The Selection of Industry 4.0 Technologies Through Aczel-Alsina Information Based on Circular Bipolar Complex Fuzzy Uncertainty: An Operational Perspective

This manuscript aims to find the most key steps and considerations for selecting industry 4.0 technology. For this, we evaluate the technique of circular bipolar complex fuzzy (CBCF) information. Further, we describe the algebraic operational laws and Aczel-Alsina operational laws based on CBCF values. Moreover, we present the technique of the CBCF Aczel-Alsina weighted averaging (CBCFAAWA), CBCF Aczel-Alsina ordered weighted averaging (CBCFAAOWA), CBCF Aczel-Alsina hybrid averaging (CBCFAAHA), CBCF Aczel-Alsina weighted geometric (CBCFAAWG), CBCF Aczel-Alsina ordered weighted geometric (CBCFAAOWG), and CBCF Aczel-Alsina hybrid geometric (CBCFAAHG) operators. Some suitable properties for the above operators are discussed in detail. Additionally, the relation between industry 4.0 and circular bipolar complex fuzzy set theory lies in their complementary roles in coping with the ambiguities and vagueness inherent in modern manufacturing processes, such as decision-making techniques, control systems, predictive maintenance, supply chain management, and conflict analysis. Therefore, to evaluate the best one among the above four, we illustrate the technique of multi-attribute decision-making (MADM) procedure based on initiated operators to show the supremacy and validity of the proposed theory. Finally, we compare our ranking theory with some prevailing ranking results to enhance the stability and worth of the initiated operators.