E ISSN: 2583-049X
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International Journal of Advanced Multidisciplinary Research and Studies

Volume 5, Issue 2, 2025

Design and Develop Mining Maintenance Mobile Application



Author(s): Peter Chewe, Eng Mwashi Matela

DOI: https://doi.org/10.62225/2583049X.2025.5.2.4037

Abstract:

The design and development of a mobile application system especially suited for mining industry maintenance management. The system was created to solve typical issues in mining operations, like equipment failures, ineffective maintenance plans, and poor communication between operators and maintenance crews.

This app is designed to streamline the assignment of maintenance tasks within mining operations, enhancing efficiency and communication.

Administrators can easily allocate jobs to employees based on skill sets, availability, and location, ensuring optimal resource utilization. The app features real-time notifications, progress tracking, and comprehensive reporting tools to monitor job status and employee performance. By integrating these functionalities, the application aims to minimize downtime, improve safety standards, and increase overall productivity in the mining sector. Chatti, M. A., & Ziegler, J. (2017) [7]

The proposed mining maintenance mobile application revolutionizes the traditional maintenance management system by enabling seamless job allocation and tracking for administrative staff.

Features including digital work orders, fault diagnostics, predictive and preventative maintenance alerts, and real-time monitoring are all integrated into the mobile application. Through intuitive user interfaces, it facilitates the easy tracking and administration of mobile machinery and equipment while offering extensive information on equipment performance, maintenance history, and downtime. To accommodate distant mining locations with spotty internet, the application also offers offline functionality. Elsayed, T., & Ramadan, H. (2020) [11]

The application's efficacy in improving asset reliability and streamlining maintenance work scheduling has been confirmed through case studies and field testing. The study ends by providing insights into the application's potential future developments, such as machine learning-based improvements for predictive maintenance and more features for extensive mining operations. Bello, O., Zeadally, S., & Badra, M. (2017) [5]


Keywords: Mobile Application, Equipment, Zambia

Pages: 1659-1668

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