With AI, engineers can now predict equipment failures

With AI, engineers can now predict equipment failures

AI-powered predictive analytics systems maintain industrial equipment, reducing downtime and operational costs.

BENGALURU: Artificial intelligence (AI) is playing a crucial role in accelerating engineering evolution and transforming traditional approaches, driving a revolution in the engineering landscape by automating tasks, optimising designs, and enabling predictive analytics. In an interaction with TNIE, Sudatta Kar, vice-president & head of engineering—India, Capgemini, has said that with AI, engineers can now generate economical designs, predict equipment failures, and make data-driven decisions more efficiently.

As a result, traditional engineering processes are becoming more agile, innovative, and efficient. She says investments in transformative technologies such as AI, Internet of Things, and machine learning have also fuelled the growth of the semiconductor industry worldwide.

“India’s AI market is growing at 25-35% CAGR, and is expected to reach $17 billion by 2027. Harnessing AI’s capabilities enables engineers to streamline workflows, enhance productivity, and drive innovation across the product life cycle. AI-powered tools and algorithms empower engineers to analyse massive datasets, optimise designs, and predict performance outcomes with unprecedented accuracy. For example, AI-driven design optimisation tools rapidly generate and evaluate design iterations, leading to more efficient solutions,” Kar explains.

AI-powered predictive analytics systems maintain industrial equipment, reducing downtime and operational costs. When Capgemini Research Institute undertook the study for the 15th edition of its World Quality Report, it found that 67% of organisations have incorporated Quality Engineering as part of their business operations and 65% believe that utilisation of AI has driven higher productivity.

As AI continues to permeate every aspect of engineering from product design and development to manufacturing and supply chain management, Kar says we can expect to see significant shifts in market dynamics and competitive landscapes.

Companies that embrace AI in their ER&D processes will gain a competitive edge by delivering products and services that meet evolving customer needs and market demands. Moreover, AI-driven insights and predictive analytics will enable companies to anticipate market trends, identify new opportunities, and adapt robust strategies in real-time, positioning them for growth in an increasingly dynamic and competitive global marketplace, she says.

On the potential applications of AI in key areas, she says: “We see AI displaying immense promise in terms of improving overall operational efficiency. This involves leveraging AI for tasks like software development with coding assistants, automating testing processes, and managing knowledge effectively within organisations. We also see further down the road interesting use cases in the ER&D space such as the fastest ever drug discovery phase in developing new molecules or lighter parts in automotive and aerospace.”

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