Predictive Analytics in Manufacturing: Use Cases & Benefits
What is an emerging and promising new artificial intelligence-driven technology that can improve maintenance, quality control protocols, and operational efficiency for a manufacturing business? Professionals working in any supply chain can attest to the importance of predictive analytics for addressing the many challenges manufacturing firms face today. For instance, labor and material shortages can strain […]
Manufacturing Metrics: First Pass Yield Analysis and Improvement
First pass yield is a key performance indicator (KPI) that measures the successful manufacturing of a given product. It’s a great KPI for understanding how successfully a given manufacturing process is at creating functional products. Knowing that, it shouldn’t surprise you that quality control in electronics manufacturing is one of the best ways to improve […]
Make THINGS better.
Why, how, and what you should do to turn ML from a buzzword to reality for your production line For many years, my days at work looked very different than how they do today. That is not too surprising, considering I moved from designing and manufacturing Semiconductors & Opto-Electronics products to running a SW startup. […]
Ultimate Guide to Anomaly Detection in Manufacturing
Detecting anomalies at all is hard; it’s even harder when you don’t know what’s an ‘anomaly.’ So what is anomaly detection in manufacturing? Anomaly detection in manufacturing is the process of identifying data points that lie outside of the ‘norm’ and are rare in occurrence. In the manufacturing industry, anomalies usually are, or strongly indicate, defects […]
The next leap in bottom-line efficiency will be data-driven
Bottom Line Efficiency is the gold standard for measuring manufacturing productivity. Simply put — it identifies the percentage of manufacturing time that is truly productive. A score of 100% means you are manufacturing only good units, as fast as possible, with no stop time. so, where will the next major leap come from? data of […]
