Faisal Mohammed Alotaibi

American scientific publishing group

Industry 4.0 emphasizes the importance of sustainable manufacturing practices. Accordingly, engineering education has increasingly incorporated virtual reality (VR) technology. This study aims to identify the potential usage of VR as an educational tool to enhance manufacturing sustainability within Industry 4.0. The methodology used an experimental design, a structured survey, and a multilevel modeling analysis to measure the effects of VR interventions. The findings show that the learning outcomes of VR treatments and post-test scores are significantly impacted by two crucial factors: age (β = 0.35, p < 0.01) and VR experience (r = 0.42, p < 0.01). Furthermore, sustainability attitudes moderately affected academic development (β = 0.25, p < 0.05). According to descriptive statistics, virtual reality treatment resulted in a 25% improvement in the post-test results. According to MLM, the combined effects of virtual reality experience and sustainability attitudes on learning outcomes account for 45% of the total variation (R² = 0.45, p < 0.01). The study’s findings highlight the importance of VR in enhancing educational outcomes and fostering sustainable production practices within Industry 4.0. This research is unique in its simultaneous investigation of VR technology, engineering education, and sustainability, providing valuable insights into how VR can contribute to preparing engineers for the challenges of Industry 4.0 and advancing sustainable initiatives in the manufacturing field.

The Industrial Internet of Things (IIoT) ecosystem faces increased risks and vulnerabilities due to adopting Industry 4.0 standards. Integrating data from various places and converging several systems have heightened the need for robust security measures beyond fundamental connection encryption. However, it is difficult to provide adequate security due to the IIoT ecosystem’s distributed hardware and software. The most effective countermeasures must be suggested together with the crucial vulnerabilities, linked threats, and hazards in order to protect industrial equipment and ensure the secure functioning of IIoT systems. This paper presents a thorough analysis of events that target IIoT systems to alleviate such concerns. It also offers a comprehensive analysis of the responses that have been advanced in the most recent research. This article examines several kinds of attacks and the possible consequences to understand the security landscape in the IIoT area. Additionally, we aim to encourage the development of effective defenses that will lessen the hazards detected and secure the privacy, accessibility, and reliability of IIoT systems. It is important to note that we examine the issues and solutions related to IIoT security using the most recent findings from research and the literature on this subject. This study organizes and evaluates recent research to provide significant insight into the present security situation in IIoT systems. Ultimately, we provide outlines for future research and projects in this field.

This manuscript presents a comprehensive mathematical model for multi-objective optimization problem of the microgrid. The microgrid consists of houses and local plants, each seen as independent agents with their specific goals. We, also, propose a heuristic algorithm for optimizing the electricity cost by using the concept of load shifting and renewable power sharing among houses in the microgrid for a particular price. The proposed algorithm also minimizes the loss of energy by prioritizing power exchange between houses and minimize discomfort factor. The findings show that houses and micro plants working in microgrid setting can make significant savings. The results also illustrate that the algorithm guarantees that no agent will lose in the microgrid.