summary
During the week of July 13-July 19, 2025, we extracted news on the application of artificial intelligence (AI) in the manufacturing industry. A series of important announcements and demonstrations were made that will shape the future of the manufacturing industry, including significant advances in industrial robotics technology, the practical application of generative AI in manufacturing, and innovations in supply chain optimization. This article analyzes a selection of AI-related news from around the world announced during the past week, focusing on technologies and case studies with high potential for application in the manufacturing industry, and explores their significance and impact on the future.
1. innovative advances in industrial robotics
Full-scale introduction of humanoid robots to manufacturing sites
The most notable announcement during this period was Nvidia and Foxconn’s joint plan to deploy humanoid robots at the AI server manufacturing plant in Houston, Texas, which is scheduled to begin operations in the first quarter of 2026. When it does, it will be the first time a humanoid robot has been directly involved in the assembly of an Nvidia product.
Foxconn is already in the process of training prototype robots (including China’s UBTech model) to perform component picking and placement, cable insertion, and assembly tasks, demonstrating their potential to fundamentally transform the traditional electronics manufacturing process. Their implementation in a modern, spacious factory facility will be a showcase for the world to see how far autonomous robot technology can go in assisting factory operations.
Development of Humanoid Technology in Europe
Several innovative humanoid robots were also unveiled in Europe, including Hexagon, which unveiled its first humanoid specifically designed for industrial applications, AEON, at the Hexagon LIVE Global event, with dual mobility capabilities aimed at solving labor shortages in the manufacturing and logistics industries.
French startup Wandercraft has unveiled Calvin, a humanoid robot, in a strategic partnership with the Renault Group. Renault has acquired a minority stake in the company and plans to invest 50 million euros to jointly develop the robot at a Renault plant.
Germany’s NEURA Robotics also premiered its third-generation cognitive humanoid, 4NE1, at Automatica 2025 and simultaneously announced the market launch of MiPA, a service robot for home and care use. These robots are equipped with a sensor “skin” for safe collaboration with humans and AI perception capabilities, and are intended to free workers from repetitive and heavy work in factories and warehouses.
Robot Introduction Surges in Japan’s Automotive Industry
According to preliminary data from the International Federation of Robotics (IFR), the Japanese automotive industry will install approximately 13,000 industrial robots in 2024, an 11% increase over the previous year. This is the highest number of installations since 2020 and is the result of investments in production line adaptations associated with the conversion to electric, fuel cell, and hydrogen vehicles.
Japan is the dominant leader with 38% of the world’s industrial robot production, and the automotive industry has the fourth highest robot density in the world (after Slovenia, South Korea, and Switzerland) with 1,531 robots per 10,000 employees.
ABB’s new generation of industrial robots
ABB Robotics heralded a new era of “autonomous versatile robotics” at Automatica 2025 (Munich) with the launch of three large industrial robot arms (IRB 6730S, IRB 6750S, and IRB 6760) and a new autonomous mobile robot.
The IRB 6730S and IRB 6750S are shelf-mounted robots that can handle payloads of up to 350 kg and can be ceiling or mezzanine mounted. The IRB 6760 is a press tending robot for medium-sized press lines with a throughput of up to 900 parts per hour and is designed for automotive and electronics plants.
Accelerate practical application of AI-driven quality control systems
Expanding market for automated vision inspection systems
In the AI-driven quality control segment, the market for automated vision inspection systems is projected to reach $2.3 billion by 2025. Manufacturers’ increasing emphasis on compliance and accuracy is driving market growth.
Compared to traditional quality control methods, the AI visual inspection system offers the following significant improvements
- Comprehensive quality assurance through 100% inspection (transcends traditional statistical sampling methods)
- Complete elimination of the effects of human fatigue and prejudice
- Real-time defect identification for immediate response
- High-speed processing of thousands of images with high-resolution imaging and analysis
Industry Applications
Automotive Industry: UnitX works with many automotive companies to inspect their vehicles using machine vision-based systems. We have detected 10-40% more defects than manual inspections, resulting in a significant improvement in product quality.
Medical Equipment: Dovideq Medical Systems uses automated systems for endoscopy to ensure compliance with quality standards for medical equipment that directly affects patient safety.
Food processing: minimize waste by detecting contaminants, packaging defects, and labeling errors while ensuring compliance with food safety regulations.
Expansion of manufacturing applications of generated AI
Generative AI Support for Manufacturing with AWS
Amazon Web Services (AWS) announced on July 15 a comprehensive solution to solve five key challenges of implementing generative AI in the manufacturing industry: data quality, ROI calculation, workforce training and implementation, security and compliance, and legacy system integration.
In the Georgia-Pacific case study, the company leveraged a centralized data store on AWS to build a generative AI chatbot to respond to operator questions to improve knowledge management and operational efficiency. Roshan Shah, Vice President of the company, commented, “Our collaboration has resulted in an effective solution for productivity improvement and value creation.
Integration through Industrial Data Fabric (IDF)
IDF solutions help companies collect, store, contextualize, and leverage manufacturing data to make data an asset in complex environments; in the Infosys case study, IDF prevented over 800 minutes of downtime in 6 months, avoided 6 machine failures, and avoided 12 critical incidents The company has realized the following results.
