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Description:
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Due to internal and external pressure , more and more manufacturing enterprises are working hard to improve the environmental performance of their products . Design for Environment (DFE ) is an efficient design methodology to reduce the negative environmental impact of products . Recently , modular design is widely used in the design of electromechanical products . In order to greatly reduce the negative environmental impact of electromechanical products , new methodology needs to be developed to integrate DFE into modular design .
The purpose of this research is to develop a quantitative environmental analysis model for modular design . The proposed model aims at providing design support in redesign of modular design ; it can be used to help designers to improve the potential environmental performance of modular design . In this research , a fuzzy graph is used to represent the structure of a modular product . A set of comprehensive environmental criteria has been established for modularity analysis after analyzing the potential environmental problems through the entire life cycle of modular products . These environmental criteria include : usage life compatibility , technology life compatibility , material compatibility , maintainability , disassembility (including geometric connection , disassembly time , disassembly energy ) and assembility . In order to quantitatively apply all these criteria to modularity analysis , all environmental criteria are thought to be fuzzy , and fuzzy numbers are used to measure the relationship between components upon each criterion . Considering the requirements of modular design , a two -step modularity analysis scheme has been developed so that the concept of DFE can be integrated into the process of modular design . The modularity analysis scheme includes similarity analysis and independence analysis . Similarity analysis pursues the similarity or compatibility within modules , and independence analysis pursues the independence between modules . Different environmental criteria have been selected for these two kinds of analysis , and fuzzy AHP is used for these two multi -criteria decision making processes . In this research , a deliverable prototype has also been developed in Microsoft Visual C++ to illustrate the proposed methodology . |