
Artificial Intelligence in Manufacturing Industry in India
Description
In recent years, the manufacturing sector has undergone substantial evolution, emerging as one of the fastest-growing industries. The advent of the fourth industrial revolution, Industry 4.0, driven by cyber-physical systems, big data analytics, IIoT, cloud computing infrastructure, AI, and 3D printing, has revolutionized manufacturing. AI adoption in manufacturing encompasses factory automation, quality monitoring, equipment failure prediction, order management, delivery management, and demand forecasting.
Market insights:
The market size of artificial intelligence (AI) in manufacturing in India is projected to reach INR 12,596.33 Mn by 2028, growing at a compound annual rate of 58.96% from 2023 to 2028. Evolving customer preferences, new distribution models, geopolitical changes, supply chain disruptions, and ESG regulations are creating opportunities for the manufacturing sector to innovate and reshape existing business models.
Market drivers:
Government initiatives in India, such as Make in India, Start-up India, and Industry 4.0, have encouraged technology-driven start-ups, software firms, and manufacturing companies to integrate AI into their daily operations, enhancing accuracy, flexibility, productivity, and efficiency. The Indian startup ecosystem is undergoing a transformation with growing investments in intelligent automation, artificial intelligence, machine learning, and Big Data.
Market challenges:
Converting conventional factories into AI-driven manufacturing units necessitates substantial capital investment, covering expenses for procuring and installing connected sensors, intelligent cameras, data analytics software, and other components. Despite the emergence of Indian start-ups in the AI market, investor reluctance, both domestically and internationally, persists due to apprehensions about failure and a limited understanding of AI systems.
Market insights:
The market size of artificial intelligence (AI) in manufacturing in India is projected to reach INR 12,596.33 Mn by 2028, growing at a compound annual rate of 58.96% from 2023 to 2028. Evolving customer preferences, new distribution models, geopolitical changes, supply chain disruptions, and ESG regulations are creating opportunities for the manufacturing sector to innovate and reshape existing business models.
Market drivers:
Government initiatives in India, such as Make in India, Start-up India, and Industry 4.0, have encouraged technology-driven start-ups, software firms, and manufacturing companies to integrate AI into their daily operations, enhancing accuracy, flexibility, productivity, and efficiency. The Indian startup ecosystem is undergoing a transformation with growing investments in intelligent automation, artificial intelligence, machine learning, and Big Data.
Market challenges:
Converting conventional factories into AI-driven manufacturing units necessitates substantial capital investment, covering expenses for procuring and installing connected sensors, intelligent cameras, data analytics software, and other components. Despite the emergence of Indian start-ups in the AI market, investor reluctance, both domestically and internationally, persists due to apprehensions about failure and a limited understanding of AI systems.
Table of Contents
75 Pages
- Table of Contents
- Chapter 1: Executive summary
- Chapter 2: Socio-economic indicators
- Chapter 3: Introduction
- 3.1. Market definition and structure
- 3.2. Manufacturing industry in India
- 3.3. Major stockholders
- Chapter 4: Market Overview
- 4.1. Manufacturing market – An overview
- 4.2. Artificial intelligence in manufacturing industry in India market size and growth forecast based on value (2020 – 2028e)
- 4.3. Major global players providing AI-based manufacturing products/solutions
- Chapter 6: Application of AI in Manufacturing
- 5.1. Major applications
- 5.2. Sector-wise applications
- Chapter 6: Use Cases of AI in the Manufacturing Industry
- 6.1. Use cases of AI in the manufacturing industry
- Chapter 7: SWOT Analysis
- 7.1. SWOT analysis
- Chapter 8: Porter’s Five Forces Analysis
- 8.1. Porter’s five forces analysis
- Chapter 9: Case Studies
- 9.1. Case study – Blue Star Limited
- 9.2. Case study – TVS Motor Company Limited
- 9.3. Case study – JK Tyre & Industries Limited
- 9.4. Case study – Bajaj Auto Limited
- 9.5. Case study – Asian Paints Limited
- Chapter 10: Impact of COVID-19
- 10.1. Impact of COVID-19
- Chapter 11: Government Initiatives
- 11.1. Government initiatives
- Chapter 12: Market Influencers
- 12.1. Market drivers
- 12.2. Market challenges
- Chapter 13: Competitive Landscape
- 13.1. Tata Consultancy Services Limited
- Company information
- Business description
- Products/services
- Key people
- Financial snapshot
- Key ratios
- Key financial performance indicators
- Key business segments
- Key geographic segments
- Note: Financial information covered for public companies only
- 13.2. Wipro Limited
- 13.3. Abee Research Labs Private Limited
- 13.4 EroNkan Technologies Private Limited
- 13.5. Flutura Business Solutions Private Limited
- 13.6. LivNSense Technologies Private Limited
- 13.7. Altizon Systems Private Limited
- 13.8. IBM India Private Limited
- 13.9. Microsoft Corporation India Private Limited
- 13.10. Universal Robots (India) Private Limited
- Chapter 14: Recent Developments
- 14.1. Recent developments
- Chapter 15: Appendix
- 15.1. Research methodology
- 15.2. About Netscribes
- 15.3. Disclaimer
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