4. ai innovation in supply chain optimization
PROPEL System at Georgia Tech
On July 10, Georgia Tech researchers unveiled PROPEL, an AI tool that dramatically reduces the time required for supply chain planning. The system combines machine learning and optimization techniques to help manufacturers make better decisions in less time.
In tests using actual industrial data from Kinaxis in Canada, PROPEL reduced the time required for high-quality planning by 88% and improved solution accuracy by more than 60% compared to conventional methods.
QAD’s AI Demand Planning Solution
On July 9, QAD announced how AI-driven demand forecasting is transforming supply chain strategies in the manufacturing industry. Overcoming the limitations of traditional forecasting methods, QAD incorporates real-time market signals, customer behavior, and supply chain variables into its forecasts, resulting in a more resilient and demand-driven approach.
Machine learning algorithms process huge data sets, identify patterns, and improve predictions over time, making predictions more responsive and accurate than traditional methods.
5. industrial AI trends and sustainability
Expansion of Industrial IoT (IIoT)
Enterprise IoT is expected to account for 72% of market revenue by 2028, up from 70% in 2023. This shift indicates that industry is rapidly investing in smarter, more connected technologies to drive next-generation automation.
Energy optimization and sustainability
AI technology plays an important role in sustainability and responsible resource management:
- Energy optimization: Smart automation systems analyze energy consumption patterns in real time to help reduce energy use without sacrificing output
- Waste Reduction: Predictive analytics and smart production planning minimize material waste
- Carbon Footprint Management: AI Helps Monitor and Track Carbon Emissions More Precisely
- Improved process efficiency: Intelligent systems continuously learn from operational data to fine-tune manufacturing processes
6. rapid adoption of AI in the life science manufacturing industry
Rockwell Automation’s 10th annual “State of Smart Manufacturing Report: Life Sciences Edition” survey of 143 life sciences manufacturing leaders in 15 countries revealed the following findings
- 95% are using or evaluating smart technologies
- 53% use AI for quality improvement
- 50% use AI to streamline operations
- 48% use AI to enhance cybersecurity
- 36% plan to invest in generative or causal AI
- 35% explore digital twin and simulation tools
Summary and Future Prospects
The week of July 13-19, 2025 will be recorded as a period of significant progress in the maturation and practical application of AI technology in the manufacturing industry. Practical applications of AI technology materialized in areas as diverse as the introduction of humanoid robots to the manufacturing floor, improvements in the accuracy of AI-driven quality control, the contribution of generative AI to operational efficiency, and innovations in supply chain optimization.
Of particular note is the fact that these technologies have moved beyond the mere proof-of-concept stage and are being operated and measured for results in actual manufacturing settings. Quantifiable results have been shown, such as the rapid adoption of robots in the Japanese automotive industry, demonstration results at Georgia-Pacific and Infosys, and an 88% time savings with the PROPEL system.
In the manufacturing industry of the future, the integration of AI technologies is expected to further accelerate, establishing a new manufacturing paradigm based on collaboration between humans and machines. Smart manufacturing that simultaneously achieves sustainability, efficiency, and quality improvement will be a decisive factor in global competitiveness.
Exhibit List
- TS2.tech – “Industrial Robotics & Automation Breakthroughs – June-July 2025”
https://ts2.tech/en/industrial- robotics-automation-breakthroughs-june-july-2025/ - Automation.com – “AI Adoption Surges in Life Sciences Manufacturing”
https://www.automation.com/en-us/articles/july-2025/ai-adoption-surges -life-sciences-manufacturing - UnitX Labs – “Streamlining Manufacturing Quality Control Using AI in 2025”
https://www.unitxlabs.com/resources/ai-quality-control- manufacturing-2025/ - IIoT World – “The Rise of Industrial AI: Automation Trends to Watch in 2025”
https://www.iiot-world.com/artificial-intelligence-ml/artificial- intelligence/industrial-ai-trends-2025/ - AI Insider – “Japan’s Car Industry Has Highest Robot Installations in Five Years”
https://theaiinsider.tech/2025/07/14/japans-car-industry-has- highest-robot-installations-in-five-years/ - AWS Industry Blog – “Empowering Manufacturing with Generative AI: Overcoming Industry Challenges with AWS”
https://aws.amazon.com/blogs/ industries/empowering-manufacturing-with-generative-ai-overcoming-industry-challenges-with-aws/ - QAD Blog – “AI in Demand Planning: Transforming Strategies for the Supply Chain”
https://www.qad.com/blog/2025/07/ai-in-demand-planning - Georgia Tech Research – “Georgia Tech AI Tool Cuts Supply Chain Planning from Hours to Minutes”
https://research.gatech.edu/georgia-tech-ai-tool- cuts-supply-chain-planning-hours-minutes - Reuters – “Nvidia, Foxconn in talks to deploy humanoid robots at Houston AI server making plant”
- International Federation of Robotics – World Robotics 2024 report
- ABB Robotics – Automatica 2025 press releases
- Rockwell Automation – “State of Smart Manufacturing Report: Life Sciences Edition” (10th annual)
