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    Application of MADM methods in Industry 4.0: A literature review
    (Pergamon-Elsevier Science Ltd, 2023) Zayat, Wael; Kilic, Huseyin Selcuk; Yalcin, Ahmet Selcuk; Zaim, Selim; Delen, Dursun
    Industry 4.0 has received inordinate attention from the business as well as research communities. Along with the development of Industry 4.0 applications and the diversity of potential alternatives, Multi-Attribute Decision Making (MADM) techniques have been employed by researchers as systematic approaches to support the decision-making processes. However, as the adoption of Industry 4.0 technologies requires considerable capital, and as it is relatively difficult to identify the suitable MADM method for the decision-making process in certain conditions, it becomes necessary to determine which components of Industry 4.0 are most commonly in demand of MADM applications of decision making, and which MADM techniques are mostly preferred by researchers and businesses for varied directions of Industry 4.0. Therefore, this study aims to provide a comprehensive review of MADM methods and their applications for different components of Industry 4.0. A methodology, including a review framework, is provided for the related analyses. The proposed framework includes analyses concerning methods, subtopics, and bibliometry along with the related exploratory tables and figures. Finally, the trends and research gaps are clearly stated to shed light on the further research areas taking into consideration different challenges that can be encountered by researchers, along with a set of propositions to potentially overcome them.
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    A Framework for Mitigating Excessive Transportation in the Context of Manufacturing Localization
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Eryarsoy, Enes; Nalcioglu, Hakki; Kilic, Huseyin Selcuk; Yalcin, Ahmet Selcuk; Zaim, Selim; Delen, Dursun
    While the zeitgeist of today prescribes localization as a key to eliminate the excessive transportation for manufacturing firms, firm-level practical and workable guidelines that go beyond maxims are scant. Laden with analytical methods, this article offers a phronetic, customizable framework based on lean six sigma (LSS). The framework mimics Define-Measure-Analyze-Improve-Control process. The early phases of the framework, ex-ante, prescribe the use of a variety of tools and techniques from LSS and employ a fuzzy analytic hierarchy process to extract the vital few root causes that may impede localization. The latter phases suggest the use of the design of experiments to evaluate the root causes, ex-post. The article outlines a clear and established procedure and demonstrates each analytical phase using evidence from a two-year real-world application in the steel industry.