The framework provides decision makers with real-time knowledge on the best and the most effective operating and maintenance options for their OT systems
Leading global corporations Pöyry and Infosys have jointly introduced an Artificial Intelligence (AI) framework for operational excellence.
The Krti 4.0 model based data driven framework helps overcome some complex and expensive lifecycle management challenges faced by industry, utilities and infrastructure organisations across operational technology (OT) systems, Pöyry claimed in a statement release on Monday.
The framework applies AI, cognitive/machine learning and Machine to Machine (M2M) capabilities to the industrial environment. The applied methodology identifies critical enterprise systems and assets, and provides a deeper understanding of their behavior to unlock and create new value for customers.
Krti 4.0 is designed to dramatically reduce system maintenance costs and expensive operation shutdowns, and improve reliability, employee and environmental safety.
A combination of the unique strengths of Infosys and Pöyry
Krti 4.0 incorporates the Pöyry RAMS (Reliability, Availability, Maintainability, Safety) methodology, which defines the criticality of every asset contributing to the functioning of a OT systems. Infosys’ Nia knowledge-based AI platform continuously executes complex, advanced analytics and machine learning models, exchanging information with the RAMS model to identify any inherent risk in operations of the overall system.
The framework’s open and intuitive machine-to-machine (M2M) interface provides for seamlessly connecting with different OT systems for collecting data. Krti 4.0 makes pervasive and secure industrial IoT connectivity real across all levels on the enterprise.
Krti 4.0 provides decision makers with real-time knowledge on the best and the most effective operating and maintenance options for their OT systems. The framework achieves this by using predictive and prescriptive analytics within acceptable risk levels.
For Industries confronting the problem of asset ‘stranding’ due either to technology obsolesce or to new regulatory regimes, Krti 4.0 provides real options to accelerate Return on Capital Employed (ROCE) and un-strand substantial asset value.
Empowers people to make smart decisions
Krti 4.0 enables a proactive way of thinking, empowering people at all levels of an organisation to make smart decisions. At the highest level, through Krti 4.0’s real-time dashboards, decision-makers have in-depth intelligence about their assets globally across the enterprise.
For plant managers, Krti 4.0’s RAMS modelling capabilities allow for scenario building, enabling the continuous operational improvement of the systems. For maintenance technician, Krti 4.0’s augmented reality and chatbot functionality minimizes repair times.
“Our Krti 4.0 framework using RAMS modelling methodology puts the Pareto principle’s 80/20 rule at the heart of the decision-making process. We know the criticality of each part of the asset and focus our data collection strategy and analytical predictive capabilities where it matters most,” said Richard Pinnock, President, Energy Business Group at Pöyry.
In Krti 4.0, real-time data from critical assets is converted to information with innovative computing and business intelligent algorithms enabling proactive prescriptive decision making, Pinnock explained.
Nitesh Bansal, Senior Vice President and Global Head of Engineering Services, Infosys Ltd., asserted, “In today’s highly competitive and digital world, our clients need to leverage their existing assets to create tangible ROI within a short period of time. Our IoT services are focused on impacting both their top line and bottom line, leveraging our capabilities to remote-monitor products and assets, prevent breakdowns, and analyse data to optimize performance across the entire production system.”
“Having this view into how products and assets operate is not just key to improving their efficiency but also to ensuring security along with legal and regulatory compliance,” Bansal added.
