Artificial Intelligence in Indian Manufacturing Industry 2020
The automated manufacturing machines use AI solutions to identify faults in the manufacturing process and notify the production team to eliminate product quality issues. Manufacturing companies are also installing AI-enabled predictive maintenance systems that are capable of self-monitoring and reporting malfunctions in real time. IBM has developed cognitive assistants using 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.
Indian manufacturers are deploying collaborative robots powered by analytics and AI. These 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.
Over the past few years, venture capital firms and global companies like GVFL Ltd., Boschand Hitachi High-Tech Solutions Corporationhave invested in Indian AI start-ups serving the manufacturing industry. These investment activities have supported the development of AI-based solutions, as a result, propelling the growth of AI in the Indian manufacturing industry.
Indian manufacturers are continuously harnessing the power of Industrial Internet of Things (IIoT) by incorporating intelligent controls, sensors and smart switches in their production units. Use of IIoT, together with AI and data analytics, is expected to benefit the manufacturing industry by providing real-time insights for faster decision making.
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.
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. India artificial intelligence market size and growth forecast
4.1.2. Funding in the Indian AI start-ups
Chapter 5: India manufacturing industry overview
5.1. India manufacturing industry overview
5.1.1. India gross value added (GVA) of manufacturing
Chapter 6: Artificial intelligence in the Indian manufacturing industry
6.1. Impact of artificial intelligence in the Indian manufacturing industry
Chapter 7: Use cases of AI in the manufacturing industry
7.1. Use cases of AI 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: Market influencers
9.1. Market drivers
9.2. Market challenges
Chapter 10: Competitive landscape
10.1. Abee Research Labs Pvt. Ltd.
10.1.1. Company information
10.1.2. Business description
10.1.4. Key people
Similar information covered for remaining companies
10.2. EroNkan Technologies Pvt. Ltd.
10.3. Flutura Business Solutions Pvt. Ltd.
10.4. LivNSense Technologies Pvt. Ltd.
10.5. Universal Robots (India) Pvt. Ltd.
10.6. Altizon Systems Pvt. Ltd.
10.7. IBM India Pvt. Ltd.
Chapter 11: Appendix
11.1. Research methodology
11.2. About Netscribes
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