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.

Beleaguered Boeing Starliner's return to Earth — without the astronauts —is scheduled for tomorrow, Friday, September 5th.

Coordinate measuring machines (CMMs) play a crucial role in verifying the dimensions of manufactured parts with precision control. CMM controllers are central to coordinating movements and processing data, driving technological advancements in the metrology industry.

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.

This article is an adaptation of my popular presentation, “Beyond the Sticker & the Cert (Ensuring Better Measurements & Reducing Risk).” Product manufacturers, testing labs, and calibration labs often overlook the importance of thoroughly reviewing calibration certificates, leading to potential measurement inaccuracies and increased risks.

I kept waking up at 7:47 and also noticed the same time on the clock in the evenings. When I mentioned it to my niece, she said it happens to her too, at a different time of the day.

A paper released by the U.S. Energy Information Administration (EIA) addresses the importance of renewable energy in mitigating climate change and the challenges posed by the global energy crisis. It emphasizes the need to improve energy efficiency in response to increased energy consumption worldwide.

Leaders prioritize efficiency and productivity over quality management, compromising long-term standards, evident in the widespread adoption of operational excellence programs like Lean and Six Sigma.

In today's tech-driven world, companies use software to collect data, but the analysis can be flawed. Charts with only specification limits, arbitrarily chosen warning and action limits, and misused Process Behavior Charts contribute to misinterpretation.