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100 I-CONNECT007 MAGAZINE I JANUARY 2026 Traceability • Quality parameters monitoring: Quality con- trol is a key focus for manufacturing operations, maintaining detailed records of production parameters to trace quality issues to specific production situations. Monitoring parameters such as process line, temperature, current, and voltage, and part specifications, enables manu- facturers to identify the root causes of defects and take corrective actions to maintain product quality standards. There may also be qualitative variables that contribute to defects. • Alarms management: Alarms play a critical role in traceability and quality, highlighting issues that require immediate attention. By analyzing alarm data, manufacturers can implement pre- ventive measures to avoid recurring problems and maintain consistent product quality. Effec- tive alarm management ensures immediate responses to potential issues, minimizing down- time and disruption to production operations. Energy Management Predictive maintenance electrical (PME) energy consumption is a challenge in manufacturing. Energy management systems monitor energy usage through various types of equipment and processes using sophisticated models to predict and optimize energy consumption, thereby con- tributing to overall operational efficiency and cost savings. By managing energy consumption effec- tively, manufacturers can reduce their environmen- tal impact and achieve sustainability goals. Remote Support Remote support capabilities enable manufacturers to monitor and manage equipment performance and facilitate quick diagnostics and interventions without onsite visits. It also minimizes downtime, reduces maintenance costs, and ensures contin- uous production operations. Secure communica- tion channels ensure effective and safe access to equipment, enhancing operational efficiency and maintenance processes. Predictive Maintenance Predictive maintenance is a highly valuable capa- bility of data-driven industrial digital solutions. It uses machine learning models to analyze his- torical and real-time data to predict when equip- ment is likely to fail. By performing maintenance just-in-time, manufacturers can avoid downtime losses and prevent unexpected failures, ultimately extending equipment life. Predictive maintenance Figure 3: Collecting and managing data from a modern factory can be complex with many sources, streams, and silos affecting understanding and compatibility. H A PPY ' S T EC H TA L K #4 6