Integration of Industrial Internet of Things (IIoT) with MIS: A Framework for Smart Factory Automation

Main Article Content

Rafiqul Islam, Shown Ahmed Faysal, Faisal Bin Shaikat, Asma Tabassum Happy, Nakul Bakchi, Md Moniruzzaman

Abstract

The Industrial Internet of Things (IIoT) integrated with Management Information Systems (MIS) is dramatically transforming factories by enabling real-time data analysis, automation, and enhanced productivity. This research aims to develop a holistic framework for integrating IIoT with MIS to achieve smart factory automation, focusing on operational efficiency, data-driven insights, and long-term global significant competitive advantage. This study was conducted by the Department of Management Information Systems at Lamar University, Texas, USA, from January 2023 to December 2023. A mixed-method approach was employed, encompassing system modeling, simulation experiments, and real-time sensor data analyses. Statistical tools measured efficiency gains, data accuracy, and integration viability across multiple pilot manufacturing sites and rigorous stakeholder interviews to validate practical outcomes. Implementation yielded a 28% improvement in production throughput and a 22% reduction in downtime across test sites. Mean data accuracy for real-time monitoring reached 95.6% (SD ± 2.3), indicating reliable sensor integration. Analysis of variance revealed significant enhancements in predictive maintenance scheduling (p < 0.01), correlating to a 15% decrease in unplanned repairs. Furthermore, user adoption rates climbed by 36% (SD ± 4.1), underscoring the system’s usability. Inventory turnover ratios also improved by 18%, optimizing resource allocation. The resulting integrated framework demonstrated robust interoperability between IIoT devices and MIS modules, empowering decision-makers with timely insights, reduced operational latency, and scalable deployment across diverse manufacturing scenarios with minimal data loss events. Overall, integrating IIoT with MIS provides a scalable, data-centric foundation for smart factories, enabling substantial gains in efficiency, predictability, and responsiveness across evolving industrial ecosystems, thereby fostering sustainable innovation globally.

Article Details

Section
Articles