Today’s industrial landscape is beset by many challenges – volatile supply chains, growing demand for sustainability, and ever-increasing volumes of operational data. At such a time, the biggest need for industries is more efficient, resilient, and profitable operations. The solution is Industrial AI – a technology that not only enhances the reliability of assets but also elevates their performance to the highest level.
In this article, we will understand how Industrial AI improves the reliability and performance of assets through smart analytics, and how this technology is shaping the future of industries.
Importance of Data Infrastructure and AI
The success of any industry depends on how efficiently it manages its production resources. Robust data infrastructure, when combined with enterprise visualization and AI technologies, gives you a clear view of the entire lifecycle of your machines and equipment.
This not only leads to earlier identification of potential breakdowns, but also reduces maintenance costs, increases safety and reduces carbon emissions. As a result, companies achieve better ROI (Return on Investment) and ensure Sustainable Operations.
AI-enabled analytics: How does it improve reliability and resilience?
Industrial AI is a blend of multiple intelligence technologies – machine learning, deep learning, reinforcement learning, neural networks and large language models (such as ChatGPT). Their main purpose is to:
- Analyze huge amounts of data
- Identify patterns and relationships
- Predict the future
- And make the best decisions based on those predictions
While earlier equipment maintenance relied only on calendar-based or condition-based strategies, now AI analytics can accurately predict when and what action should be taken. This reduces unplanned interruptions and increases the life of assets.
Five types of AI to increase asset reliability
Different types of AI techniques are adopted to ensure the reliability of industrial assets. Let’s understand:
1. Predictive AI
This technology finds patterns in your data and warns even of minor changes. For example, if the temperature and pressure of a pump are changing differently than normal, it may indicate a potential malfunction.
2. Performance AI
This is also called Hybrid AI Modeling, where machine learning and physics-based simulation are combined. It gives you a 360-degree operational view, reducing risks and tracking performance in real-time.
3. Prescriptive AI
This technology not only explains the cause of the problem, but also suggests the right solution and action plan. It is especially useful in complex industrial plants where safety is a top priority.
4. Prognostic AI
This technology accurately predicts the future – such as “How will the condition of the turbine be in the next two weeks?” or “Will we be able to work without interruption until the next planned maintenance?”. This allows companies to perform maintenance at the right time and avoid unnecessary downtime.
5. Perceptive AI
It is based on generative AI and provides human-like thinking and communication capabilities. Users can ask questions in normal language and get data-based answers immediately. In the future, it will be widely used in production planning, supply chain management, and customer service.
Risk-Based Maintenance and Digital Transformation
Risk-Based Maintenance takes a holistic approach, including analyzing current performance, identifying opportunities for improvement, and testing the right strategies. It combines operational technology (OT) and information technology (IT), leading to digital transformation and helping companies achieve their long-term business goals.
Conclusion
Industrial AI is not just a technology but an indispensable tool for today’s industries to survive and remain competitive. It not only makes operations flexible but also reduces costs, enhances safety and contributes to sustainable development.
The industry of the future belongs to those companies that adopt smart analytics, AI and digital transformation. This will not only increase the reliability of their assets but also create a robust, sustainable and profitable industrial future.
