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Global Edge AI for Smart Manufacturing Market Growth (Status and Outlook) 2025-2031

Publisher LP Information, Inc.
Published Aug 05, 2025
Length 113 Pages
SKU # LPI20275507

Description

According to this study, the global Edge AI for Smart Manufacturing market size will reach US$ 1848 million by 2031.

Edge AI for smart manufacturing refers to the use of artificial intelligence algorithms processed locally on hardware devices ("at the edge") within a manufacturing environment, without relying on centralized cloud infrastructure. These devices integrate sensors, embedded processors, and AI models to enable real-time decision-making, anomaly detection, quality control, and automation in factories and industrial settings.This approach reduces latency, enhances data privacy, saves bandwidth, and improves operational efficiency by enabling fast, on-site intelligence.

LPI (LP Information)' newest research report, the “Edge AI for Smart Manufacturing Industry Forecast” looks at past sales and reviews total world Edge AI for Smart Manufacturing sales in 2024, providing a comprehensive analysis by region and market sector of projected Edge AI for Smart Manufacturing sales for 2025 through 2031. With Edge AI for Smart Manufacturing sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Edge AI for Smart Manufacturing industry.

This Insight Report provides a comprehensive analysis of the global Edge AI for Smart Manufacturing landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Edge AI for Smart Manufacturing portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Edge AI for Smart Manufacturing market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Edge AI for Smart Manufacturing and breaks down the forecast by Solution, by End User, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Edge AI for Smart Manufacturing.

This report presents a comprehensive overview, market shares, and growth opportunities of Edge AI for Smart Manufacturing market by product type, application, key players and key regions and countries.

Segmentation by Solution:
Predictive Maintenance
Process Optimization
Anomaly Detection
Quality Inspection
Others

Segmentation by End User:
Automotive Manufacturing
Electronics and Semiconductor Fabs
Food and Beverage Production
Pharmaceuticals and Medical Device Manufacturing
Heavy Machinery and Equipment Assembly
Others

This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries

The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Google
NVIDIA
Intel
Qualcomm Technologies
Siemens
Edgeimpulse, Inc
Hailo
Ambarella International
Ceva Inc
STMicroelectronics
Infineon
Lattice Semiconductor

Please note: The report will take approximately 2 business days to prepare and deliver.

Table of Contents

113 Pages
*This is a tentative TOC and the final deliverable is subject to change.*
1 Scope of the Report
2 Executive Summary
3 Edge AI for Smart Manufacturing Key Players
4 Edge AI for Smart Manufacturing by Regions
5 United States
6 Europe
7 China
8 Rest of World
9 Market Drivers, Challenges and Trends
10 Key Investors in Edge AI for Smart Manufacturing
11 Key Players Analysis
12 Research Findings and Conclusion

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