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Background: Minimal hepatic encephalopathy (MHE) is the mildest form of hepatic encephalopathy. One of the neuropsychological tests that detects MHE is the Stroop test (via EncephalApp). The aim was to evaluate the Stroop test for the screening and diagnosis of MHE. Methods: This prospective case–control study was performed at the Clinic for Gastroenterology and Hepatology, University Clinical Center of Serbia, and included patients with cirrhosis and MHE and healthy controls. In all patients, the presence of MHE was confirmed using the animal naming test. The Stroop test was performed on each participant, and the results were compared between the two groups. The test has two components, the “OFF” and “ON” states. Results: A total of 111 participants were included. The median OFF time did not differ between the two groups, 106.3 and 91.4, p > 0.05. However, in patients with MHE, the median values of ON time and total time were significantly higher, with 122.3 vs. 105.3 and 228.0 vs. 195.6, respectively, p < 0.05. Statistical significance between patients and controls in examined parameters was detected in younger participants and the group with higher educational levels. Conclusions: The Stroop test displayed limited sensitivity in Serbian patients. Age and education affect time measurements and test performance.

Purpose: The ever-evolving market dynamics and the trend toward increased product individualization demand a high degree of adaptability in production management. This calls for novel approaches, such as Industry 4.0 (I4.0), which integrates the Quality 4.0 (Q4.0) model as well. Methodology/Approach: I4.0 builds upon the foundation of digital manufacturing and entails three key dimensions: (i) The employment of advanced digital technologies to enable digital production, (ii) The development of smart products, which incorporate novel production methods and innovative features, and, (iii) The adoption of an intelligent supply chain, designed to facilitate the procurement of raw materials and the delivery of finished goods. In our research studies, we focus specifically on the first and third approaches. Findings: A bilateral flow of information in collaborative manufacturing is facilitated through digital platforms that span the entirety of the production process, from the inception of cutting-edge product designs to the final delivery to end-customers, integrating quality management (QM) as well. Research Limitation/Implication: The current study outlines a QM model developed for a digital factory in Serbia, utilizing the Q4.0 model, with particular emphasis on the workshop section, integrated within the Enterprise Resource Planning/Manufacturing Execution Systems module. Originality/Value of paper: The manuscript serves as a notable illustration of best practices for digital manufacturing, and the implementation of a digital QM model within the metalworking industry.