Engineers have deployed a hierarchical smart energy monitoring system across more than fifteen manufacturing facilities, wiring roughly 15,000 field devices and nearly 30,000 operational data streams into a single centralized platform built on the ISA-95 enterprise-control integration standard. The study, published open access in Energy Informatics on 11 October 2026 by Levent Kılıç, describes how the architecture links field instrumentation, PLC and SCADA systems, manufacturing execution systems, and enterprise resource planning platforms into one unified energy monitoring environment.
The motivation behind the work lies in a persistent weakness of industrial energy management. Many organizations still rely on fragmented or static monitoring systems that fail to deliver actionable insight across organizational levels. Energy-related concerns differ sharply between operational staff, engineers, and executives: engineers focus on equipment performance, fault detection, and maintenance, while executives prioritize investment efficiency, policy standardization, and long-term sustainability. Existing systems rarely address these diverse needs in a unified framework, leading to inefficiencies, misaligned strategies, and missed optimization opportunities.
The deployed infrastructure was substantial in scale. The implementation incorporated 1,476 electrical analyzers, 23 power-quality analyzers, 214 compressed-air flowmeters, 126 gas correctors, 31 gas metering systems, and 73 water meters. Data acquisition ran through industrial communication networks connecting field devices, automation platforms, SCADA servers, historian databases, and enterprise information systems, using standards such as Modbus TCP, Ethernet/IP, Profinet, and OPC-UA. The communication architecture was deliberately designed to accommodate both legacy and modern automation environments, allowing facilities with different levels of digital maturity to participate in the same monitoring framework.
At the core of the design is the ISA-95 reference architecture, a widely accepted framework for integrating field devices, industrial control systems, manufacturing operations, and enterprise management systems. In this implementation, the lower layers represent the Operational Technology domain, where energy and process information are collected through sensors, meters, analyzers, and controllers. The upper layers represent the Information Technology domain, where that raw information is transformed into energy-performance indicators, management reports, benchmarking analyses, and strategic decision support. The result is a continuous information flow from physical assets up to executive management functions across five logical levels.
The framework also applies a hierarchical decomposition approach to energy analysis. An entire production facility is treated as a system; furnace operations, compressed-air networks, electrical distribution, and water systems are treated as subsystems; and individual equipment such as compressors, pumps, transformers, burners, or heat exchangers are analysed as sub-subsystems. A complementary four-zone energy zoning scheme traces energy from incoming resources such as electricity, natural gas, coal, water, and industrial gases, through generation and utility systems, into manufacturing processes and finally down to individual production lines. This structure supports both top-down performance evaluation and bottom-up identification of efficiency opportunities.
The quantitative heart of the study comes from datasets obtained from twenty-one glass manufacturing facilities, including flat-glass, container-glass, and glassware production plants. A Sankey-based energy-flow analysis revealed that natural gas is the dominant energy source, accounting for approximately 84 percent of total energy input, while electricity contributes approximately 16 percent. Melting operations dominate overall facility energy consumption at roughly 73 percent of total energy use, and within the melting stage, furnace systems alone consume approximately 58 percent of total facility energy. Process-related systems account for about 20 percent, compressed-air systems about 6 percent, and auxiliary systems about 1 percent, while energy losses represent approximately 15 percent of total energy use.
Consolidating historical project records and energy-performance analyses into a common dataset also allowed the researchers to quantify where energy-saving potential is concentrated. Furnace and waste-heat-recovery applications form the largest category, representing approximately 34.7 percent of the total identified energy-saving potential. Although only 21 projects fell into this category, they generated an estimated saving potential of 3,992 tonnes of oil equivalent per year, with an associated economic benefit exceeding 2.27 million US dollars annually. Fan, pump, and drive applications accounted for approximately 22.7 percent of identified savings and represented the largest number of implemented projects, while heating, cooling, and insulation projects contributed 21.6 percent and compressed-air improvements added 17.8 percent.
Beyond the numbers, the deployment changed how information moves through the organization. Previously isolated utility systems were consolidated within a unified monitoring platform, eliminating fragmented data structures and data gaps between operational and enterprise systems. Role-based dashboards served operators, engineers, maintenance teams, energy managers, plant management, and executives, enabling rapid identification of performance deviations and abnormal consumption patterns. Centralized reporting allowed energy managers to compare electricity consumption, reactive energy indicators, and power-quality metrics across geographically distributed plants using identical performance indicators, supporting cross-facility benchmarking and the dissemination of best practices. Emissions data, including oxygen concentration and nitrogen oxide levels from furnace systems, were integrated into the same reporting structure to support compliance monitoring and process-efficiency insight.
The author is careful about what the study does and does not demonstrate. Industrial validation was conducted primarily within glass manufacturing, so the findings may not generalize fully to other energy-intensive sectors such as cement, steel, chemicals, food processing, or automotive manufacturing without further validation. The study also focused on monitoring, integration, and decision-support capabilities rather than direct measurement of long-term energy savings from individual projects; corrective actions remained the responsibility of individual facilities, so the work does not establish a direct causal relationship between system deployment and achieved savings. Interoperability challenges with legacy equipment required additional engineering effort, and the effectiveness of such systems ultimately depends on organizational factors including user engagement, management support, and decision-making practices that were outside the scope of the evaluation.
Future directions outlined in the paper include integrating advanced analytics and predictive models for anomaly detection, predictive maintenance, and energy-performance forecasting; developing digital-twin-based energy-management environments combining real-time monitoring with simulation and optimization; designing cybersecurity frameworks specifically for OT-IT integrated monitoring architectures; and conducting longitudinal studies of how monitoring-system utilization and organizational learning relate to long-term performance improvement. For now, the study offers a practical reference model: the contribution is not a new integration standard but a demonstrated, energy-focused implementation showing that large-scale, hierarchical monitoring can turn scattered industrial measurements into enterprise-wide energy intelligence.
Subject of Research: A hierarchical ISA-95-based industrial energy monitoring architecture integrating field devices, SCADA, MES, and ERP systems across manufacturing facilities
Article Title: Hierarchical multilevel smart energy monitoring system
Article References: Kılıç, L. (2026). Hierarchical multilevel smart energy monitoring system. Energy Informatics, 9(1), Article 78. https://doi.org/10.1186/s42162-026-00697-8
Image Credits: AI Generated
DOI: 10.1186/s42162-026-00697-8
Keywords: ISA-95, industrial energy management, OT-IT integration, SCADA, glass manufacturing, energy monitoring, Sankey diagram, benchmarking, waste heat recovery, Industry 4.0, energy efficiency, MES
News Source: Denise Maddox. (October 28, 2026). ISA-95-based energy monitoring platform spans 15,000 devices across glass plants. Scienmag.
