1,615,834 research outputs found

    Multi-agent system for dynamic manufacturing system optimization

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    This paper deals with the application of multi-agent system concept for optimization of dynamic uncertain process. These problems are known to have a computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs bundle of intelligent systems algorithms tied together in a multi-agent system. In order to demonstrate the system, a metal reheat furnace scheduling problem is adopted for highly demanded optimization problem. The proposed multi-agent approach has been evaluated for different settings of the reheat furnace scheduling problem. Particle Swarm Optimization, Genetic Algorithm with different classic and advanced versions: GA with chromosome differentiation, Age GA, and Sexual GA, and finally a Mimetic GA, which is based on combining the GA as a global optimizer and the PSO as a local optimizer. Experimentation has been performed to validate the multi-agent system on the reheat furnace scheduling problem

    IMPACT OF AMT INVESTMENTS ON EFFECTIVENESS AND COMPETITIVENESS OF MANUFACTURING SYSTEMS

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    Every manufacturing company is a system of individual manufacturing units, which have to be carefully laid out taking into account time, space, technology, and organisation perspective in order to deliver maximum final product. In order to secure absolute effective and efficient functionality of manufacturing process all manufacturing units have to be reviewed already in stage of its planning and organising. Only continual process of measuring, evaluating and managing effectiveness of individual manufacturing units as well as whole manufacturing system will provide sustainable competitive advantage. The goal of the article is therefore propose methods of evaluation of effectiveness of Advanced Manufacturing Technology(AMT).Effectiveness, Layout, Manufacturing System, Evaluation.

    A modular hybrid simulation framework for complex manufacturing system design

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    For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

    Scheduling of non-repetitive lean manufacturing systems under uncertainty using intelligent agent simulation

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    World-class manufacturing paradigms emerge from specific types of manufacturing systems with which they remain associated until they are obsolete. Since its introduction the lean paradigm is almost exclusively implemented in repetitive manufacturing systems employing flow-shop layout configurations. Due to its inherent complexity and combinatorial nature, scheduling is one application domain whereby the implementation of manufacturing philosophies and best practices is particularly challenging. The study of the limited reported attempts to extend leanness into the scheduling of non-repetitive manufacturing systems with functional shop-floor configurations confirms that these works have adopted a similar approach which aims to transform the system mainly through reconfiguration in order to increase the degree of manufacturing repetitiveness and thus facilitate the adoption of leanness. This research proposes the use of leading edge intelligent agent simulation to extend the lean principles and techniques to the scheduling of non-repetitive production environments with functional layouts and no prior reconfiguration of any form. The simulated system is a dynamic job-shop with stochastic order arrivals and processing times operating under a variety of dispatching rules. The modelled job-shop is subject to uncertainty expressed in the form of high priority orders unexpectedly arriving at the system, order cancellations and machine breakdowns. The effect of the various forms of the stochastic disruptions considered in this study on system performance prior and post the introduction of leanness is analysed in terms of a number of time, due date and work-in-progress related performance metrics

    VALIDATING COOPERATIVE SYSTEMS SIMULATION AND REMODELING FOR PUMP COVER DESIGN AND MANUFACTURING IN A VIRTUAL ENTERPRISE

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    In order to integrate the manufacturing systems in virtual environment some changes must be made in manufacturing systems architecture. To support this environment, the basic infrastructure for the enterprise must to consider two main modules: The Internal Module, that represents the autonomous unit of a particular company and includes the manufacturing system, the complete structure of the company information (databases, information system etc.) and all the decision making processes;virtual enterprise, manufacturing systems, remodeling, simulation, cooperative systems

    Part Repair using a Hybrid Manufacturing System

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    Nowadays, part repair technology is gaining more interest from military and industries due to the benefit of cost reducing as well as time and energy saving. Traditionally, part repair is done in the repair department using welding process. The limitations of the traditional welding process are becoming more and more noticeable when the accuracy and reliability are required. Part repair process has been developed utilizing a hybrid manufacturing system, in which the laser aided deposition and CNC cutting processes are integrated. Part repair software is developed in order to facilitate the users. The system and the software elevate the repair process to the next level, in which the accuracy, reliability, and efficiency can be achieved. The concept of repair process is presented in this paper. Verification and experimental results are also discussed.Mechanical Engineerin

    Cloud-based manufacturing-as-a-service environment for customized products

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    This paper describes the paradigm of cloud-based services which are used to envisage a new generation of configurable manufacturing systems. Unlike previous approaches to mass customization (that simply reprogram individual machines to produce specific shapes) the system reported here is intended to enable the customized production of technologically complex products by dynamically configuring a manufacturing supply chain. In order to realize such a system, the resources (i.e. production capabilities) have to be designed to support collaboration throughout the whole production network, including their adaption to customer-specific production. The flexible service composition as well as the appropriate IT services required for its realization show many analogies with common cloud computing approaches. For this reason, this paper describes the motivation and challenges that are related to cloud-based manufacturing and illustrates emerging technologies supporting this vision byestablishing an appropriate Manufacturing-as-a-Service environment based on manufacturing service descriptions

    A multi-sensor based online tool condition monitoring system for milling process

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    Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications
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