Flood susceptibility mapping is essential for urban planning and disaster risk management, especially in rapidly urbanizing areas exposed to extreme rainfall events. This study applies an integrated approach combining Geographic Information Systems (GIS), map algebra, and the Analytic Hierarchy Process (AHP) to assess flood-prone zones in Ananindeua, Pará, Brazil. Five geoenvironmental criteria—rainfall, land use and land cover (LULC), slope, soil type, and drainage density—were selected and weighted using AHP to generate a composite flood susceptibility index. The results identified rainfall and slope as the most influential criteria, with both contributing to over 184 km² of high-susceptibility area. Spatial patterns showed that flood-prone zones are concentrated in flat urban areas with high drainage density and extensive impermeable surfaces. CHIRPS rainfall data were validated using Pearson’s correlation (r = 0.83) and the Nash–Sutcliffe efficiency (NS = 0.97), confirming the reliability of the precipitation input. The final susceptibility map, categorized into low, medium, and high classes, was validated using flood events derived from Sentinel-1 SAR data (2019–2025), of which 97.2% occurred in medium- or high-susceptibility zones. These findings demonstrate the model’s strong predictive performance and highlight the role of unplanned urban expansion, land cover changes, and inadequate drainage in increasing flood risk. Although specific to Ananindeua, the proposed methodology can be adapted to other urban areas in Brazil, provided local conditions and data availability are considered.

The study has as purpose to identify, analyze, and validate challenge constructs of Industry 4.0, which can affect the promotion of sustainability within the industry. A systematic literature review was conducted to identify challenges to the promotion of Industry 4.0 sustainability. A set of seventy challenges were grouped into the following eight constructs: finances, technology, organizational, human resources, legislation, geopolitical and economic factors, and both internal and external factors. Subsequently, the same constructs were validated using a survey involving industry professionals. The data were analyzed using the Lawshe method. Five constructs within the eight constructs were considered relevant to industry sustainability according to the experts’ opinion. The validated set of constructs included: finance, technology, organizational, human resources, and internal factors. This study contributes to the literature in the field by addressing a research gap of constructs identification based on expert’s opinions that impact Industry 4.0 in promotion of sustainable development. This study delivers theoretical and practical implications. From a theoretical standpoint, it contributes to expanding knowledge by providing valuable insights into the adoption of Industry 4.0 and its specific challenges concerning the pursuit of more sustainable practices. These implications extend to diverse research areas given the multidisciplinary nature of Industry 4.0.

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems