Smart Manufacturing: How AI can propel India to the top of the global production chain

India's manufacturing sector stands at a critical and troubling juncture. Despite ambitious initiatives like 'Make in India' and the Production Linked Incentive (PLI) scheme, manufacturing's contribution to GDP has declined from 17.4% in 2006 to approximately 13% in recent years. This is in stark contrast to competitors like China, where manufacturing accounts for nearly 28% of GDP, or Vietnam at 25%. The gap isn't just in numbers – it represents missed opportunities for job creation, economic growth, and technological advancement. It is reflecting in the jobs crisis in India and had an impact on electoral results.

The challenges facing Indian manufacturing are manifold. Infrastructure bottlenecks, complex regulatory frameworks, and skill gaps are some of those, affecting growth and efficiency. While India has established itself as a services powerhouse, specifically in IT and BPO services, the manufacturing sector has struggled to achieve similar success. High logistics costs, estimated at 14% of GDP compared to the global average of 8%, further erode competitiveness. Additionally, small and medium enterprises or SMEs, which form the backbone of Indian manufacturing, often lack access to advanced technologies, good credit and other best practices.

It is here that India should look at Artificial Intelligence as a potential technology to ratchet up its manufacturing performance. The emergence of AI and generative AI, gives a transformative opportunity to address these challenges and revolutionise India's manufacturing landscape. I speculate on some of the ways AI can do so:

Smart Factory Operations

AI can help build smart, robotic factories. For example, AI-powered predictive maintenance systems can dramatically reduce equipment downtime and maintenance costs. By analysing sensor data from machinery, these systems can predict failures before they occur, enabling proactive maintenance. Companies like Tata Steel have reportedly claimed a 20% reduction in maintenance costs through AI implementation. Generative AI can go further by suggesting optimal maintenance schedules and procedures based on historical data and current conditions. Process Co-pilots, developed by companies such as Findability Sciences, can help optimise manufacturing processes and present real time views to the management.

Quality Control and Defect Detection

Computer vision and machine learning algorithms can perform quality inspections with greater accuracy than human inspectors. Generative AI can analyse patterns in defect data to suggest process improvements and design modifications. This is particularly valuable in sectors like automotive and electronics manufacturing, where quality standards are stringent and defect costs are high.

Supply Chain Optimisation

AI can transform supply chain management by predicting demand patterns, optimising inventory levels, and suggesting alternative suppliers during disruptions. Generative AI can simulate various supply chain scenarios, helping manufacturers prepare for contingencies. This could significantly reduce India's logistics costs and improve delivery reliability. While no substitute for building better transportation and supply chain infrastructure, AI can do its bit to optimise what is available.

Skill Development and Training

One of the most promising applications of generative AI is in workforce training for manufacturing. AI-powered systems can create personalised training modules, simulate complex manufacturing processes, and provide real-time guidance to workers. This can help bridge the skill gap that currently plagues Indian manufacturing, particularly in advanced manufacturing techniques.

Energy Efficiency

AI algorithms can optimise energy consumption in manufacturing facilities by analysing usage patterns and suggesting operational adjustments. With energy costs being a significant factor in manufacturing competitiveness, this could provide Indian manufacturers with a crucial advantage.

The government needs to play a big role in accelerating AI adoption in manufacturing through several initiatives:

First, establishing AI Centres of Excellence focused on manufacturing applications, similar to successful models in countries like Germany and South Korea. These centres can serve as testing grounds for AI solutions and provide technical support to manufacturers, particularly SMEs.

Second, creating a regulatory framework that encourages AI adoption while ensuring data security and ethical use. This includes standards for AI implementation in manufacturing and guidelines for data sharing between stakeholders.

Third, providing financial incentives for AI adoption, particularly for SMEs. This could include tax benefits for AI investments and subsidies for technology upgrades.

But efforts by the government alone are not enough. Industry needs to step up too. Manufacturing companies need to approach AI adoption strategically, and this would involve a few things:

- Conducting thorough assessments of their AI readiness and identifying high-impact application areas

- Investing in digital infrastructure and data collection systems

- Building partnerships with AI solution providers and research institutions

- Developing in-house AI capabilities through hiring and training

- Building AI Literacy amongst its management and employees

For India to achieve its target of increasing manufacturing's share in GDP to a globally respectable 25%, AI adoption needs to be scaled and accelerated. The technology's potential to improve efficiency, reduce costs, and enhance quality makes it an essential tool in this journey. Success will require coordinated efforts from government, industry, and academia, but the potential rewards – in terms of economic growth, job creation, and global competitiveness – make this investment worthwhile. India has done this in Digital Public Infrastructure by digitally transforming a country at scale. We need a similar National Mission on how to use AI and other digital technologies to leapfrog traditional manufacturing constraints. By embracing AI comprehensively, India can not only revitalise its manufacturing sector but also position itself as a global manufacturing hub for the AI era.

Authored by Jaspreet Bindra, Co-founder of AI&Beyond