Designing an IoT-Based EMIS using Linear Regression and CUSUM for Real-Time Anomaly Detection in Pharmaceutical Industry
DOI:
https://doi.org/10.22441/0.22441/10.22441/pasti.2025.v19i3.011Keywords:
Energy Management Information System (EMIS), Digital Transformation, IoT, CUSUM, Energy Efficiency, SDGsAbstract
The pharmaceutical industry is a high energy-intensity sector requiring strict operational stability. However, many companies still rely on manual energy monitoring methods, leading to information latency. A case study at a multinational pharmaceutical company in Indonesia revealed a baseload inefficiency of 14.3 kW during non-operational hours, which remained undetected due to an ad-hoc energy management system. This study aims to design an IoT-based Energy Management Information System (EMIS) architecture to transform the energy management business process from reactive to proactive-predictive. The study utilizes secondary data from the 2025 Energy Audit Report. The system design integrates a linear regression model (R²=0.80) for Energy Performance Indicators (EnPI) determination and the Cumulative Sum (CUSUM) algorithm for real-time anomaly detection. Investment feasibility is evaluated using techno-economic analysis. The implementation of EMIS requires an investment of IDR 225,000,000 with potential annual energy cost savings of IDR 44,172,687. Although the Simple Payback Period (SPP) is 5.1 years, the project is considered feasible due to its strategic value in data transparency, operational risk mitigation, and ISO 50001 compliance. Furthermore, this digital transformation supports the achievement of Sustainable Development Goals (SDG 7, 9, and 12) by promoting energy efficiency and responsible industrial consumption. Digitizing energy systems is not merely a tool replacement but a strategic transformation that turns energy data into critical business decision assets.
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Abidin, A. Z., et al. (2025). Leveraging IoT, digital twin and machine learning for smart energy audit in office building: A systematic literature review and recommendation. e-Prime - Advances in Electrical Engineering, Electronics and Energy, 100124. https://doi.org/10.1016/j.prime.2025.101124
Abujiya, M. R., Riaz, M., & Lee, M. H. (2013). Increasing the sensitivity of cumulative sum charts for location. Quality and Reliability Engineering International, 29(6), 869-881. https://doi.org/10.1002/qre.1661
Beck, A., et al. (2025). Towards fossil-free energy supply: Cost-effective decarbonization measures in pharmaceutical energy systems. Applied Thermal Engineering, 236, 128213. https://doi.org/10.1016/j.applthermaleng.2025.128213
Cesarotti, V., & Spada, C. (2016). Investigating the relationship between energy consumption and overall equipment effectiveness for improving manufacturing systems. International Journal of Productivity and Quality Management, 17(3), 336-352. https://doi.org/10.1504/IJPQM.2016.076711
Chen, Y., et al. (2022). Optimization of key energy and performance metrics for drug product manufacturing. International Journal of Pharmaceutics, 618, 122487. https://doi.org/10.1016/j.ijpharm.2022.122487
Gao, Z., et al. (2019). Analysis of energy-related CO2 emissions in China's pharmaceutical industry and its driving forces. Journal of Cleaner Production, 223, 679-690. https://doi.org/10.1016/j.jclepro.2019.03.092
Garrido-Zafra, J., et al. (2022). IoT Cloud-Based Power Quality Extended Functionality for Grid-Interactive Appliance Controllers. IEEE Transactions on Industry Applications, 58(4), 1-10. https://doi.org/10.1109/TIA.2022.3160410
Jagtap, S., et al. (2021). Real-time data collection to improve energy efficiency: A case study of food manufacturer. Journal of Food Process Engineering, 44(2), e13600. https://doi.org/10.1111/jfpp.14338
Jeevitha, D. (2023). Energy Management in Industry 4.0 Using AI. In Artificial Intelligence and Industry 4.0 (pp. 1-20). CRC Press. https://doi.org/10.1201/9781003432319-20
Kementerian Energi dan Sumber Daya Mineral Republik Indonesia. (2025, 18 September). Audit energi ungkap potensi penghematan puluhan juta kilo watt hour di industri. Direktorat Jenderal EBTKE. https://ebtke.esdm.go.id/artikel/berita/audit-energi-ungkap-potensi-penghematan-puluhan-juta-kilo-watt-hour-di-industri.
Mahandari, C. P., et al. (2025). Energy Baseline for Measurement and Verification on Energy Audit for an Oil and Gas Industry. Lecture Notes in Electrical Engineering, 1120. https://doi.org/10.1007/978-981-97-8197-3_49
Maitra, S., et al. (2025). Real-Time Anomaly Detection in Smart Energy Systems Using Statistical and Adaptive Learning Technique. Smart Innovation, Systems and Technologies. https://doi.org/10.1007/978-981-96-9191-3_28
Naji, K. K., et al. (2024). Unveiling Digital Transformation: Analyzing Building Facility Management’s Preparedness for Transformation Using Structural Equation Modeling. Buildings, 14(9), 2794. https://doi.org/10.3390/buildings14092794
Pelser, W. A., et al. (2018). Results and prospects of applying an ISO 50001 based reporting system on a cement plant. Journal of Cleaner Production, 198, 642-653. https://doi.org/10.1016/j.jclepro.2018.07.071
Pokane, S. S., & Masota, L. (2023). Architecture Approach to Manage Electricity Utility in a Smart City. 2023 IEEE European Technology and Engineering Management Summit (E-TEMS), 1-6. https://doi.org/10.1109/E-TEMS57541.2023.10424593
Prudenzi, A., et al. (2019). Smart distributed energy monitoring for industrial applications. 2019 IEEE International Workshop on Metrology for Industry 4.0 and IoT, 218-223. https://doi.org/10.1109/METROI4.2019.8792861
Reichardt, A. (2023). The use of the Internet of Things to increase energy efficiency in manufacturing industries. International Journal of Energy Sector Management. https://doi.org/10.1108/IJESM-12-2023-0017
Tesch da Silva, F., et al. (2020). Looking at energy through the lens of Industry 4.0: A systematic literature review of concerns and challenges. Computers & Industrial Engineering, 143, 106426. https://doi.org/10.1016/j.cie.2020.106426
Vetrivel, S. C. (2024). Smart factories and energy efficiency in industry 4.0. In Industry 4.0 and Climate Change (pp. 55-78). Wiley. https://doi.org/10.1002/9781394197798.ch4
Zsebik, A. (2018). ISO 50001—Energy Planning and Monitoring Tools and Examples. 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), 1205-1210. https://doi.org/10.1080/01998595.2018.12027901
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