A Picture Fuzzy Decision-Making Framework for COBOT Selection in Digital Supply Chains

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Abstract

Driven by digitalization in supply chains, the use of Collaborative Robots (COBOTs) has become increasingly widespread in recent years. They significantly contribute to process effciency by working in place of, or in collaboration with, humans in a variety of operations, including welding, painting, assembly and disassembly, transportation, packaging, and palletizing. However, when uncertainty and different criteria are taken into account, decision support systems that compare practical robots based on their suitability for specific needs are inadequate. This study presents a comprehensive multi-criteria decision-making (MCDM) framework for prioritizing COBOTs with different features used in digital supply chain processes. Based on in-depth research in the literature and the opinions of experts working in companies that use relevant robots in the industry, the criteria to be evaluated when selecting COBOT types are identified. The importance of these criteria was determined using the Picture Fuzzy Step-wise Weight Assessment Ratio Analysis (PiF-SWARA) method, which effectively captures the uncertainty in experts’ decisionmaking processes. Subsequently, alternative COBOT types were ranked using the Picture Fuzzy Combinative Distance-Based Assessment (PiFCODAS) approach. This case study, which evaluates the PiF-SWARACODAS concept, reveals that according to expert assessments, cost is the most important criterion in COBOT selection, followed by process quality and space utilization. The findings about the selection of types emphasize that high-effciency articulated robots operating at high speeds under mass production conditions are the primary priority. These robots are followed by humanoid robots. The third most important are power and force-limiting robots. The fourth and fifth types of COBOTs are hand-guided and safety-monitored stop robots. Validation and sensitivity analyses confirmed the robustness of the results. Overall, the proposed framework not only clarifies the key priorities for manufacturing facilities but also provides a validated decision support tool to align digitalization strategies with the most appropriate COBOT investments.

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APA

Kesici, B. (2025). A Picture Fuzzy Decision-Making Framework for COBOT Selection in Digital Supply Chains. Revista Internacional de Metodos Numericos Para Calculo y Diseno En Ingenieria, 41(4). https://doi.org/10.23967/j.rimni.2025.10.72342

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