How does maintenance influence/or is influenced by short-term scheduling decisions?

This report seeks to understand the influence of maintenance in short-term scheduling decisions, particularly in digitalizing operations in e-learning platforms. Higher education institutions heavily rely on online learning. The competence and efficacy of the e-Learning platform, especially in the short-term scheduling of tasks or activities related to the scheduling of classes, exams, reporting, feedback, and assessments, are significant elements influencing the effectiveness of e-Learning. The maintenance difficulty is a substantial component of short-term scheduling in online education. A critical factor of short-term scheduling in online learning is the maintenance challenge illustrated in a study by Olanrewaju et al., 2020), which includes issues relating to; There is a need for a comprehensive and systematic framework for maintenance management that guides decision-making in online learning. A convoluted and disjointed maintenance issue reporting system that causes delays and higher expenses. Since the maintenance department is understaffed and needs properly qualified workers, contractors are being outsourced. Delays and backlogs in complaint resolution due to unavailability of maintenance department is closed on weekends. eLearning infrastructure is crutial and can presents several maintenance challenges, as shown in papers by Nawaz & khan, 2012 and Khedr et al., 2021. These include issues pertaining to; Frequent updates and modifications are required in response to rapid technological improvements. The initial investment and continuing costs for maintaining and enhancing infrastructure are costly and can cause budget constraints. The security of the eLearning systems requires constant attention and resources. Addressing hacking, data breaches, and other cyber threats requires continuous dedication. The co-dependency between the users and the technical department due to a lack of skills and expertise. The monitoring of load distribution to prevent bottlenecks and guarantee seamless operation when they receive less technical assistance. Data backup and recovery mechanisms are required to preserve data availability and integrity in the case of malfunctions. Elghibari et al., 2015 and Papathanasiou et al., 2012 focused on digitalizing eLearning processes, such as intelligent eLearning systems and algorithms, to address maintenance issues within eLearning platforms. Elghibari, concluded that automated updating mechanisms ensured consistent and high-quality course materials by detecting anomalies in current and obsolete information. Subsequently, Papathanasiou claimed that utilizing algorithms for e-maintenance systems improves eLearning systems’ efficiency, accuracy, and responsiveness. These improvements included preventative and condition-based maintenance, real-time data access, and integrated systems to streamline maintenance processes. “How can short-term scheduling decisions be influenced by the digitalization of maintenance systems within the Stadio e-learning platforms?”