Infosys and Finnish Pöyry Release Krti 4.0; An AI Framework for Operational Excellence
Software giant Infosys and Finnish global corporation Pöyry have announced the release of Krti 4.0, Artificial Intelligence (AI) Framework for Operational Excellence. The framework helps solve some complex and costly lifecycle management problems currently challenging the industry, utilities, and infrastructure organisations across operational technology (OT) systems.
According to an Infosys statement, the data driven framework, which is based on Krti 4.0 model, uses AI, cognitive/machine learning, and Machine to Machine (M2M) competences to the industrial environment. The applied methodology recognizes critical enterprise systems and assets, offering a profounder comprehension of their behaviour to unveil and form new value for customers. Krti 4.0 is intended to affectedly lessen system maintenance costs and expensive operation shutdowns, while improving reliability and employee and environmental safety.
The data driven framework incorporates the Pöyry RAMS (Reliability, Availability, Maintainability, Safety) methodology, which outlines the significance of every asset that contributes to the running of 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. Krti 4.0’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 of the enterprise,” an Infosys statement explained.
The statement also says that Krti 4.0 aids decision makers with real-time knowledge on selecting the optimum operating and maintenance options for their OT systems, for which, it uses predictive and prescriptive analytics within acceptable risk levels.
Several industries right now are faced with the problem of asset stranding, because of technology obsolesce or to new regulatory regimes. Stranded assets are assets that have become obsolete or non-performing, but must be recorded on the balance sheet as a loss of profit. They are assets that have had to be written down, devalued, or converted to liabilities because of unanticipated reasons. Krti 4.0 claims to provide real options to accelerate Return on Capital Employed (ROCE) and un-strand substantial asset value.
“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” says Nitesh Bansal, Senior Vice President and Global Head of Engineering Services, Infosys Ltd.
Krti 4.0 attempts to make way for a proactive way of thinking, empowering people at all levels of an organisation to make smart decisions. At the highest level, through its real-time dashboards, decision-makers can gain detailed intelligence regarding their assets globally across the enterprise. For plant managers, its RAMS modelling capabilities aid in scenario building, allowing continuous operational improvement of systems. For maintenance technicians, its 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. 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. This is the difference,” says Richard Pinnock, President, Energy Business Group at Pöyry.