AI in Manufacturing Industry in India 2021
Market insights:
With the introduction of industry 4.0 technology, India's manufacturing industry is on the verge of a digital transformation. Several Indian manufacturing firms have invested in artificial intelligence (AI)-based industrial automation technologies to improve product quality and design, save labour costs, shorten manufacturing cycles, and track equipment health in real time. Blue Star Ltd., TVS Motor Company Ltd., JK Tyre & Industries Ltd., and Asian Paints Ltd. have all used AI to boost the efficiency and productivity of their production plants.
The contribution of AI in the Indian GVA was valued at INR 12,272.38 Bn in 2020 and is expected to reach INR 40,703.34 Bn by 2025, expanding at a CAGR of 4.83% during the forecast period (2021 – 2026). AI is being implemented for factory automations, 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 to minimize stress risks associated with it.
Impact of COVID-19:
The unprecedented impact of the pandemic has changed the business landscape of the manufacturing sector. Frontier technologies such as AI have become the key to maintaining resilience against the effects of the pandemic. Manufacturing units that struggled with significant labor shortages during the lockdown adopted AI-based solutions to continue with production. Government initiatives such as the Atmanirbhar Bharat mission and Production Linked Incentive Scheme for White Goods (PLIWG) are expected to drive the adoption of AI in the manufacturing industry amid the pandemic.
Global players are aiming to divest in China and are considering India as the preferred destination to shift their manufacturing bases. Indian players can seize this opportunity and leverage AI to create a safe, inter-connected, intuitive, and interactive manufacturing environment.
With the introduction of industry 4.0 technology, India's manufacturing industry is on the verge of a digital transformation. Several Indian manufacturing firms have invested in artificial intelligence (AI)-based industrial automation technologies to improve product quality and design, save labour costs, shorten manufacturing cycles, and track equipment health in real time. Blue Star Ltd., TVS Motor Company Ltd., JK Tyre & Industries Ltd., and Asian Paints Ltd. have all used AI to boost the efficiency and productivity of their production plants.
The contribution of AI in the Indian GVA was valued at INR 12,272.38 Bn in 2020 and is expected to reach INR 40,703.34 Bn by 2025, expanding at a CAGR of 4.83% during the forecast period (2021 – 2026). AI is being implemented for factory automations, 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 to minimize stress risks associated with it.
Impact of COVID-19:
The unprecedented impact of the pandemic has changed the business landscape of the manufacturing sector. Frontier technologies such as AI have become the key to maintaining resilience against the effects of the pandemic. Manufacturing units that struggled with significant labor shortages during the lockdown adopted AI-based solutions to continue with production. Government initiatives such as the Atmanirbhar Bharat mission and Production Linked Incentive Scheme for White Goods (PLIWG) are expected to drive the adoption of AI in the manufacturing industry amid the pandemic.
Global players are aiming to divest in China and are considering India as the preferred destination to shift their manufacturing bases. Indian players can seize this opportunity and leverage AI to create a safe, inter-connected, intuitive, and interactive manufacturing environment.
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: AI MARKET IN INDIA – AN OVERVIEW
4.1. India artificial intelligence market overview
4.1.1. AI market size and growth forecast: Contribution of AI to GVA
CHAPTER 5: AI IN THE MANUFACTURING INDUSTRY – AN OVERVIEW
5.1. Manufacturing industry in India – An overview
5.2. AI in the manufacturing industry – An overview
5.2.1. Market size and growth forecast of AI in manufacturing: Contribution of AI in manufacturing to GVA
CHAPTER 6: APPLICATION OF AI IN MANUFACTURING
6.1. Major applications
6.2. Sector-wise applications
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: 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 has been 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
COMPANIES PROFILED
COMPANIES PROFILED
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: AI MARKET IN INDIA – AN OVERVIEW
4.1. India artificial intelligence market overview
4.1.1. AI market size and growth forecast: Contribution of AI to GVA
CHAPTER 5: AI IN THE MANUFACTURING INDUSTRY – AN OVERVIEW
5.1. Manufacturing industry in India – An overview
5.2. AI in the manufacturing industry – An overview
5.2.1. Market size and growth forecast of AI in manufacturing: Contribution of AI in manufacturing to GVA
CHAPTER 6: APPLICATION OF AI IN MANUFACTURING
6.1. Major applications
6.2. Sector-wise applications
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: 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 has been 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
COMPANIES PROFILED
COMPANIES PROFILED
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.
