Assessing workforce productivity in industrial manufacturing is a complex task influenced by fluctuating workloads, operational uncertainties, and human performance variability. Traditional evaluation methods often fail to capture these dynamics. This study proposes a Circular Intuitionistic Fuzzy Model (C-IFPr) for workforce productivity assessment, extending intuitionistic fuzzy set theory by incorporating circular intuitionistic fuzzy triples (C-IFTs) to enhance the representation of cyclic patterns and uncertainty in performance evaluation. The model defines key productivity criteria such as task completion efficiency, adaptability to shift variations, machine-handling proficiency, and error rates. A real-world case study illustrates the model’s applicability, demonstrating how C-IFPr supports workforce planning and strategic decision-making.