Integrating SCADA, Industrial IoT, and Edge AI to Modernize a Process Manufacturing Plant
1.Customer Profile
Industry: Specialty Chemicals & Process Manufacturing
Customer: Multi-Plant Process Manufacturer (Anonymous)
The organisation operated continuous process manufacturing facilities producing industrial chemicals for domestic and international customers. The plants relied on distributed control systems, SCADA, Industrial IoT sensors, laboratory testing, and manual operating procedures to maintain production stability. While individual systems generated large volumes of operational data, each represented only one aspect of the manufacturing process, making it difficult to understand how process conditions, equipment behaviour, and human activities influenced one another.
2.Operational Environment
Unlike discrete manufacturing, process manufacturing depends on maintaining stable operating conditions over extended production cycles. Product consistency is influenced by equipment performance, environmental conditions, operator interventions, raw material characteristics, and process parameters occurring simultaneously.
Operators monitored control rooms through SCADA, engineers reviewed equipment trends, maintenance teams inspected assets, and supervisors relied on CCTV and shift reports. Each department possessed valuable operational knowledge, but that knowledge remained distributed across independent systems rather than forming a unified operational picture.
3. Business Challenges
The organisation’s greatest challenge was not the absence of operational data—it was the inability to connect related events.
When production deviations occurred, teams investigated SCADA trends, maintenance records, laboratory reports, CCTV footage, and operator logs separately. This fragmented approach extended investigation times and made recurring operational issues difficult to recognise.
The company sought a solution capable of relating machine behaviour, environmental conditions, visual observations, and operational activities into a single decision-making framework without disrupting existing automation systems.