Automation

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As robots gain prevalence in manufacturing, emphasizing their safe use is vital. This includes understanding safety features, challenges, and best practices across all robot types, such as industrial, collaborative (cobots), autonomous mobile (AMRs), and humanoid robots, to navigate their complexities effectively.

ABB Robotics announced its sponsorship of MassRobotics, a leading innovation hub and startup accelerator for robotics in the United States.

The recent Boeing door plug failures highlight the urgent need for better quality control. Utilizing AI, particularly Large Vision Models (LVMs), offers a promising solution for enhancing quality assurance by providing unparalleled precision, efficiency, and scalability.

We explore two critical applications of AI and ML in quality management: predictive quality analytics and automated quality inspections.

For automation-focused companies, Autonomous Process Control (APC) isn’t just a tech advancement—it’s essential for achieving six sigma quality and boosting yields and profitability.

Quality assurance (QA) meets artificial intelligence (AI). How can they coexist safely? Integrating AI into QA brings opportunities and risks, especially in safety-critical environments. Balancing rigorous standards and human oversight is crucial.

In today’s industrial landscape, IO-Link enables seamless data exchange for efficient operations.

In modern manufacturing, it's crucial to validate parts immediately after manufacturing or assembly and detect defects before further processing. Automation in manufacturing has outpaced inspection processes, creating a challenge and opportunity for the metrology industry.

No robot can replace a person, but they can handle dull, dangerous, or repetitive tasks, freeing up employees for more fulfilling work. Businesses need to embrace robotics to efficiently adapt to production cycles and address supply chain backlogs and labor shortages.

The growing use of AI in manufacturing has revolutionized quality control. Traditional inspection methods struggle to keep pace with complex production processes, but AI augments accuracy and efficiency, upholding high-quality standards.