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    Decisioning-based approach for optimising control engineering tools using digital twin capabilities and other cyber-physical metaverse manufacturing system components
    (IEEE, 2024) Mourad, Nahia; Alsattar, Hassan A.; Qahtan, Sarah; Zaidan, Aws Alaa; Deveci, Muhammet; Sangaiah, Arun Kumar; Pedrycz, Witold
    The optimisation of control engineering tools based on digital twin capabilities and other cyber-physical metaverse manufacturing system (CPMMS) components are crucial for the successful performance. This study proposes a model for optimising control engineering tools using digital twin capabilities and other CPMMS components to solve the open issues. The main contributions and novelty aspects of the methodological process are outlined as follows: Formulated and developed is a decision matrix based on a utility procedure for 10 control engineering tools with digital twin capabilities and other three CPMMS components (Programmable-Logic-Controller and Human-Machine-Interface, Internet of Things connectivity and cybersecurity features). This matrix accounts for the uncertainty associated with tool assessment and transformation evaluation issue; formulated and develop an integrating fuzzy weighted with zero-inconsistency-interval-valued spherical fuzzy rough sets (IvSFRS-FWZIC) and combined compromise solution (CoCoSo) methods. The IvSFRS-FWZIC method is utilised to assign importance degrees to the digital twin capabilities and other CPMMS components. The applicability and robustness of the proposed approach are validated and evaluated through conducting sensitivity, correlation, and comparative analyses. The proposed approach can assist managers in analysing and selecting the most suitable tool for developing CPMMS.
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    Evaluation of industry 4.0 adoption strategies in small and medium enterprises: A Circular-Fermatean fuzzy decision-making approach
    (Elsevier ltd, 2025) Abu-Lail, Dareen; Mourad, Nahia; Qahtan, Sarah; Zaidan, A.A.; Alsattar, Hassan A.; Zaidan, B.B.; Pamucar, Dragan; Deveci, Muhammet; Pedrycz, Witold; Delen, Dursun
    The evaluation of Industry 4.0 (I4.0) technology adoption strategies (I4.0AS) in Small and Medium Enterprises (SMEs) from I4.0 technologies and technology-organization-environment (TOE) ecosystem perspectives poses a significant challenge due to three primary concerns: the importance of criteria, data variability for each individual I4.0AS, and uncertainty in expert opinions. This complexity arises from the consideration of diverse criteria groups for I4.0 deployment in the SMEs sector with a focus on the TOE context, which is linked to a second criteria group characterized by uncertain evaluative data. Although research in this area has increased, a comprehensive assessment methodology tailored to the unique needs of SMEs remains elusive. Addressing this gap is crucial to provide SME decision-makers with detailed insights that enhance their strategic choices. In our study, we introduce a holistic evaluation of I4.0ASs, emphasizing the performance dynamics within the TOE framework. Central to our assessment methodology is the integration of advanced Circular-Fermatean Fuzzy sets (C-FFS), designed to capture uncertain evaluative data. This three-phased methodology formulates the Circular-Fermatean Fuzzy Sets-Fuzzy-weighted zero-inconsistency (C-FFS–FWZIC) approach and evaluates I4.0ASs from both the I4.0 technology and TOE-ecosystem perspectives. Through a rigorous examination of 37 distinct I4.0ASs based on 30 I4.0 technology perspective criteria and 114 TOE-ecosystem perspective criteria, our study illuminates their efficacy across these dual perspectives. The results indicate that I4.0AS23 ranked first according to the I4.0 technologies perspective but 26th according to the TOE-ecosystem perspective, while I4.0AS1 ranked first according to the TOE-ecosystem perspective and 15th according to the I4.0 technologies perspective. I4.0AS25 yielded consistent results, scoring 6th place in both perspectives. Additionally, the resilience and versatility of our methodology are validated through an in-depth sensitivity and comparative analysis, reinforcing its potential as a valuable tool for future industry applications.
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    Neutrosophic bipolar fuzzy decision-based approach for developing sustainable circular business model innovation tools
    (Pergamon-Elsevier Science Ltd, 2024) Zaidan, Aws Alaa; Deveci, Muhammet; Alsattar, Hassan A.; Qahtan, Sarah; Shang, Wen-Long; Delen, Dursun; Mourad, Nahia
    The circular economy (CE) has been identified as a possible catalyst for sustainable development by business, academics, and policymakers. To aid company developers in creating and improving business models that incorporate circularity, a variety of tools for circular business model innovation (CBMI) have been proposed. Nevertheless, the existing tools failed to consider sustainability or CE in their advancements. Currently, there is no research that has presented a complete dataset including all potential tools that may be created based on the CE' sustainability performance attributes. Moreover, there has been a dearth of research conducted to assess and model these tools in order to determine the most efficient ones, which has resulted in a research gap. This paper constructs a decision matrix of CBMI tools by intersecting 100 CBMI tools with 10 CE' sustainability performance attributes. The modeling of CBMI tools falls under Multiple Attribute Decision Making (MADM) due to the presence of many attributes, varying importance levels of these attributes, and the and variation in data. Thus, the fuzzy weighted with zero inconsistency (FWZIC) method is reformulated under neutrosophic bipolar fuzzy sets (NBFS) to determine the weight of CE's sustainability performance attributes. The matrix that has been constructed and the resulting weight values are fed into the CODAS method in order to model CBMI tools and identify the most sustainable tool. The results indicate that the NBFS-FWZIC method gave a weight value of 0.1031 to A7, which is the greatest weight value. On the other hand, A3 had the lowest weight value of 0.0944. The CODAS method modeled the 100 CBMI tools, with Tool39 being identified as the most sustainable tool and Tool26 as the least sustainable tool. The robustness and durability of the proposed method are evaluated using a sensitivity analysis, Spearman's rank correlation test, and comparison analysis.