Organizations are increasingly adopting Software as a Service (SaaS) for quality management, moving away from traditional on-premises systems due to its scalability and cost-effectiveness. By 2025, SaaS is projected to power 85% of all business applications, up from 70% in 2023.
As smart factories have grown to embrace more advanced technologies such as AI, machine learning, and smart sensors, they’ve also evolved to include more developed forms of metrology.
These advancements made our factories smarter by enabling systems to communicate with each other, share live data, and make decisions without human intervention.
As businesses increasingly rely on machine vision to enhance quality, improve productivity, and increase the bottom line, technology providers are relying more on industrial computing solutions that enable faster processing speeds and higher efficiency, or that support new tasks altogether.
As consumers demand higher-quality goods at steadily increasing volumes, the chief benefits of industrial automation — speed, accuracy, and consistency—become more important to businesses worldwide with each passing day.
In March 2023, after a GPT model passed a biology exam, Bill Gates noted on his blog that AI could save lives and address climate change. If AI can tackle such significant challenges, it can also help with issues faced by manufacturers, metrologists, and quality control professionals. This article will examine the challenges metrologists encounter and highlight potential AI-driven solutions in the metrology value chain.
Initially seen as science fiction, machine vision in manufacturing faced hesitance due to high costs and lack of awareness. However, interest has surged, shifting the focus from "Can it be done?" to "How will we do it?" This reflects significant transformative changes in the industry.
Automated processes are vital in industrial production, with robots handling finished products and sorting parts for quality assurance. Equipped with 3D cameras and machine vision, they accurately identify and grasp items from disordered bins.
Calibration is essential for maintaining quality and safety in industries like pharmaceuticals, food and beverage, and chemicals. The future looks to digital certificates and AI technology to make calibration processes faster and more efficient. This article discusses how AI is set to transform calibration.