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Fuzzy regression-based mathematical programming model for quality function deployment

机译：基于模糊回归的质量函数展开数学规划模型

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摘要

Quality function deployment (QFD) is becoming a widely used customer-driven approach and tool in product design. The inherent fuzziness in QFD modelling makes fuzzy regression more appealing than classical statistical tools. A new fuzzy regression-based mathematical programming approach for QFD product planning is presented. First, fuzzy regression theories with symmetric and non-symmetric triangular fuzzy coefficients are discussed to identify the relational functions between engineering characteristics and customer requirements and among engineering characteristics. By embedding the relational functions obtained by fuzzy regression, a mathematical programming model is developed to determine targets of engineering characteristics, taking into consideration the fuzziness, financial factors and customer expectations among the competitors in product development process. The proposed modelling approach can help design team assess relational functions in QFD effectively and reconcile tradeoffs among the various degree of customer satisfaction and determine a set of the level of attainment of engineering characteristics for the new/improved product towards a higher customer expectation within design budget. The comparison results under symmetric and non-symmetric cases and the simulation analysis are made when the approach is applied to a quality improvement problem for an emulsification dynamite packing machine.
机译：质量功能部署（QFD）正在成为产品设计中广泛使用的以客户为导向的方法和工具。 QFD建模中固有的模糊性使模糊回归比经典统计工具更具吸引力。提出了一种新的基于模糊回归的QFD产品规划数学规划方法。首先，讨论具有对称和非对称三角模糊系数的模糊回归理论，以识别工程特征与客户需求之间以及工程特征之间的关系函数。通过嵌入通过模糊回归获得的关系函数，开发了数学编程模型来确定工程特性的目标，同时考虑了产品开发过程中竞争对手之间的模糊性，财务因素和客户期望。所提出的建模方法可以帮助设计团队有效地评估QFD中的关系功能，并在不同程度的客户满意度之间进行权衡，并确定新产品/改进产品在达到设计预算范围内朝着更高客户期望的一组工程特性达到水平。 。当该方法应用于乳化炸药包装机的质量改进问题时，进行了对称和非对称情况下的比较结果以及仿真分析。

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