Automation

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Quality teams now rely on a dense stack of tools: automated test frameworks, AI assisted test generation, self healing locators, visual testing, static analysis, and observability platforms. 

We treat mistakes like something to be engineered out of existence. Every roadmap promises fewer defects. Every system promises more precision. 

My career started with the early days of the semiconductor industry, and a few years later techies started dreaming of large-scale semiconductor memory. 

David Ryeson, Kaushik Shubhank, and Dr. Jan Nöcker of the Boston Consulting Group have written for Quality about AI and Quality 4.0.

The idea of the ‘dark factory’ has gained new attention as advances in robotics and AI accelerate. Stories range from fully automated automotive plants that operate around the clock and lights-out facilities in China, to experiments with humanoid robots on production lines, often framed as early signs of factories that no longer require people on the shop floor.

The application of AI in quality receives mixed responses: to some, it solves many problems; to others, it feels like Pandora’s box.

The relentless pace of innovation is redefining modern manufacturing. 

As someone focused on shaping the future of automation, I see four trends that will redefine how robots create value. 

Automation doesn't fix unstable processes—it scales them. This white paper explains how closed-loop process control, real-time SPC, and root-cause discipline create a zero-defect process state that enables reliable, lights-out manufacturing.

Congratulations to the winner of the Quality Caption Contest! See who won and what the winning caption is.