Guillermo García Rodríguez

Prof. Guillermo García Rodríguez

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Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 April 2026 in Applied Sciences
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Journal Article
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LVLuis Villanueva
Luis Villanueva
RTRosa Jazmín Trasviña-Osorio
Rosa Jazmín Trasviña-Osorio
Juan De anda suárezJuan De anda suárez
Juan De anda suárez
José Luis López-RamírezJosé Luis López-Ramírez
José Luis López-Ramírez
Guillermo García RodríguezGuillermo García Rodríguez
Guillermo García Rodríguez
Jose Ruiz TamayoJose Ruiz Tamayo
Jose Ruiz Tamayo
Quality evaluation in production systems represents a significant challenge in the manufacturing industry, particularly in environments where expert judgment plays a key role in managing the inherent uncertainty of the production system. This study proposes a fuzzy multicriteria decision-making control chart, termed Fuzzy Decision-Making Control Chart based on AHP-Extent and Triangular Fuzzy Numbers (FDMCC-AHPE). The method integrates expert knowledge through triangular fuzzy numbers and a Fuzzy Analytic Hierarchy Process supported by Extent Analysis, to define fuzzy decision intervals for quality assessment and subsequently perform a structured analysis to classify the product within a control chart framework. In this framework, expert judgments expressed through linguistic evaluations are systematically translated into triangular fuzzy numbers and processed using FAHP–Extent Analysis, allowing the aggregation of subjective assessments within a structured mathematical decision model. The proposed method was validated in a tannery company, specifically in the retanning process. The industrial case study considers both qualitative criteria, such as surface defects and color uniformity, and quantitative process variables that include bath pH, treatment duration, and processing temperature. The results were compared with an empirical expert-based evaluation and a structured expert assessment supported by a multicriteria decision-making method. The findings demonstrate that the FDMCC-AHPE exhibits greater sensitivity in discriminating between quality states under uncertain evaluation conditions, particularly when samples involve complex evaluation conditions.