Accelerating Machine Learning Deployment in Industrial Environments

Many industrial organisations pursue artificial intelligence but struggle to move projects beyond the pilot stage. Production facilities operate a maze of historians, SCADA systems, PLCs, spreadsheets and maintenance databases. Data lives everywhere and nowhere. Models remain stuck in notebooks rather than delivering value in the plant. ARDI’s Industrial DataOps platform is designed to break this cycle by providing a consolidated, contextualised and actionable foundation for industrial AI.

In modern facilities, engineers and data scientists must work with data generated by historians, DCS, SCADA and PLCs. Adding ERP, shift, maintenance and production records increases complexity. Collecting and aligning these feeds for a single machine learning project can take weeks. 

Each system uses different formats and time stamps, making models brittle and difficult to maintain. ARDI addresses this by consolidating process variables and related data from multiple sources into a unified platform. It gathers information from monitoring and control systems, production databases and alert systems. Importantly, ARDI does not duplicate data; it makes information available in one place, producing a live, complete picture of each asset. This consolidation eliminates silos and removes hours of manual data wrangling.

A tidy dataset alone is not enough. Machine learning models also require context. ARDI helps organisations consolidate and contextualise information in ways that are human readable, bring different knowledge domains together and work with a wide range of tools.  

The platform’s asset relationship model maps sensors, equipment, documents and departments so that features carry real meaning. This structure speeds feature engineering and keeps models robust even as systems change. ARDI’s open driver framework and flexible API allow teams to develop new applications or integrate with Python, JavaScript or other analytics tools.

Once data is consolidated and contextualised, ARDI’s machine learning capabilities can run continuously to optimise processes by identifying inefficiencies, predicting equipment failures and adjusting operating conditions. By analysing data from a wide range of sources, ARDI’s algorithms uncover trends that traditional control and expert systems miss. The result is more efficient resource use, fewer unplanned shutdowns and improved product quality.

ARDI also excels at delivering insights to the people who need them. Visual dashboards, alarms and three dimensional environments present complex data in a format that operators, engineers and plant managers can understand immediately. When conditions change, teams can react quickly and confidently because they trust the underlying information. This combination of continuous analytics and intuitive visualisation turns machine learning from a science project into a day to day business tool.

Machine learning deployment should not require a complete overhaul of control infrastructure. ARDI integrates seamlessly with existing SCADA, PLC and DCS systems and consolidates data without replicating it. The platform can run on premises for real time performance and security or be deployed in the cloud when appropriate. ARDI is open, flexible, scalable and vendor independent. This allows organisations to start with a proof of concept and scale across a plant without vendor lock in.

Machine learning is not just about algorithms; it depends on clean, reliable and contextualised data. ARDI’s Industrial DataOps suite provides the foundation needed to turn fragmented data into predictive insights. For organisations seeking to reduce downtime, improve quality or optimise energy use, ARDI helps achieve those goals more quickly.

To learn how ARDI’s services can accelerate industrial machine learning deployment, contact us to connect with our team. Our team will help you to consolidate data, develop robust models and operationalise them across multiple sites. This first conversation can be the catalyst for smarter, more efficient operations.