The manufacturing industry in India is on the precipice of transformation—a shift to Industry 5.0, where humans and machines work together to boost efficiency and productivity. The key focus area at the heart of this shift is the pursuit of quality, where the dual combination of artificial intelligence (AI) and machine learning (ML) technologies plays a pivotal role. According to the PwC India Survey, Indian companies are showing an upward trend towards adopting analytics and AI, with a current implementation rate of 54 per cent.
One of the key sectors to face the most impact in manufacturing is original equipment manufacturers (OEMs). Tasked with delivering components to other industries, the rising demand for global standard goods across different sectors means that OEMs must meet the rising demand. To do so, OEMs have turned to technology to build smarter factories. But this transition brings to the forefront three big bottlenecks: legacy infrastructure, rising input concerns in data integration, and skill gaps.
Let’s take a closer look at what these challenges are: Treading new horizons through a holistic approach
Integration of new technologies with existing processes and legacy systems offers a complex challenge, especially with compatibility. Any form of tech integration with a process-heavy system like manufacturing throws up tons of data. Gathering data from different sources and leveraging it to provide an integrated perspective is extremely challenging. Another major challenge is the skilled workforce shortage to work with the new technologies.
This story is from the February 2024 edition of The Machinist.
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This story is from the February 2024 edition of The Machinist.
Start your 7-day Magzter GOLD free trial to access thousands of curated premium stories, and 9,000+ magazines and newspapers.
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