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An integrated model for robot selection in robotic cells under uncertain situations

机译:不确定情况下机器人单元中机器人选择的集成模型

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摘要

Robots have become an extremely important part of society today; therefore, optimal selection of a robot is more important than ever. Companies, decision-makers and experts have experimented with several methodologies for selecting the proper robot to meet their needs and make an overall good business decision. This paper applies fuzzy AHP with QFD to compensate for the vagueness and imprecision of the data to provide the best ranking and customer needs for the weights given for the options to make an optimal selection for a robot. The case study discusses how this is an important aspect of a production environment and how it can provide great benefits with proper implementation.
机译:如今,机器人已成为社会中极为重要的一部分。因此,最佳选择机器人比以往任何时候都更为重要。公司,决策者和专家已经尝试了几种方法,以选择合适的机器人来满足他们的需求并做出总体良好的商业决策。本文应用带有QFD的模糊AHP来补偿数据的模糊性和不精确性,从而为最佳选择权重提供最佳排名和客户需求,从而为机器人做出最佳选择。该案例研究讨论了这如何成为生产环境的重要方面,以及如何通过适当实施为它带来巨大的好处。

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