India AI in Manufacturing Market Research Report 2023 offers a comprehensive analysis of the market, including business opportunities, growth, and trend analysis for various applications, types, and regions such as North America, Europe, Asia-Pacific, South America, Middle East, and Africa. The report delves into important producers, market developments, opportunities, challenges, and threats to the market as a whole. It is a 100+ page report that provides a detailed examination of growth statistics, opportunities, trends and the competitive landscape in the industry.
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The contribution of AI in the Indian GVA was valued at INR 12,272.38 Billion in 2020 and is expected to reach INR 40,703.34 Billion by 2025, expanding at a CAGR of 4.83% during the forecast period (2021 to 2026).
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.
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.
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Our most recent research report showcases the thriving expansion of the India AI in Manufacturing Market and offers in-depth insights into the projected market size, share, and revenue until 2030.
The report addresses the following key questions regarding the India AI in Manufacturing market:
- What is the expected growth rate of the market in the upcoming years and what factors are driving this growth?
- How do consumers perceive and adopt different types of India AI in Manufacturing in the market?
- How are regulatory policies and government initiatives impacting the growth of the India AI in Manufacturing market?
- What is the market share of the top 5 players in the India AI in Manufacturing market and how is it likely to change in the future?
- What are the latest technologies and innovations in the India AI in Manufacturing market and how are they shaping the industry landscape?
- How do macroeconomic factors such as inflation, GDP, and exchange rates affect the India AI in Manufacturing market?
- What are the challenges related to the supply chain and logistics that India AI in Manufacturing market players face and how are they addressing them?
- How is the changing consumer behavior and preferences influencing the dynamics of the India AI in Manufacturing market?
- What are the potential risks and uncertainties associated with investing in the India AI in Manufacturing market, and how can they be mitigated?
Reasons to Buy This Report
(A) The research provides valuable insights for top administration, policymakers, professionals, product advancements, sales managers, and stakeholders in the market. It helps them make informed decisions and strategize effectively.
(B) The report offers comprehensive analysis of India AI in Manufacturing market revenues on a global, regional, and country level, projecting trends until 2030. This data allows companies to assess their market share, identify growth opportunities, and explore new markets.
(C) The research includes segmentation of the India AI in Manufacturing market based on types, applications, technologies, and end-uses. This segmentation enables leaders to plan their products and allocate resources based on the expected growth rates of each segment.
(D) Analysis of the India AI in Manufacturing market benefits investors by providing insights into market scope, position, key drivers, challenges, restraints, expansion opportunities, and potential threats. This information helps them make informed investment decisions.
(E) The report offers a detailed analysis of competitors, their key strategies, and market positioning. This knowledge allows businesses to better understand the competition and plan their own strategies accordingly.
(F) The study helps evaluate India AI in Manufacturing business predictions by region, key countries, and top companies, providing valuable information for investment planning and decision-making.
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