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Appraisal of smart factory design for advance manufacturing plants based on transition strategies by using an integrated fuzzy decision-making methodology

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TAYLOR & FRANCIS LTD

DOI

10.1080/0951192x.2023.2177735

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One of the most critical points of the Industry 4.0 (I4.0) era is the smart factories (SFs) that emerged with the digital evolution of production facilities, that aims to achieve competitiveness, sustainability, customer focus, flexibility, and digitalization of processes in production. It is necessary to determine strategic priorities and determine road maps using effective decision-making systems for a successful smart factory design (SFD) and transformation process. Likewise, one of the most significant obstacles to achieving a sustainable transformation is to systematically identify the requirements, challenges, and stages of this transformation. This study aims to create a framework for SFD and a road map with the strategic priorities by considering both opportunities and threats. For this aim, a multi-criteria decision-making methodology (MCDM) which consists of DEMATEL, ANP, and TOPSIS methods by considering human knowledge-based data that converted by using Pythagorean fuzzy sets (PFSs) has been suggested for the problem solution. The highest importance criteria are determined as 'Management', 'Operation', 'Structure', 'Organization' for the main criteria and 'Finance-Budget', 'Labor Force', 'Production Operations', 'Architectural Layer', 'Production Technologies', 'Smart Machine', and 'Integration' for sub-criteria among the identified 7 main criteria and 30 sub-criteria, respectively. As a result, it has been determined that the strategy 'Design and Automation of Processes' is determined as the most appropriate strategy for the transition process of the SF among the 8 main strategies and 36 action plans. Finally, a sensitivity analysis is also performed, and the current situation and different scenarios are compared and discussed.

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING

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0951-192X

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