Artificial Intelligence (AI) in Indian Manufacturing Industry 2020

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Description

The manufacturing industry in India is edging toward a digital overhaul, with the adoption of industry 4.0 technologies. Several Indian manufacturing companies have been investing in artificial intelligence (AI)-based factory automation solutions to improve product quality and design, reduce labor costs, minimize manufacturing cycles, and monitor real-time condition of machines. AI has helped companies such as Blue Star Ltd., TVS Motor Company Ltd., JK Tyre & Industries Ltd., and Asian Paints Ltd., to enhance efficiency and productivity in their manufacturing units.
The contribution of AI in manufacturing to India’s gross value added (GVA) was valued at INR 1,227.46 Bn in 2019, and is expected to reach INR 4,845.64 Bn by 2025, expanding at a at a compound annual growth rate (CAGR) of ~27.41% during the forecast period (2020-2025). AI is being implemented for factory automation, quality monitoring, predicting equipment failure, order management, delivery management, and demand forecasting.
Market trends:
Indian manufacturing companies are utilizing AI-enabled predictive maintenance systems for self-monitoring and reporting malfunctions in real time. IBM has developed its cognitive computing platform, Watson for manufacturers to reduce errors and improve product quality. Similarly, Qualitas Technologies has developed the Eagle Eye Inspection System, which uses an AI-based vision controller to check the quality of products.
Players in the Indian manufacturing sector have been keen on the use of collaborative robots that leverage AI and analytics. Collaborative robots are capable of handling additional cognitive tasks and making independent decisions based on real-time data. Blue Star Ltd. is using AI-enabled collaborative robots (offered by Universal Robots A/S) to optimize the task of copper tube expansion and minimize stress risks associated with it.
Impact of COVID-19:
The unprecedented turmoil caused by the pandemic has changed the business landscape of the manufacturing sector. Frontier technologies such as AI have become the key to maintain resilience against the multi-pronged effect of the pandemic. Manufacturing units that struggled with significant labor shortage during the lockdown, adopted AI-based solutions to continue production. Government initiatives such as the Atmanirbhar Bharat mission and production linked incentives (PLI) are expected to drive the adoption of AI in the manufacturing industry amid the pandemic.
Global players are aiming to divest in China and considering India to be a preferred destination to shift their manufacturing base. The Indian players can seize this opportunity and leverage AI to create a safe, inter-connected, intuitive, and interactive manufacturing environment.
Companies covered
• Abee Research Labs Pvt. Ltd.
• EroNkan Technologies Pvt. Ltd.
• Flutura Business Solutions Pvt. Ltd.
• LivNSense Technologies Pvt. Ltd.
• Universal Robots (India) Pvt. Ltd.
• Altizon Systems Pvt. Ltd.
• IBM India Pvt. Ltd.

Additional information

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Geography Covered

Date Published

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Table of Contents

Chapter 1: Executive summary

Chapter 2: Socio-economic indicators

Chapter 3: Introduction
3.1. Market definition and structure
3.2. Major global players using AI-based manufacturing process

Chapter 4: India artificial intelligence market overview
4.1. India artificial intelligence market overview
4.1.1. AI market size and growth forecast: Contribution of AI to GVA

Chapter 5: India artificial intelligence in manufacturing industry overview
5.1. India manufacturing industry overview
5.2. Artificial intelligence in manufacturing industry overview
5.2.1. AI in manufacturing market size and growth forecast: Contribution of AI in manufacturing to GVA

Chapter 6: Application of artificial intelligence in manufacturing industry
6.1. Major applications
6.2. Sector-wise applications

Chapter 7: Use cases of artificial intelligence in the manufacturing industry
7.1. Use cases of artificial intelligence in the manufacturing industry
Chapter 8: Case studies
8.1. Case study – Blue Star Ltd.
8.2. Case study – TVS Motor Company Ltd.
8.3. Case study – JK Tyre & Industries Ltd.
8.4. Case study – Bajaj Auto Ltd.
8.5. Case study – Asian Paints Ltd.

Chapter 9: Impact of COVID-19
9.1. Impact of COVID-19

Chapter 10: Market influencers
10.1. Market drivers
10.2. Market challenges
Chapter 11: Competitive landscape
11.1. Abee Research Labs Pvt. Ltd.01
11.1.1. Company information
11.1.2. Business description
11.1.3. Products/services
11.1.4. Key people
Note: Similar information covered for other companies
11.2. EroNkan Technologies Pvt. Ltd.
11.3. Flutura Business Solutions Pvt. Ltd.
11.4. LivNSense Technologies Pvt. Ltd.
11.5. Universal Robots (India) Pvt. Ltd.
11.6. Altizon Systems Pvt. Ltd.
11.7. IBM India Pvt. Ltd.

Chapter 12: Recent Developments
12.1. Recent developments
Chapter 13: Appendix
13.1. Research methodology
13.2. About Netscribes
13.3. Disclaimer

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