The Intelligent Manufacturing Systems

2012

The current trend of increasing quality and demands of the final product is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings. In this paper a concept of designing and building intelligent decision support systems in production management is introduced. The new approach to the design of intelligent management systems is proposed based on integration of artificial intelligence technologies (fuzzy logic, artificial neural networks ,expert systems and genetic algorithms) with exact methods and models of decisions search and simulation techniques. The proposed approach allows for creating intelligent decision support systems of complex, unstructured management problems in fuzzy conditions. The systems learn based on accumulated data and adapt to changes in operation conditions.

International Journal of Recent advances in Mechanical Engineering, 2014

This paper shows a framework of the different techniques for the design of the planning and governing components, implementation, Evolution and execution of an intelligent manufacturing system. Architecture of a modern manufacturing industry is presented, which makes possible to create specific manufactrons system for the specific tasks, depending on the self-operated analysis of its essential characteristics. The manufactronic industry concept helps in the integration of intelligence and to increase flexibility at the maximum level of the manufacturing system as well as at the minimum level of the particular machine. This concept is implemented & demonstrated in the automobile and aeronautical industries, but can be simply applied to nearly all manufacturing industries. Implementation of manufactronic techniques in the industries helps to forecast and to fulfill the rapidly varying customer requirements, to produce high quality products in sufficient quantities with reduction in costs. The Modern Intelligence Technologies are also presented in this paper.

International Journal of Manufacturing Technology and Management

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems.

Department of Electronics & communication Engineering PSIT

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial intelligence (AI) techniques to be considered and then shows how these Artificial Intelligence (AI) techniques are used for the components of intelligent manufacturing systems

Proceedings of the 15th IFAC World Congress, 2002, 2002

The authors are involved i n a major, industrially-funded, research project which is connecting manufactured components and products to the internet. The Auto-ID project will enable unique information about a particular item to be stored, retrieved, communicated to others and even used in automated decision making relevant to that item. In this way we begin to build a specification for an intelligent product-one whose information content is permanently bound to its material content. This paper will begin to explore the impact of such developments on manufacturing shop floor control and management and will in particular, examine the way in which so called distributed, intelligent manufacturing control methods can be enhanced.

IOP Conference Series: Materials Science and Engineering

The basic requirement of production is to produce as many products as possible, at the lowest cost, with the highest possible quality. These requirements can be met with the new "Intelligent Production" paradigm. In particular, this paradigm involves the use of intelligent manufacturing systems and the introduction of intelligent production management. In this article, we'll look at intelligent manufacturing systems. The intelligent manufacturing system itself is a flexible manufacturing system that can flexibly respond to changes in production requirements as well as changes in its surroundings and interact with its surroundings. As a result of these flexible responses, there is less space, reduced production and investment costs, and increased productivity.

Computers in industry, 1997

Design of Machines and Structures, 2020

Additive production technologies made the realization of individually designed, highly complicated geometric structures in practically all fields of industry and human therapy (implantation) possible. In order to minimalize the risk of failure originating from production technology the continuous development of measurements technologies provides the possibility to track the parameters of production and if necessary to ensure their modification. The great number of recorded production data (big data) at the same time can be used in the quality control of the product.

Engineering, 2021

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The Intelli gent Systems Architecture for Manufacturing (ISAM) addresses the application of intelligent systems to the manufacturing enterprise at three degrees of abstraction: I) a conceptual framework for developing metrics, standards, and performance measures, 2) a reference model architecture for conceptual design of intelligent systems, and 3) a set of engineering guidelines for the implementation of manufacturing applications. ISAM consists of a hierarchically layered set of intelligent processing nodes organized as a nested series of control loops. In each node, tasks are decomposed, plans are generated, world models are maintained, feedback from sensors is processed, and control loops are closed. In each layer, nodes have a characteristic span of control, with a characteristic planning horizon, and corresponding level of detail in space and time. Nodes at the higher levels deal with corporate and production management, while nodes at lower levels deal with machine coordination and process control. ISAM integrates and distributes deliberative planning and reactive control functions throughout the entire hierarchical architecture, at all levels, with different spatial and temporal scales at each level.