing is a new production mode. This pa per discusses the four problems of production management in the environment of a gile manufacturing, and some countermeasures are advanced: (1) Organization of production. Traditional MTO production or MTS production ca n not meet the requirement of agile manufacturing which request both high produc tivity and the manufacturing flexibility. For this, the paper advances best way is to use the production organization mode of MCP (Mass Customization Production ),and some strategies of MCP are discussed. (2) Production planning. The requirement of agile manufacturing to production pl anning embodies in two facets: synchronization and flexibility. The paper su ggests that the structure and function of MRPII system should be improved in ord er to meet the demand of agile manufacturing. (3) Production control. The problem of production control is how to reduce the u ncertainty of hand over time between enterprises and increase the production syn chronization level. The paper advances some research direction on improving production ability. (4) Quality control. The problems of quality management are how to transfer the information of customer’s quality requirement between different organizations an d how to keep the consistency and stability of quality. Some countermeasures are advanced. In the end of the paper, one case advanced administrates how to utilize the thou ghts of agile manufacturing to upgrade the competition ability.

Modeling of Agile Manufacturing Execution Systems with an Agent-based Approach

Agile manufacturing execution systems (AMES) are used to help manufacturers optimize shop floor production in an agile way. And the modeling of AMES is the key issue of realizing AMES. This paper presents an agent-based approach to AMES modeling. Firstly, the characteristics of AMES and its requirements on modeling are discussed. Secondly, a comparative analysis of modeling methods is carried out, and AMES modeling using an agent-based approach is put forward. Agent-based modeling method not only inherit the favorable features of traditional object-oriented modeling method such as data encapsulation, modularity and so on, but also has the ability to construct intelligent, rational and autonomous agent which can cooperate together to realize the goal of agile operation. A general agent architecture used in AMES modeling is described. Under this architecture, an agent can be divided into domain-independent components and domain-specific components which helps solve problems such as information overload, incomplete information handling and soft decision-making. Furthermore, an AMES model using four types of agents, i.e., interface agent, information agent, resource agent and management agent, is established. Thirdly, a snapshot of AMES model is provided in the case study. Especially, an agent-based cooperating process of task scheduling in AMES is illustrated in detail. Finally, the advantages and disadvantages of this modeling approach are discussed as well.

Research on an Agile Manufacturing Information System

With the more intense competition in the worldwide market, the agile virtual enterprise (AVE) will become a new organization form of manufacturing enterprise. To support the new relationship, an agile manufacturing information system (AMIS) is described in this paper which serves to assist the virtual enterprise to manage and control information flow among collaborating partners. Based on the requirement analysis of virtual information system, the architecture, functions, features and execution scheme of AMIS are discussed in detail.

Event-driven Dynamic and Intelligent Scheduling for Agile Manufacturing Based on Immune Mechanism and Expert System

Based on the biological immune concept, immune response mechanism and expert system, a dynamic and intelligent scheduling model toward the disturbance of the production such as machine fault,task insert and cancel etc. Is proposed. The antibody generation method based on the sequence constraints and the coding rule of antibody for the machining procedure is also presented. Using the heuristic antibody generation method based on the physiology immune mechanism, the validity of the scheduling optimization is improved, and based on the immune and expert system under the event-driven constraints, not only Job-shop scheduling problem with multi-objective can be solved, but also the disturbance of the production be handled rapidly. A case of the job-shop scheduling is studied and dynamic optimal solutions with multi-objective function for agile manufacturing are obtained in this paper. And the event-driven dynamic rescheduling result is compared with right-shift rescheduling and total rescheduling.

Research on Business Processes Optimization for Agile Manufacturing

Based on macroscopic and synthetic approaches, especially information entropy approach, the quantification of the flexible degree and order degree of business processes is studied. According to the outcome of above analysis, a conceptual model of optimizing business processes is proposed which supports to construct dynamic stable business processes. The research above has been applied in project 863/SDDAC-CIMS, and achieved primary benefits.

