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A systematic decision making approach for product conceptual design based on fuzzy morphological matrix

机译:基于模糊形态学矩阵的产品概念设计系统决策方法

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Conceptual design plays an important role in development of new products and redesign of existing products. Morphological matrix is a popular tool for conceptual design. Although the morphological-matrix based conceptual design approaches are effective for generation of conceptual schemes, quantitative evaluation to each of the function solution principle is seldom considered, thus leading to the difficulty to identify the optimal conceptual design by combining these function solution principles. In addition, the uncertainties due to the subjective evaluations from engineers and customers in early design stage are not considered in these morphological-matrix based conceptual design approaches. To solve these problems, a systematic decision making approach is developed in this research for product conceptual design based on fuzzy morphological matrix to quantitatively evaluate function solution principles using knowledge and preferences of engineers and customers with subjective uncertainties. In this research, the morphological matrix is quantified by associating the properties of function solution principles with the information of customer preferences and product failures. Customer preferences for different function solution principles are obtained from multiple customers using fuzzy pairwise comparison (FPC). The fuzzy customer preference degree of each solution principle is then calculated by fuzzy logarithmic least square method (FLLSM). In addition, the product failure data are used to improve product reliability through fuzzy failure mode effects analysis (FMEA). Unlike the traditional FMEA, the causality relationships among failure modes of solution principles are analyzed to use failure information more effectively through constructing a directed failure causality relationship diagram (DFCRD). A fuzzy multi-objective optimization model is also developed to solve the conceptual design problem. The effectiveness of this new approach is demonstrated using a real-world application for conceptual design of a horizontal directional drilling machine (HDDM). (C) 2017 Elsevier Ltd. All rights reserved.
机译:概念设计在新产品开发和现有产品的重新设计中起着重要作用。形态矩阵是用于概念设计的流行工具。尽管基于形态矩阵的概念设计方法对于生成概念方案是有效的,但很少考虑对每个功能解决方案原理进行定量评估,从而导致难以通过组合这些功能解决方案原理来确定最佳概念设计。此外,在这些基于形态矩阵的概念设计方法中,未考虑工程师和客户在设计初期对主观评估的不确定性。为了解决这些问题,本研究针对模糊概念矩阵对产品概念设计开发了系统的决策方法,从而利用具有主观不确定性的工程师和客户的知识和偏好对功能解决方案原理进行定量评估。在这项研究中,通过将功能解决方案原理的属性与客户偏好和产品故障的信息相关联来量化形态矩阵。使用模糊成对比较(FPC)从多个客户那里获得不同功能解决方案原理的客户偏好。然后通过模糊对数最小二乘法(FLLSM)来计算每个解决方案原理的模糊顾客偏好度。此外,产品故障数据还用于通过模糊故障模式影响分析(FMEA)来提高产品可靠性。与传统的FMEA不同,通过构造定向故障因果关系图(DFCRD)来分析解决方案原理的故障模式之间的因果关系,以更有效地使用故障信息。为了解决概念设计问题,还建立了模糊的多目标优化模型。通过将实际应用用于水平定向钻机(HDDM)的概念设计,可以证明这种新方法的有效性。 (C)2017 Elsevier Ltd.保留所有权利。

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