Ports are essential nodes in global trade, linking maritime and land transport. As maritime logistics increasingly drive global supply chains, optimizing port operations has become vital for enhancing economic efficiency and environmental sustainability. This study presents a Mixed Integer Linear Programming (MILP) model to address inefficiencies in berth allocation and stevedoring processes at the Port of Leixões, Portugal. By integrating real operational data, the model reduces vessel waiting times by 47.56% (from 8.1 to 4.2 h) and operational delays by 37.39% (from 11.5 to 7.2 h). These optimizations also result in a 41.85% reduction in greenhouse gas emissions per ship, aligning with global emissions regulations and promoting sustainable port management. The model’s innovations include real-time data integration and a holistic resource allocation approach to mitigate congestion and inefficiencies. Key findings demonstrate the model’s potential to streamline operations and minimize environmental impacts. These advancements align economic efficiency with environmental sustainability, addressing global emissions regulations. However, the study acknowledges limitations, such as excluding unpredictable factors like weather conditions and equipment failures. Future research should explore dynamic variables, such as weather conditions and mechanical failures, and expand the model’s applicability to other seaports worldwide.

Purpose: This research investigates Portuguese manufacturing companies' Industry 4.0 (I4.0) maturity perception level and proposes an index to measure that aim.Design/methodology/approach: This study uses a survey method to gather the companies' perceptions of their I4.0 maturity level and applies subsequent exploratory factor analysis to propose a global I4.0 measurement index.Findings: The research results show that the most critical factors in evaluating the perception level of I4.0 Perception Maturity (IPM) are strategy, leadership, and customer experiences. The result for the Global Index was 53.50%. Hence, the global Index companies' perception of the level of maturity of I4.0 in Portugal is medium.Research limitations/implications: This study encompasses only Portuguese manufacturing organizations (50 valid responses). Moreover, the research is subject to the limitations of the survey methodology, such as possible respondent bias.Practical implications: The Portuguese I4.0 strategy mainly targets small and medium-sized enterprises through a bottom-up approach. Hence, companies need proper methodologies and tools for evaluating I4.0 adoption, identifying their present situation concerning I4.0 and where to focus on improving the process and achieving the intended benefits.Social implications: This research identifies the main perceived benefits and obstacles of adopting I4.0, suggesting avenues for its successful implementation by the Portuguese companies.Originality/value: This study provides a valuable tool for manufacturing companies to identify the factors that need to be improved to create significant growth in the I4.0 Perception Maturity (IPM) index. Therefore, it can support companies in establishing a roadmap for successful I4.0 adoption and improving their performance and competitive position accordingly.

The following work aims to show how a combination of continuous improvement (CI) and Lean tools can reduce waste and process variability along an air-conditioned pipe production line (PL), calculate its capacity, and improve its efficiency to achieve the expected productivity. A variability study focused on the PL’s balancing was conducted to identify and reduce possible bottlenecks, as well as to evaluate the line’s real capacity. Several layout improvements were made to upgrade the line’s operational conditions and reduce unnecessary movements from the workers. The Constant Work-In-Progress (CONWIP) methodology was also applied to ease the component’s production management in the preparation stage. Additional modifications were implemented to support production and to contribute to the increases in efficiency, quality, and safety on the line. The results revealed an increase in the line’s capacity, associated with an efficiency rise from 28.81% to 47.21% from February to June 2023. The overall equipment effectiveness (OEE) in the same period increased by 18%. This demonstrates that, by interactively applying a mix of tools and methodologies, it is possible to achieve better performance of production lines. This knowledge can help scholars and practitioners to apply the same set of tools to solve usual problems in cell and production lines with performance below expectations.