4,452 research outputs found

    Development of the evaluation system for automobile remanufacturing

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    By 2015, the EU directives required the automobile manufacturers to produce a vehicle that contains reusable and / or recoverable parts at least 95% of total weight. In the developed countries, the legislative issue the take – back policy which requires the manufacturers to consider the end – of – life (EOL) of their products at early design stage. The goal of this paper is to propose a framework of development methodology that focuses on integrated design for remanufacturing evaluation system. This system supports the automobile product design and development at the early design phase. The proposed method is divided into two phases. The first phase aims to identify the suitable EOL process. The second phase aims to verify the most economical EOL process. The proposed method incorporates the Case base Reasoning [CBR] into the remanufacturing techniques. It is expected that the proposed method can provide the EOL with decision support during designing the automobile parts at the early design stage

    Intelligent systems in manufacturing: current developments and future prospects

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    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 AI techniques are used for the components of IMS

    Optimal and intelligent decision making in sustainable development of electronic products

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    Increasing global population and consumption are causing declining natural and social systems. Multi-lifecycle engineering and sustainable development address these issues by integrating strategies for economic successes, environmental quality, and social equity. Based on multi-lifecycle engineering and sustainable development concepts, this doctoral dissertation aims to provide decision making approaches to growing a strong industrial economy while maintaining a clean, healthy environment. The research develops a methodology to complete both the disassembly leveling and bin assignment decisions in demanufacturing through balancing the disassembly efforts, value returns, and environmental impacts. The proposed method is successfully implemented into a demanufacturing module of a Multi-LifeCycle Assessment and Analysis tool. The methodology is illustrated by a computer product example. Since products during the use stage may experience very different conditions, their external and internal status can vary significantly. These products, when coming to a demanufacturing facility, are often associated with incomplete/imprecise information, which complicates demanufacturing process decision making. In order to deal with uncertain information, this research proposes Fuzzy Reasoning Petri nets to model and reason knowledge-based systems and successfully applies them to demanufacturing process decision making to obtain the maximal End-of-Life (BOL) value from discarded products. Besides the BOL management of products by means of product/material recovery to decrease environmental impacts, the concepts of design for environment and sustainable development are investigated. Based on Sustainability Target Method, a sensitivity analysis decision-making method is proposed. It provides a company with suggestions to improve its product\u27s sustainability in the most cost-effective manner
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