A framework for designing intelligent manufacturing systems

Rzevski, George

doi:10.1016/s0166-3615(97)00056-0

Cited by 29 publications

(9 citation statements)

References 1 publication

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“…They can utilize several AI technologies in order to perform their intended functions. Intelligent manufacturing systems can be designed in such a way that they can operate when it is difficult to measure the outcomes, where frequent changes in operations are possible and when there are no available prior decisions about the system behaviour (Rzevski, 1997).…”

Section: Intelligent Manufacturing Systemsmentioning

confidence: 99%

Intelligent Manufacturing Systems

Öztemel

2010

Springer Series in Advanced Manufacturing

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This chapter provides information on intelligent manufacturing systems including an analysis on change and historical progress of manufacturing systems as well as a brief review of traditional manufacturing systems. Fundamental technologies of artificial intelligence are also reviewed in order to establish the baseline for intelligent manufacturing systems. Following that, basic characteristics of intelligent manufacturing and respective architectures are provided. Some examples of the applications of intelligent manufacturing systems are highlighted.Keywords Artificial intelligence, manufacturing system, fuzzy logic, genetic algorithm, holonic manufacturing system IntroductionAutomation is one of the major indicators of the change in manufacturing. Machines behaving themselves not only decrease the cost but also produce the products to be more compliant with the needs and specifications of the customers. Although technologies such as flexible manufacturing systems provide various advantages, automation itself is not enough to provide competitive advantage. In most of the modern manufacturing facilities, machines are capable of making decisions and exhibiting intelligent behaviour. That is to say that the manufacturingrelated activities starting from the design to product shipment are being carried out through intelligent manufacturing technologies. As traditionally known, manufacturing systems are the integrated combination of various functions such as design, process planning, production planning, quality assurance, storing and shipment etc. In each of these functions several activities are carried out. Intelligent behaviour is exhibited by the machines in all of these functions. This diverted the attention of the researcher to "unmanned factories" and there have been quite interesting studies and implementations along this line. In this chapter, a general overview E. Oztemel ( ) Marmara University, Engineering Faculty,

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Section: Intelligent Manufacturing Systemsmentioning

confidence: 99%

Intelligent Manufacturing Systems

Öztemel

2010

Springer Series in Advanced Manufacturing

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“…Rzevski (1997) analysed and introduced some artificial intelligence factors that were suitable for a multi-agent environment. A distributed 1315 Solving part selection and task allocation problem in FMS manufacturing environment consisting of different agents was proposed by Gu (1997) that created a model for process planning and production scheduling.…”

Section: Related Workmentioning

confidence: 99%

Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

Tripathi¹,

Tiwari²,

Chan

2005

International Journal of Production Research

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Agent technology is currently being considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. A multiagent-based approach for solving the part allocation problems in flexible manufacturing systems (FMS) is presented that can easily cope with the dynamic environment. Four agents were involved in carrying out the tasks of allocating parts on different machines: communicator, machine, part and material handling device (MHD). Upon arrival in the manufacturing facility, the part informs the communicator agent about the task requirements. The communicator agent divides the task into subtasks and sends a call-for-bids message to the machine and MHD agents. Each machine responds in accordance with its process capabilities and buffer limit. This response may be for the whole task or for one or more subtasks and it contains the price and cost details for these subtasks along with the performance index and acceptance ratio of the machine. The final allocation is made based on the objective function that includes processing and transportation costs and time. An algorithm is presented that is used by the communicator agent for allocating parts to different machines. An illustrative example is given to solve the task allocation on five machines, with each machine having different performance index and acceptance ratio.

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“…Kim (1997) proposed the cooperation mechanism between process planning and production plan control, and designed the cooperation model that consisted of part agents and resource agents. Rzevski (1997) analysed and introduced some arti®cial intelligence factors to fabricate a multi-agent environment. Gu (1997) presented a distributed manufacturing environment that comprises di erent agents and creates models for process planning and production scheduling.…”

Section: Recon®gurable Control Systemmentioning

confidence: 99%

Investigation of the reconfigurable control system for an agile manufacturing cell

Zhang

Chan

et al. 2002

International Journal of Production Research

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A new type of manufacturing cell, with characteristics of recon®gurability, reusability and scalability, needs to be developed. To achieve the agile recon®gura-tion of a manufacturing cell, the cell control system must be rapidly and e ciently generated or modi®ed. In this paper, a multi-agent based architecture is de®ned that supports the design and implementation of highly recon®gurable control systems for agile manufacturing cells, which are comprised of resource agents (material processing agents, material handling agents, and material storage agents), a control agent, and an information agent, in order to reduce costs and increase the control system's agility with respect to the changing environment. Di erent agents in the cell control system can be organized dynamically, communicate with each other through messages, and cooperate with each other to perform¯exibly the task in the cell control system. The structure of the agents is proposed and the message-passing between agents is discussed in detail.

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A framework for designing intelligent manufacturing systems

Cited by 29 publications

References 1 publication

Intelligent Manufacturing Systems

Intelligent Manufacturing Systems

Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

Investigation of the reconfigurable control system for an agile manufacturing cell

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