A mobile application approach for improving data consolidation in industry

Abstract

Reliable data collection is crucial in South Africa's industrial sector due to the escalating operational costs. Effective data utilisation allows companies to optimise their systems, enhance resource efficiency, and expedite decision-making processes. Leveraging data-driven insights empowers companies to identify opportunities for improved resource allocation, leading to cost savings and enhanced performance. To address the need for robust data collection in challenging environments, a curated application was developed and integrated with an existing online system. This integration ensures real-time data synchronisation and efficient access, facilitating seamless data flow and system performance. Through analysing existing data collection applications, deficiencies were identified, and shortcomings were addressed, particularly in the storage and processing methods employed. The developed cross-platform application utilises onboard components across different devices and platforms. The artefact seamlessly integrates with existing systems to store data on a server. The application dynamically generates collection pages based on active generation, allowing for diverse data collection configurations without altering the application structure. Moreover, it generates adaptable storage structures for various data layouts, ensuring flexibility and expandability. The system was then assessed using a case study conducted at South African mines, specifically focusing on collecting diesel log readings from mining equipment and vehicles. The system was configured to meet the specific needs of each mine, including the functionality to scan barcodes attached to each asset. The system successfully collected the data and saved user, location and date information ensuring traceability. The collected data was utilised for various purposes, including diesel rebate processing. The diesel rebate claims, created using the data collected with the system, were accepted by the South African Revenue Service (SARS). In addition, the inclusion of pictures and user information in the logs further enhanced the reliability of the data. The diesel rebates resulted in substantial cost savings for the mines, totalling an average of R1.5 million per month (to date). This dissertation addresses the critical requirement for reliable data collection in South Africa's industrial sector. The developed cross-platform application demonstrates its efficacy in traceable data collection, accommodating diverse configurations and seamless integration with existing systems. The case study at South African mines showcases the system's ability to efficiently collect and process data, resulting in significant cost savings through successful diesel rebate claims. Overall, this research contributes to advancing data collection methods, benefiting industrial operations in South Africa.