Items Tagged with 'machine learning'

The job market is struggling with fake job postings that mislead American job seekers and distort employment data. These listings, created to collect résumés or inflate company statistics, erode trust in online job platforms and create inefficiencies in the hiring process, worsening challenges for job seekers and the unemployed.

Companies face a pivotal decision when choosing a machine vision system: develop in-house or partner with a system integrator. Balancing control and expertise against potential challenges is essential, and key factors like expertise, time, budget, and complexity must be evaluated.

The assembly line, introduced by Henry Ford in 1913, connects product quality to component integrity. Many manufacturers now use computed tomography (CT) for pre-assembly inspections.

Optimism for 2025 is rising as logistics and supply chain sectors embrace digital transformation and automation to enhance resilience. Key trends shaping the industry are on the horizon.

A new type of database can facilitate cost-saving activities, such as predictive maintenance.

AI is revolutionizing quality control in electronics manufacturing by enhancing inspection processes and reducing costs. Anna-Katrina Shedletsky emphasized the power of machine learning and deep learning to automate tasks, improve product quality, and deliver significant ROI, making quality control the perfect starting point for AI implementation.

Despite advancements in intelligent automation, human oversight remains crucial in navigating complex warehouse environments. This article highlights the enduring role of humans in the future of robotics, emphasizing a human-centered approach to automation.

Regulatory bodies like the FDA and MHRA are adapting guidelines to accommodate the evolving AI landscape, stressing the importance of innovative compliance approaches alongside traditional software regulations, including audit trails, electronic records, and signatures.

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