Figure 3 An asset health monitoring dashboard
Examples of autonomous orchestration Higher levels of autonomy require greater data and applica- tion integration. High-quality contextualised data is imper- ative for building, deploying, and maintaining AI models at scale to support ‘worker enablement’ and IA2IA. Worker enablement is a strategic practice that provides employees with everything they need to do their jobs to the best of their abilities and creates an environment that allows them to perform optimally. A prerequisite for achieving higher levels of autonomy is to ensure workers are ‘connected’ or integrated with their environment via technology. Technology can include hard- ware, network, and software tools that enable workers to communicate, collaborate, and access predictive informa- tion in real-time. Worker enablement applies to all workers,
as ‘soft sensors’ for product quality assessment in industrial environments. By replacing traditional physical analysers, these sophisticated AI systems provide immediate, cost- effective quality estimates directly from operating param- eters. Unlike conventional methods that require time- consuming lab tests or analyser processing, neural networks deliver real-time insights, eliminating hardware maintenance costs and operational delays. Their ability to rapidly analyse complex data sets and continuously improve through ML makes them an invaluable tool for manufacturers seeking to enhance production efficiency and product consistency. As AI technology advances, neural networks are increasingly becoming a critical component in modern quality control strategies, offering unprecedented speed, accuracy, and adaptability across diverse industrial applications.
Corporate dashboards PAT, EBIT, Safety, Environment, Ops e ciency etc.
Executive
Directorate dashboards Projects, Production plan/actual cost,
Manager
Sales & marketing etc. Safety, actual vs target
Asset dashboards Production, Facility status. Quality, Facility utilisation, Maintenance, Energy etc.
Supervisor
Station dashboards
Operator
Unit details, Alarms. Samples, Tag details, Work orders etc.
Figure 4 An example of an operational advisory decision support dashboard displaying the different levels of granularity of data required to make decisions based on the employees’ role in the process
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PTQ Q2 2025
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