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基于混合层次分析法-逼近理想解排序法的多准则决策技术在燃油滤清器装配过程中的协作机器人选型

Cobot selection using hybrid AHP-TOPSIS based multi-criteria decision making technique for fuel filter assembly process.

作者信息

C Sivalingam, Subramaniam Senthil Kumar

机构信息

School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014, India.

出版信息

Heliyon. 2024 Feb 15;10(4):e26374. doi: 10.1016/j.heliyon.2024.e26374. eCollection 2024 Feb 29.

Abstract

The choice of a suitable collaborative robot (cobot) for a real-time industrial process is one of the obstacles to effective robot implementation in terms of energy and cost. The cobot selection process for an application have become more complex due to increasing sophisticated features and capabilities in cobots offered by the manufacturers. The paper presents a hybrid Multi-Criteria Decision-Making (MCDM) technique based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches for selecting cobots for fuel filter assembly operation. The product design methodology, manufacturing method, and associated cost are directly influencing the decision on cobot selection. The most appropriate robot to accomplish the desired task at the lowest possible cost and capability can be selected by AHP with prospective criterion weight for subsequent processing. The TOPSIS approach orders alternatives based on the prominence of criteria. A diesel fuel filter assembly process case was considered for validating the proposed technique of cobot selection process. An expert knowledge base was generated for 12 advocated cobots and the best cobot was selected using the proposed hybrid MCDM technique.

摘要

就能源和成本而言,为实时工业过程选择合适的协作机器人(cobot)是有效实施机器人技术的障碍之一。由于制造商提供的协作机器人功能和能力日益复杂,针对特定应用的协作机器人选择过程变得更加复杂。本文提出了一种基于层次分析法(AHP)和逼近理想解排序法(TOPSIS)的混合多准则决策(MCDM)技术,用于为燃油滤清器装配操作选择协作机器人。产品设计方法、制造方法以及相关成本直接影响协作机器人的选择决策。通过层次分析法赋予预期准则权重,以便后续处理,从而能够以尽可能低的成本和能力选择最合适的机器人来完成所需任务。逼近理想解排序法根据准则的重要性对备选方案进行排序。通过一个柴油燃油滤清器装配工艺案例来验证所提出的协作机器人选择技术。针对12款推荐的协作机器人建立了专家知识库,并使用所提出的混合多准则决策技术选出了最佳的协作机器人。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f5f1/10882119/6141336f92cb/gr1.jpg

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