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A Fuzzy Approach for Modeling and Design of Agile Supply Chains using Interpretive Structural Modeling

机译:基于解释性结构建模的敏捷供应链建模与设计模糊方法

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Supply chain agility has opened new perspectives for efficient and intelligent manufacturing. In the arena of intense global competition, analysis of supply chain enablers and their interactions between one another decide the levels of agility. Previous research studies have effectively used Interpretive Structural Modeling (ISM) to study the relationships between identified enablers with the aid of Structural Self Interaction Matrix (SSIM), Reachability Matrix (RM) & Graph Theoretic Approach (GTA). In the present paper, fuzzy agility evaluation is deployed to spot and rank Agile Supply Chain Attributes (ASCA) of ISM identified driver enablers. The fuzzy system addressed uses linguistic variables, MATLAB & fuzzy Technique for Order Preferences by Similiarity to Ideal Solution (TOPSIS) methods for the tabulation of Fuzzy Agility Index (FAI), Fuzzy Merit Important Index (FMII) and ranking the scores of ASCA. This attempt may provide firms with engrossed information in the design of agile supply chains which will be dominant competitive vehicles in future.
机译:供应链敏捷性为高效智能制造开辟了新视野。在激烈的全球竞争中,对供应链支持者及其之间的相互作用的分析决定了敏捷性的水平。先前的研究有效地利用解释性结构建模(ISM)借助结构自交互矩阵(SSIM),可及性矩阵(RM)和图论方法(GTA)研究已识别的促成因素之间的关系。在本文中,使用模糊敏捷性评估来对ISM识别的驱动因素进行敏捷供应链属性(ASCA)的排序和排名。所解决的模糊系统使用语言变量,MATLAB和“按相似度至理想解决方案的订单偏好的模糊技术”(TOPSIS)方法对模糊敏捷指数(FAI),模糊优点重要指数(FMII)进行制表,并对ASCA的得分进行排名。这种尝试可能会为企业提供设计敏捷供应链的全神贯注的信息,而敏捷供应链将成为未来的主要竞争工具。

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