Design of Scheduling Decision Mechanism for Agile Manufacturing System

Design of scheduling decision mechanism is a key issue of scheduling decision method and strategy for agile manufacturing system. Effective scheduling decision mechanism helps to improve the operational agility of manufacturing system. Several scheduling decision mechanisms are discussed, including scheduling forecasting mechanism, cooperation mechanism and cell scheduling mechanism. Also soft decision mechanism is put forward as a promising prospect for agile manufacturing system, and some key techniques in soft decision mechanism are introduced.

Conceptual Framework and Curriculum for Networked Agile Manufacturing

Networked agile manufacturing (NAM) is a new manufacturing paradigm for the 21st century. Manufacturing businesses based on NAM are characterized by virtual organization, innovation, global sourcing of materials and production centered on the workforce. Therefore, NAM requires a knowledgeable, motivated workforce. This paper reviews the literature related to developing an NAM curriculum to: (1) review the progress for organizing manufacturing information, (2) study the fundamental technologies impacting NAM, including product data management (RDM), enterprise resource planning (ERP), and component/supplier management (CSM), (3) present a definition of NAM and its conceptual framework, and (4) generalize the basic NAM curriculum. The NAM curriculum can be used for developing a manufacturing course.

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

Evaluation of Agile Manufacturing Enterprises

Agile manufacturing is an important manufacturing philosophy to develop advanced manufacturing enterprises to improve competivity. The evaluation of Agile Manufacturing Enterprises (AME) is one of the key activities in implementing agile manufacturing. This paper proposes a method for evaluating AME, establishes a basic feature model of AME based on the feature tree and discusses the hierarchical decomposition algorithm based on the model with an example.

Assessing Enabling Competence of Leagile Manufacturing Model and Its Impact on Performance of Small and Medium Factories in Uganda

Purpose: Leagile manufacturing is one of the time-based manufacturing practices used to improve factory performance. It is a practice that combines initiatives of Lean and agile manufacturing under certain enabling competences. Therefore, the purpose of this study is investigate the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. Methodology: Firstly, the underlying factor structure of competences and time-based manufacturing was examined was conducted using Principal Component Analysis (PCA). Enabling competences and time-base manufacturing practices were modelled and validated for each using confirmatory factor analysis, particularly composite reliability, average variance extracted and convergent validity. A fully fledged structural equation model was used to test the impact of leagile manufacturing on performance of factories. Findings: The study results revealed that time-based manufacturing of lean, and leagile are related but differ, in terms of their enabling competences and philosophical orientation. The findings also revealed that when small and medium factories in Uganda adopt leagile practice, they are likely not improve their performance. This is perhaps due to the fact that small and medium factories have inadequate resources. Practical Implications: The study findings shed more insights on the factors that enable adoption and implementation of time-based manufacturing practices. The extent to which these competences are orchestrated determines the benefits derived from the time-based manufacturing practices. In addition, small and medium enterprises should keenly make a choice on the appropriate practices that purposely reduce their lead time and cost of conversion. Originality: This study investigated the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. It is among the few studies that provide evidence on the leagile model anchored in the appropriate enabling competences in the context of developing countries. The empirical survey was done on small and medium factories to validate a leagile manufacturing model and tested its impact on factory performance.

Agile Manufacturing of Complex Moulds For Punch Devices

This paper focuses on agile manufacturing of complex moulds for punch devices and a decision analysis for the key link of agile manufacturing resources integration—the virtual company in a multivariate criterion universe of discourse. On the basis of presenting an agile manufacturing model of complex moulds for punch devices, we give a fuzzy decision method of two level judgment space of synthetic decision and several key problems which the production of complex moulds for punch devices must face under the architecture hierarchy of agile manufacturing. We give a fuzzy decision method of two level judgment space of synthetic decision and several key problems which the production of complex parts must face under the architecture hierarchy of agile manufacturing.

