Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.

Three-dimensional (3D) bioprinting is a promising technological approach for various applications in the biomedical field. Natural polymers, which comprise the majority of 3D printable “bioinks”, have played a crucial role in various 3D bioprinting technologies during the layered 3D manufacturing processes in the last decade. However, the polymers must be customized for printing and effector function needs in cancer, dental care, oral medicine and biosensors, cardiovascular disease, and muscle restoration. This review provides an overview of 3D bio-printed natural polymers—commonly employed in various medical fields—and their recent development.

This paper presents a practical approach to empowering software entrepreneurship in Saudi Arabia through a unique course offered by the Software Engineering department at Prince Sultan University. The course, SE495 Emergent Topics in Software Engineering: Software Entrepreneurship, combines software engineering and entrepreneurship to equip students with the necessary skills to develop innovative software solutions that solve real-world problems. The course covers a range of topics, including platform development, market research, and pitching to investors, and features guest speakers from the industry. By the end of the course, students will have gained a deep understanding of the software development process and its intersection with entrepreneurship and will be able to develop a working prototype of a software solution that solves a real-world problem. The course’s practical approach ensures that students are well-prepared to navigate the complexities of the digital and software sectors and succeed in an ever-changing business landscape.

Climate change is an important factor that must be considered by designers of large infrastructure projects, with its effects anticipated throughout the infrastructure’s useful life. This paper discusses how engineers can address climate change adaptation in design holistically and sustainably. It offers a framework for adaptation in engineering design, focusing on risk evaluation over the entire life cycle. This approach avoids the extremes of inaction and designing for worst-case impacts that may not occur for several decades. The research reviews case studies and best practices from different parts of the world to demonstrate effective design solutions and adjustment measures that contribute to the sustainability and performance of infrastructure. The study highlights the need for interdisciplinary cooperation, sophisticated modeling approaches, and policy interventions for developing robust infrastructure systems.

The objective of this work was to analyze the effect of the use of ChatGPT in the teaching-learning process of scientific research in engineering. Artificial intelligence (AI) is a topic of great interest in higher education, as it combines hardware, software and programming languages to implement deep learning procedures. We focused on a specific course on scientific research in engineering, in which we measured the competencies, expressed in terms of the indicators, mastery, comprehension and synthesis capacity, in students who decided to use or not ChatGPT for the development and fulfillment of their activities. The data were processed through the statistical T-Student test and box-and-whisker plots were constructed. The results show that students’ reliance on ChatGPT limits their engagement in acquiring knowledge related to scientific research. This research presents evidence indicating that engineering science research students rely on ChatGPT to replace their academic work and consequently, they do not act dynamically in the teaching-learning process, assuming a static role.