Industrial Robotics & Automation Breakthroughs – June–July 2025

How Artificial Intelligence is Transforming Manufacturing

Human-AI collaboration in manufacturing: insights from MIM 2025

Master Your Manufacturing Data To Supercharge AI - Industry Today

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This week showcased how AI helpers called **agentic AI** are transforming factories worldwide. These smart systems work alongside humans to make manufacturing faster, safer and more efficient.

Swiss company **ABB Robotics** unveiled three **heavy-duty robot arms** (IRB 6730S, IRB 6750S, IRB 6760) at Germany's Automatica show. These shelf-mounted robots can lift 350 kg and fit in tight spaces for car welding and plastic molding. ABB also launched the **Flexley Mover** - an autonomous cart using camera navigation to transport 1,500 kg loads with ±5 mm precision. ABB's president Marc Segura said **versatility** defines 2025 robots, combining AI, vision and mobility to switch tasks independently [1].

In Germany, **Siemens** expanded its **Industrial Copilots** - AI assistants for manufacturing. The Engineering Copilot already helps companies like **Thyssenkrupp** inspect electric car batteries. It automates sensor setup and report writing, meeting strict quality rules while freeing engineers for creative problem-solving. Siemens' Operations Copilot is being tested in factories for reliability. Separately, Siemens' **Senseye Predictive Maintenance** uses AI to monitor machine health. At Canadian pulp producer Mercer Celgar, it analyzes real-time temperature and vibration data across production lines, spotting problems early to reduce downtime [2].

Human-AI collaboration took center stage at Norway's MIM 2025 conference. Researchers and factory experts held a special "Sunset Session" symbolizing the shift to human-AI teamwork. Dr. Sotirios Panagou from NTNU university explained AI should **augment human skills**, not replace workers. Participants shared examples where AI handles repetitive tasks while humans focus on strategy and quality control. This approach makes factories more efficient while keeping jobs meaningful [3].

For AI to work well, **data quality** is essential. New research shows 75% of companies plan AI investments this year, but 98% face data challenges. Manufacturing involves complex data flows from supply chains to machines. **Master Data Management** systems solve this by cleaning and organizing information. Without good data, AI systems struggle to learn properly or make accurate predictions about machine health or production needs [4].

These developments highlight a global shift toward **AI partners** in manufacturing. From Swiss robots to German AI assistants and Norwegian teamwork ideas, factories are becoming places where humans and intelligent systems collaborate. The focus remains on AI handling routine jobs while people guide complex decisions, all supported by reliable data systems.

Looking ahead, the key trends are **versatile robots**, **AI copilots** for specialized tasks, **predictive maintenance**, and **ethical collaboration** between workers and machines. As one conference participant noted, the sunset of human-only manufacturing has given way to brighter teamwork dawn.

This week brought exciting advances in manufacturing with AI helpers. **ABB Robotics** launched new heavy-duty robot arms and a self-driving cart called **Flexley Mover** that carries 1,500 kg loads precisely [1]. These robots use **AI vision** and mobility to handle different factory jobs.

**Siemens** introduced **Industrial Copilots** that act as AI assistants for engineers. At Thyssenkrupp in Germany, these Copilots handle battery inspection reports automatically, freeing humans for complex work [2]. Siemens also has AI tools that predict machine breakdowns by watching temperature and vibration data.

Experts gathered in Norway to discuss **human-AI teamwork**. They agreed AI should **support workers** not replace them, taking over boring jobs while people make important decisions [3].

Good **data management** remains crucial for AI success. A report found 98% of companies struggle with messy data, so tools that organize manufacturing information are key [4].

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