October 13, 2023
Life as a quality professional is far from easy. We encounter an array of problems every day. As if this weren’t enough, in today’s environment, we’re bombarded with talk of AI, ML, data analytics, and more. But what does all this mean for quality professionals like us? Should we be concerned about the future of our profession? Let’s have a look from different perspectives:
Quality “Control” (Automated Quality Testing):
Especially if you’re involved in quality “control”, well… it’s better that you pay attention. With technology and AI advancing at lightning speed, this field is undergoing a significant transformation. Now, machine learning (ML) technology enables us to detect abnormalities through data analysis, employ vision detection, and even “listen” to a product to pinpoint failures. See the example from MHP Company here.
But hold on, this is just the beginning. Most of the AI applications still require huge expertise in ML, AI, and coding. However, what if creating these use cases become as user-friendly as “step-by-step help wizards”? Imagine the ability to initiate vision detection instantly with just a webcam and a mobile app. Or designing complex data analytics workflows by just drag and drop? Check KNIME, which require no coding at all.
“Preventive” Quality:
Okay I’ll admit, quality “control” might be a perfect match for AI. But what about data analytics that demand complex cognitive skills? Traditionally, as quality professionals, we’ve been trained to be effective statisticians, since, measurement points or parts to be tested were always limited. Thus, we had to rely on “statistical estimations” based on limited data. But with the aid of big data analytics, we can analyze all population of available data points. That means not just a couple of dozen but millions of data points. This is a breakthrough since it opens the door to identify patterns or even “predict” anomalies by analyzing extensive datasets that human testers might overlook.
Problem Solving:
We are not done with AI yet. It may sound like Darth Vader but, “Do not underestimate the power of generative AI” 😄. Let’s get specific; when we’re discussing traditional manufacturing processes like machining, there is an extensive repository of research and informative materials available on the internet. This means that with generative AI, you can easily access all the accumulation of knowhow just by writing the right prompts. Give it a try! You can even conduct a 5-Why analysis and create Ishikawa diagrams. While this won’t provide you with an instant solution like a magic pill, it will save you a substantial amount of time and give you a strong starting point for your analysis.
In conclusion, I personally don’t see AI as a threat to the quality profession. In fact, it will liberate quality professionals from boring and repetitive tasks. Last but not least, it will also enable us to thrive in the big data world. So, let’s embrace the opportunities that AI offers. Our roles are evolving, and it’s time for us to adapt, acquire new skills, and excel in this changing landscape! 🚀
I hope you found this article useful. So, dear digitalization ambassadors and quality professionals, are you experiencing the impact of AI in your field? I’d love to hear your opinions and experiences in the comments.
#AI #ML #Digitalization #quality #qualityexcellence #continuousimprovement
Zero Defect AI 