基于集成模糊决策方法的制造工厂智能工厂转型战略优先排序:土耳其案例

Esra Ilbahar, A. Karaşan, I. Kaya
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引用次数: 0

摘要

随着智能工厂这一工业4.0的重要元素越来越受欢迎,企业通过采用不同的转型策略,试图以不同的方式跟上这一概念。这种差异背后的原因可能是,随着企业规模和技术水平的不同,企业的需求也会发生变化,因此企业在这些转型战略上的优先级也会有所不同。智能工厂原则的适应是工业4.0转型的关键过程,应该在多标准环境中进行评估。因此,本文提出了一个决策制定(DM)程序来评估制造工厂的智能工厂转型策略。为了提高决策过程的敏感性和灵活性,必须考虑决策过程的不确定性。因此,本文提出的多准则决策(MCDM)方法由认知映射和TOPSIS方法组成,并在z - number模糊集的基础上进行了扩展,能够更有效地处理决策过程的可靠性。本文采用Z-Numbers模糊认知映射方法对影响转型过程的因素之间的依赖关系进行建模,并利用Z-Numbers模糊TOPSIS方法根据这些准则对备选转型策略进行评估。最后,研究表明,替代策略s3 -流程设计和自动化被确定为智能工厂转型的最佳策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prioritization of Smart Factory Transition Strategies for Manufacturing Plants with an Integrated Fuzzy Decision-Making Approach: The Case of Turkey
As the smart factory concept, a significant element in Industry 4.0, has become more popular, enterprises have tried to keep up with this concept in different ways by adopting different transition strategies. The reason behind this difference might be that enterprises' priorities on these transition strategies become different as their needs change according to their size and technology levels they have. Adaptation of smart factory principles is completely critical process to transition for Industry 4.0 and it should be evaluated in multi-criteria environment. Therefore, in this paper, a decision making (DM) procedure has been suggested to assess smart factory transition strategies for manufacturing plants. To improve the sensitivity and flexibility of the process, the uncertainties of decision making process should be considered. Therefore, in this paper, the proposed multi-criteria decision making (MCDM) methodology consists of cognitive mapping and TOPSIS methods and they are extended based on Z-Numbers fuzzy sets which are able to handle reliability of a DM process in a more effective manner. The proposed method, Z-Numbers fuzzy cognitive mapping, is adopted to model the dependencies among factors having an impact on this transition process whereas the other method, Z-Numbers fuzzy TOPSIS, is utilized to evaluate the alternative transition strategies according to these criteria. Finally, it has been revealed that the alternative strategy, S3-Design and Automation of Processes, is determined as the best strategy for the smart factory transition.
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