Flexible ERP:Enterprise Information System Under the Agile Manufacture Mode

Flexibility is the demand of management revolution,and also the milestone of management development.The flexible ERP system is the information system to orientate variety and handle uncertainties.The market with rapid change and agile manufacture need a flexible ERP system.The article elaborates the meanings and characteristics about flexibility,the flexibility of ERP and the flexible ERP system;it discussed the necessity,the possibility and the related condition of setting up the flexible ERP system;and puts forward the strategy and the approaches of setting up the flexible ERP system.

Regarding the Regulatory Sandbox Route and Mechanism for Governance of Artificial Intelligence

The main challenge in AI governance today is striking a balance between controlling AI dangers and fostering AI innovation.Regulators in a number of nations have progressively extended the regulatory sandbox,which was first implemented in the banking sector,to AI governance in an effort to reduce the conflict between regulation and innovation.The AI regulatory sandbox is a new and feasible route for AI governance in China that not only helps to manage the risks of technology application but also prevents inhibiting AI innovation.It keeps inventors'trial-and-error tolerance space inside the regulatory purview while offering a controlled setting for the development and testing of novel AI that hasn't yet been put on the market.By providing full-cycle governance of AI with the principles of agility and inclusive prudence,the regulatory sandbox offers an alternative to the conventional top-down hard regulation,expost regulation,and tight regulation.However,the current system also has inherent limitations and practical obstacles that need to be overcome by a more rational and effective approach.To achieve its positive impact on AI governance,the AI regulatory sandbox system should build and improve the access and exit mechanism,the coordination mechanism between the sandbox and personal information protection,and the mechanisms of exemption,disclosure,and communication.

Research of Agile Supply Chain Management Decision Support System

Agile Supply Chain Management (ASCM) is an important topic and has received much attention recently. ASCM is a new management technology. Agile Supply Chain Management Decision Support System (ASCM DSS) is presented. Firstly, agile supply chain management technology is introduced. Secondly a decision support system for agile supply chain management is proposed. Then, the implementation of ASCM DSS in enterprise is discussed. Finally, a fuzzy intelligence decision making process in Shanghai Turbine Generator Company (STGC) is described in detail.

Intelligent manufacture adapts to agile manufacture production mode in the 21st century

The paper describes the characteristics of the intelligent manufacturing system and production mode in the 21st century in the information age, therefore draws a conclusion that the intelligent manufacturing system adapts to agile manufacture (AM for short) production mode in the 21st century.

人工智能风险治理:模式、工具与策略

人工智能技术在近二十年飞速迭代,由此产生的风险治理挑战呼唤治理模式与治理工具的创新。规制型治理、创新型治理、自治型治理、市场导向型治理、集中式治理、敏捷治理是目前较为成熟的风险治理模式,法律规制、伦理规范、数据算法、社会场景等领域的新兴风险催生更具体、更灵活的风险治理工具,以适应新涌现的风险治理需求。中国坚持人工智能技术创新与风险治理的协同改进和动态均衡,逐步向敏捷治理模式转变,各具体领域的风险治理工具呈现全面性、及时性、精准性的特征。中国应从治理理念更新、多元主体协同、强度刚柔并济、工具灵活有效、追求可信目标等方面提升风险应对能力,并将国家、政府、企业、公众纳入风险治理模式构建全过程,实现治理工具在各领域的多维组合性使用。

生成式人工智能个人信息安全挑战及敏捷治理

生成式人工智能秘密收集个人敏感数据,冲破“知情同意”原则和“最小必要”原则的限制,或将使信息关联违法高发。生成式人工智能信息收集行为主动、收集内容全面、泛化能力强劲,对“知情同意”原则和“最小必要”原则带来严重挑战。宏观层面,我国现有民事法律无力于数据安全治理,刑事法律缺乏明确的违法计量标准,由行政法规挑起数据法治大梁。微观层面,我国现有法律规范体系对被侵权人加以不合理的举证义务,司法救济路径单一,不利于权利救济。选择风险控制路径,从算法协议透明化、治理场景化和多方位协同化应对信息关联违法等方面展开制度构建,引入个人敏感数据单独监管制度和预防性公益诉讼制度破解该困局。