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This study aims to address challenges related to long lead time within a hazelnut company, primarily attributed to product quality issues. The purpose is to propose an integrated lean-based methodology incorporating a continuous improvement cycle, drawing on Lean Six Sigma (LSS) and Industry 4.0 applications.

The research adopts a systematic approach, commencing with a current state analysis using VSM and fishbone analysis to identify underlying problems causing long lead time. A Pareto analysis categorizes these problems, distinguishing between supplier-related issues and deficiencies in lean applications. Lean tools are initially implemented, followed by a future state VSM. Supplier-related issues are then addressed, employing root cause analyses and Industry 4.0-based countermeasures, including a proposed supplier selection model.

The study reveals that, despite initial lean implementations, lead times remain high. Addressing supplier-related issues, particularly through the proposed supplier selection model, significantly reduces the number of suppliers and contributes to lead time reduction. Industry 4.0-based countermeasures ensure traceability and strengthen supplier relationships.

This research introduces a comprehensive LSS methodology, practically demonstrating the application of various tools and providing managerial insights for practitioners and policymakers. The study contributes theoretically by addressing challenges comprehensively, practically by showcasing tool applications and managerially by offering guidance for system performance enhancement.

Rice is the main cereal in Senegal. Despite efforts to improve the sector, consumers still prefer imported rice. Only one previous study conducted by the authors analyzed these preferences using a sensory analysis approach (Mané et al., 2021). This initial study showed that local rice can compete with imported rice if processing is improved. Based on these results, this study aims to identify the physicochemical parameters responsible for the sensory quality identified in Senegalese consumers.

In this context, the physicochemical and cooking properties of 12 rice samples were analyzed and the correlations between these physicochemical and sensory properties were studied.

The results showed that imported rice had a higher 1000-kernel weight, grain length and transparency values, whereas local rice had higher water uptake, swelling ratios, gelatinization temperature and iron and magnesium contents. Correlations have shown that positive descriptors such as “beautiful,” “white color,” “good taste,” “fragrant,” “fine grains,” “typical rice odor,” well-cooked” and “scattered” were correlated with varietal and technological criteria such as high 1000-grain weight, grain length, whiteness, transparency and absence of impurities in rice. In contrast, negative sensory descriptors such as “pasty” and “sticky texture” were associated with water uptake ratio, gelatinization temperature, rice breakage and cooking time.

These results show how to improve the quality of new rice varieties in the country based on the physicochemical parameters associated with the positive sensory properties cited above by consumers.