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Fuzzy multi-criteria analysis approach for the evaluation and classification of cognitive performance factors in flexible manufacturing systems

机译:模糊多准则分析方法在柔性制造系统中认知绩效因子的评估和分类

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摘要

Being affected from high technology, modern manufacturing systems have become more complex which means that performance factors of both individuals and manufacturing systems have become more critical due to the overloading of cognitive and decision-making tasks. In addition to this development, the classical performance measurement systems are insufficient to measure cognitive performance and the new measurement systems are needed. But converting the abstract factors of cognition to quantitative models is very difficult and complicated. In this paper, developing quantitative models for determination of cognitive performance factors is studied using the combination of cognitive mapping technique and the analytical hierarchy process in fuzzy theory to identify these factors, express and classify them quantitatively. The pairwise comparison matrices are constructed from cognitive maps, converted to fuzzy numbers using a scale, and the subjectiveness of decision-makers is prevented. Also, more accurate weights are obtained and the monitoring levels of performance factors are suggested. An example in Flexible Manufacturing Systems is provided throughout the paper in order to explain the concepts and discussion.
机译:受高科技影响,现代制造系统变得更加复杂,这意味着由于认知和决策任务的超负荷,个人和制造系统的性能因素都变得更加关键。除了这一发展之外,经典的绩效评估系统还不足以评估认知绩效,因此需要新的评估系统。但是将认知的抽象因素转换为定量模型是非常困难和复杂的。本文结合认知测绘技术和模糊理论中的层次分析法,研究了确定认知绩效因素的量化模型,对这些因素进行识别,定量表达和分类。成对比较矩阵由认知图构成,并使用比例尺转换为模糊数,从而避免了决策者的主观性。此外,可以获得更准确的权重,并建议对性能因子进行监视。全文中提供了“柔性制造系统”中的示例,以解释概念和讨论。

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